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Quantitative Research - Science topic

This group is for quantitative researchers
Questions related to Quantitative Research
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I am aiming to apply for a PhD with the following topic: Youth Awareness and Engagement with Degrowth Principles in Central and Eastern Europe – An Investigation of Climate Anxiety, Consumer Behaviour, Stakeholder Influence and Communication Strategies in Shaping Attitudes and Actions towards Degrowth
I have started to investigate research gaps and found that hardly any researches are dealing with the above topic, targeting CEE and youth. Do you find the topic novel, would you have any recommendations? I am aiming to do focus groups in related countries (ie Hungary, Slovakia, Romania, Bulgaria), quantitative research among youth upon focus group initiatives and a stakeholder mapping among NGOs, policy-makers, educational bodies, influencers to understand their strategies and narratives and their impact on youth in CEE. Thank you for your recommendations. Kind regards, Katalin
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Thank you, good luck on your intellectual journey.
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¿Qué ventajas y limitaciones presenta el uso de la investigación cuantitativa para evaluar la efectividad de las políticas sociales en comunidades marginadas?
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Las ventajas en la investigación cuantitativa sería la objetividad y precisión, ya que usa datos numéricos y análisis estadísticos lo que reduce la subjetividad. La repetibilidad, que se puede replicar los estudios para verificar la validez de los hallazgos, el análisis estadístico avanzado que usa herramientas matemáticas para identificar patrones, correlaciones y causalidades.
Como limitaciones de la investigación cuantitativa podemos encontrarnos la falta de profundidad la rigidez o la dificultad para estudiar contextos específicos.
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I find it hard to seek a survey questionnaire from the previous researches. Can someone help me where can I find ASQ for my quantitative research?
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It would help if you told us the topic you are seeking for your questionnaire.
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If I have done complete quantitative research, then complete qualitative research, then complete experimental research, and interpret all separately, then what will be my research design?
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From your descriptions, I think you are doing an explanatory deductive mixed-methods approach. Why? It seems you are following QUAN - QUAL pattern. In other words, it seems you are drawn to test some hypothesis through any qualitative methods, I assume maybe an interview?
This particular case could mean that you are pursuing something novel to understand a ground-breaking phenomenon, based on the review of the literature?
I hope this is of help.
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What is difference between Quantitative research and qualitative research ?
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I think to put it simply, both research aim to solve issues in entire humanities.
Quantitative research is generally associated with statistical analysis, aka math some kind of niches (e.g., survey questionnaire, Structural equation modelling, bayesian methods). Through these, you will approach your results objectively.
In contrast, qualitative research is about how do you reflect on human interactions, inner monologues, and self-reflexive practices through, let us say, interviews, autoethnography, duoethnography, action research, and so on. Therefore, it is highly subjective. But the good news is that qualitative research helps you navigate you through some extremely complicated questions related to human beings. In my case as a future educator, I am particularly amazed by qualitative inquiries.
Due to their opposing nature, you also need to consider the suitable paradigms they fit in for disparate inquiries.
I hope this helps.
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Quantitative research is a cornerstone of scientific inquiry, providing researchers with objective, numerical data to analyze patterns, test hypotheses, and derive conclusions. It is widely used across various disciplines such as social sciences, health sciences, economics, and business studies. Unlike qualitative research, which focuses on subjective insights, quantitative research uses structured tools and techniques to collect and analyze numerical data. This article explores the most common statistical tools and techniques used in quantitative research. These tools help researchers process data, identify relationships, and draw valid conclusions. By understanding and applying these statistical techniques, researchers can enhance the reliability and validity of their findings. Elements of Quantitative Research It's important to understand the key components of quantitative research. Quantitative research involves collecting numerical data and performing statistical analysis to test hypotheses or answer research questions. The fundamental steps in quantitative research include: 1. Defining a research question; formulate a clear, testable hypothesis. 2. Data collection; collect data using structured methods such as surveys, experiments, or observations. 3. Data analysis; apply statistical techniques to interpret the data collected. 4. Drawing conclusions; make inferences based on the results of the analysis.
Read more at: https://blog.hamnicwritingservices.com/blog-details/quantitative-research-statistical-tools-and-techniques #qualitativeresearch #statisticalanalysis #dataanalysis #researchproject
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ResearchGate is getting clogged with pointless queries to AIs. Maybe we should shut it down and just refer everyone to their favorite chatbot?
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Qualitative research is a powerful tool in the social sciences, humanities, education and other disciplines. Unlike quantitative research which focuses on numbers and statistical analysis, qualitative research seeks to understand the deeper meanings, experiences and perspectives of individuals and groups. It provides rich, detailed insights that help researchers gain a holistic understanding of complex phenomena. This article explores the best practices for conducting qualitative research. These practices guide you in designing, collecting, analyzing and presenting qualitative data in a way that ensures rigor, reliability and ethical integrity.
Qualitative research is a method of inquiry that focuses on exploring phenomena from a subjective, in-depth perspective. It is often used to investigate complex social, cultural, psychological or behavioral issues that cannot be easily quantified. Unlike quantitative research which collects numerical data and uses statistical methods to test hypotheses, qualitative research deals with non-numerical data such as interviews, focus groups, observations and textual analysis.
Characteristics of Qualitative Research
Qualitative research is often used to explore new areas of study where little prior knowledge exists. It emphasizes understanding the context in which the research occurs, such as the cultural, social or historical backdrop. Qualitative research design is flexible as it allows researchers to adapt their approach as they collect and analyze data. It also focuses on personal experiences, meanings and interpretations. Common qualitative research methods include; interviews (structured, semi-structured, or unstructured), focus groups, observations, case studies, ethnography, content analysis and narrative analysis.
Best Practices in Qualitative Research
When designing and conducting qualitative studies, you need to consider the following key practices to ensure the quality and rigor of your qualitative research.
· Clear research objectives; before beginning any qualitative study, it is crucial to clearly define the research objectives. These objectives should address the research question or problem that you aim to explore. A focused and well-defined research question will guide the design, data collection and analysis stages of the research. Your research question should be open-ended and exploratory to allow for detailed responses.
For example: Instead of asking, "How many people use social media?" a qualitative question would be, "How do individuals experience social media use in their daily lives?"
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This discussion seems very brief. However, the discussion in itself is comprehensively elaborate and might even suffice for a qualitative research methods handbook to enable both novice and experienced researchers gain meaningful insights into this very important but invaluable research approach.
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I've to make an analisys about a quantitative and empirical research about same topics in education but i didn't find something interesting
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The first step is accessing data, and if you are time-limited seeing what data are available in your local school system, country, etc. Most countries collect much education data, but do not have time to do all the analyses themselves.
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It will be a quantitative research. (For MA. thesis) in the context of Iran.
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I agree with Muhammad Amjad Bashir . Additionally, you can consider organising trial lessons where you demonstrate the effectiveness of certain teaching tools or materials (AI? audiovisual materials?). For instance, you could consider the use of AI tools to improve second language learning, or you could verify whether exposing students to film extracts in an L2 (with subtitles) can improve their language skills, etc.
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To keep it very precise, I would say: Qualitative Research explores the why and how, diving deep into emotions, opinions, and experiences. Quantitative Research focuses on the what and how much, giving us numbers, patterns, and trends.
You can also get some information here.
what are your insights on the topic?
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Qualitative research explores answers to “how”, “why” and “what” aspects of questions because it gives details of events and reasons of happenings. In the case of Quantitative research is concerned with quantification, replicability, objectivity which is tailored towards positivist idea of research.
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Te agradecere tu atención
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Au estoy empezando con primer trabajo de ivestigación
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This is necessary for my asm. I cannot find the articles/ documents/ researches/reports that includes the questionaires. Remenber it's quantitative researches.
I research about the impact of AI chatbot on customer experience in Uniqlo
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The following are few research papers that explore the impacts of AI chatbots on customer experiences that might help you:
  • AI-based chatbots in customer service and their effects on user compliance | Electronic Markets
  • Serving customers through chatbots: positive and negative effects on customer experience | Emerald Insight
  • https://sdmimd.ac.in/marketingconference2024/papers/IMC2466.pdf
  • AI-based chatbots in customer service and their effects on user compliance | Electronic Markets
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Me ha ingresado la duda respecto a un proyecto de investigación cualitativa se le tiene que formular una hipótesis tal cual se hace en las investigaciones cuantitativas. Sé que son supuestos teóricos objetivos en las experimentales, sin embargo en las que corresponden en la investigación-acción son subjetivas, digamos creencias a partir de las experiencias y desde esos hechos se analizan y se establecen lógicas...
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Okay if you are looking at Qualitative research the hypothesis as an example might say, To what extent is land line user friendly compare to mobile phones in telecommunication networks?
While in quantitative research you will say How many people use Land line compare to mobile phones?
Therefore assuming theoretically what you will be expecting from correspondence, will be depending on your experimental research correspondence, and what you obtain from their feedback will show the result of the correspondence subject to it. In other words analyzed, logics established..
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please I will be grateful if someone can assist me to modify my research objectives into a Quantitative objectives. on stand by
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You will need to say more about your research topic and design, so people can decide whether they can help you.
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with reference(s) please
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Yes, I agree with Prof Drs
Hanh Le and Carole C Tranchant that it is used to indicate both quantitative and qualitative research.
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I am looking for a finished quantitative research and I'm going to identify the following:
Research Title
Research Objectives
Statement of the Problem
Hypotheses of the Study
Respondents of the Study
Locale of the Study
Period/Duration of the Study
Theoretical Framework (if applicable)
Specific type of quantitative research design used. Description of the design.
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Hallo Krezziel Mae Odjoy
We are excited to invite scholars from around the globe to collaborate on our research article titled "Disharmony in the Implementation of Religious Education Policies for Students Adhering to Indigenous Beliefs in Indonesia."
The draft of our article is ready, and we are now seeking an international co-author to join us as a second author. This collaboration offers a unique opportunity to address a critical educational policy issue from a cross-cultural perspective, enriching the depth and impact of the research.
We would like to highlight that there are no fees associated with this collaboration. You will be credited as the second author in the publication, and we welcome your insights to further broaden the scope and reach of this work.
If you are interested in contributing to this research or have any questions, please feel free to get in touch. We look forward to a fruitful and meaningful collaboration.
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Based on this, identify the following:
Research Title
Research Objectives
Statement of the Problem
Hypotheses of the Study
Respondents of the Study
Locale of the Study
Period/Duration of the Study
Theoretical Framework (if applicable)
Specific type of quantitative research design used. Description of the design.
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A lot of government reports would fit that description. For example, you might look here: https://nces.ed.gov/pubsearch/
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Muñoz, Lucio, 2002.  Non-Traditional Research Methods and Regional Planning Needs in Developing Countries: Is There An Ideal Methodology?, In: THEOMAI, Issue 6, Second Semester, Argentina
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Thank you Mohamad for sharing the link in redalyc
Respectfully yours;
Lucio
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Instead of data saturation I will prefer the sample quantity selection as we do selection in quantitative research. Thank you
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in qualitative research since you will be researching and evaluating peoples lived experiences through an interview perhaps, it would be helpful to look at past research with similar or even the same research question and aim to collect a similar sample size! if we are talking about a new research idea you could either find similar studies and recruit your own number of participants evidenced on previous literature or find multiple studies and calculate the mean number of participants they had and that will be your sample size.
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Flavors of all tea leaves are determined by their respective chemical compositions. Are there any quantitative research on this?
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Thank you so much Professor Mirgorod. And thanks for introduce rutine to me.
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Need the questions for a quantitative research.
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LMX theory focuses on the relationship between leaders and their subordinates. One of the most widely used tools for measuring LMX is the LMX-7. questionnaire. You can separately collect data with multiple sources (leaders + subordinate) to get more insights. Here are the questions included in the LMX-7 scale ( you can modify according to research context):
1. LMX1. Do you know where you stand with your leader and do you usually know how satisfied your leader is with what you do?
- (1 = Rarely, 5 = Very Often)
2. LMX2. How well does your leader understand your job problems and needs?
- (1 = Not a Bit, 5 = A Great Deal)
3. LMX3. How well does your leader recognize your potential?
- (1 = Not at All, 5 = Fully)
4. LMX4. Regardless of how much formal authority he/she has built into his/her position, what are the chances that your leader would use his/her power to help you solve problems in your work?
- (1 = None, 5 = Very High)
5. LMX5. Again, regardless of the amount of formal authority your leader has, what are the chances that he/she would “bail you out” at his/her expense?
- (1 = None, 5 = Very High)
6.LMX6. I have enough confidence in my leader that I would defend and justify his/her decision if he/she were not present to do so.
- (1 = Strongly Disagree, 5 = Strongly Agree)
7. LMX7. How would you characterize your working relationship with your leader?
- (1 = Extremely Ineffective, 5 = Extremely Effective)
References:
- Graen, G. B., & Uhl-Bien, M. (1995). "Relationship-based approach to leadership: Development of leader-member exchange (LMX) theory of leadership over 25 years: Applying a multi-level multi-domain perspective." *The Leadership Quarterly*, 6(2), 219-247.
- Liden, R. C., & Maslyn, J. M. (1998). "Multidimensionality of leader-member exchange: An empirical assessment through scale development." *Journal of Management*, 24(1), 43-72.
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I got 384 (Cochran, 1977), if this is true, I would actually have to take 384 or even higher.
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If you have a particular statistical test in mind, then you might use the more recently developed approach to sample size of assessing the "power" of that test. The program g*power will do this for you.
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Hi,
I would like to publish research paper in journal that is in Scopus or Web of science data bases. Reserach is in education sciences and is a quantitative research. I don't have any budget (very limited budget) so it probbaly can not be an open access publication. As publication is part of a project i am willing to sacrifice journal quality (it can be in Q3 or Q4) over acceptence rate and review time. Maybe somone can recomend some journal that would align with my needs?
Thank you in advance!
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Thanks!
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I want questionnaire for quatitative research
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can you do a search on Pubmed MeSH with terms to generate what research already exists?
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What are your thoughts on using Likert-type scales with another instrument that must total 100? Specifically, I'm curious about using 5-point or 7-point Likert scales in the same study with an instrument that offers a scale where the participant must total 100 with four dimensions. The Organizational Culture Assessment Instrument (OCAI) is the survey I am referring to. Can you pair that with typical Likert-type scales such as the Minnesota Satisfaction Questionnaire (MSQ) which is a 5-item Likert-type scale?
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I am not familiar with the The Organizational Culture Assessment Instrument, but in general, measures that call for a fixed sum are hard to analyze because the separate sections are not independent. For example, imagine a simple version that requires a sum of 100 across only two dimensions, so that if a respondent scores dimension one at 51, then the score for dimension two is automatically forced to be 49. In this case, the two dimensions would be correlated 1.0 because the second one is a linear combination of the first ( Y = 100 - X ). Similar but more complex patterns apply when there are more than two dimensions.
You can read more about this issue under the heading of "ipsative measures."
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I would like to cordially invite all the young and experienced researches and scientist out there who are looking for collaborations on IOT, AI, ML , FL , blockchain techniques and data privacy, fake new detection to join my research lab. My lab is full of talented members ranging from industry experts to postDocs, undergrads to PhD scholars. It’s a common learning workspace
to support and guide all the qualitative and quantitate researches. Please check out my lab and works and share your thoughts or
feel free to connect with me for future collaborations.
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Please checkout my lab
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This question is looking for detailed, actionable advice on leveraging statistical tools in quantitative research to yield more reliable and accurate outcomes.
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The statistical tools should be used to give the results expected from the analysis. I didn't think you should leverage the tools to produce more reliable results. If you select the appropriate statistical test, then that should give you an accurate answer. If you use the wrong test, then the answer is not valid.
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In China you will find quantitative research results in the field of psychology or socialpsychology. Why is there very little or even no qualitatice explorative research to be found?
Thanks for your support
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António José Rodrigues Rebelo
I am galso imaghine there could be more or deeper understanding of this. I guess that some of it is rooted back to the first emperor and his political unit of the 7 parts of of China and his strategy of importance given to structure in all parts of society and culture. This has helped to unite the countries, to reign this big new China and establish time by time specific mode of perception life and siociety and to learn hereweith connected patterns of behaviou. These are still dominant in CHina
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Hi.. How do I analyze structured interview questions with experts in quantitative research? more specifically, questions used the Likert scale? any references
Thank you
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Thank you
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I am in a kind of dilemma between picking stratified sampling and convenience sampling techniques for my purely quantitative research. I am fully aware of convenience sampling being a non-probability sampling technique but is there a room I can use convenience sampling?
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To a large degree, the threats differ depending upon how the samples are taken within the strata. If you use convenience samples within each strata, there is little difference between the two methods other than the opportunity to compare the results across the strata. However, even that is questionable when the samples within the strata are not random as any differences could be attributed to sampling error. However, if the samples within the strata are randomly sampled, there is a major difference that being between an experiment and a descriptive study.
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Our research adviser told us to use specified terms for validity and reliability in qualitative research, since he referred to these terms as specific for quantitative research. To my understanding, validity and reliability are also used for qualitative data, but are defined differently.
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There is quite a bit of debate about whether the terms reliability and validity are appropriate for qualitative research. ss far as I can tell, however, the majority opinion is that they are not.
For example, reliability in quantitative research is based on the idea that two different measurements of the same phenomenon should return equivalent results. But in qualitative research we do not measure things, and we recognize that the subjectivity of the researcher can often lead to different insights when examining any aspect of social life.
For validity, in quantitative research, one common formulation is that we measure what we intend to measure in a way that minimizes bias. But in qualitative research, we are far more likely to be exploratory, with a goal of describing something in a meaningful way, other than separating out "true scores" from sources of bias.
In terms of how these terms are replaced in qualitative research, one of the most influential treatments is in Lincoln and Guba's 1985 book, Naturalistic Inquiry. You can find a nice summary of their ideas at:
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What are the key considerations, methodologies, and interpretive techniques for correctly applying and interpreting regression analysis in quantitative research, and how do they compare in terms of their accuracy, reliability, and suitability for different research contexts?
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The primary goal of regression analysis is to identify the significant predictors of a dependent variable. I have a YouTube video on how to carry it out and to interpret it.
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If we have a quantitative research confirming effect of one independent variable on one dependent variable in the presence of a moderating and a mediating variable and the construct of the scale/instrument/questionaire is correlates in such a way that all items are highly corelated to measure the same regressional relationship can we analyse cronbach alpha of all items together or do we have to do it seperately...? What makes more sense, suggestions are welcomed.
Regards
Sidra
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You should calculate one Cronbach's alpha for each of your separate scales.
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I would like to know about the future development of quantitative research on night light.
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One can estimate population densities.
For sure in regions where demographic data are non existent or of deplorable quality.
One has to train and validate the demographic model as well.
A validated model exists for child labour in the Ganghes catchment.
#NoMercyCV
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Hi people,
Are there any potential challenges I should be aware of when transitioning from qualitative research in my thesis to a career as a professor in a university setting?
Regards,
Joane R.
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If you are indeed planning on shifting your methods, one of the key things I would highlight about quantitative research is that is typically much more expensive than qualitative research. In particular, survey research requires large, high quality samples that are difficult to gather without external funding.
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Can I do this research as quantitative research?
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Scientifically, technically, and statistically, yes, you can
It depends on how you will define the variables studied and how you will express them.
Best wishes,
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This is for a quantitative research study.
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I would put it in an archive in a fully documented form. I see no need for a time limit. For example: https://www.data-archive.ac.uk/managing-data/standards-and-procedures/persistent-identifiers/qualitative-data/
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This is for a quantitative research study.
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Make sure you select a researcher from a known organisation and see a recent publication document. The nominee should be referenced by a known scientist; he or she should confirm their ethics.
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This will be for a quantitative research study via an online survey.
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Participants are free to withdraw at any given time for whatsoever reason/s. If this happens, their data should be excluded and deleted.
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I cannot apply modeling as it requires quantitative research, not qualitative research, as it requires a large sample. Is this true?
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You are correct: structural equation modeling is a statistical technique that typically requires a large sample.
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Why Quantitative research is better then qualitative research?
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Various versions of this questions have been asked before on RG, and the typical consensus is that your choice of methods depends on your research question. In other words, different methods have different strengths, so one is only "better" than another when you are referring to a specific goal that you want to reach.
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The Moderating Role of Peer Influence on Financial Literacy and Budgeting Behaviors
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Hi,
Some studies offer insights into social influence and financial literacy but don't focus on peer influence's moderating role in budgeting behaviours.
See study links below.
Hope this helps.
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If you were considering research in a developing import-dependent African country, what would be those contemporary areas of interest that hold both practical and theoretical contributions??? Your opinion is highly appreciated.
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marketing sensing, aligning organizational strategies, considering digital transformation and industry 4.0 perspectives considering customer 4.0, cultural orientation culture 4.0.
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While it's true that quantitative research is often associated with theory testing due to its emphasis on hypothesis testing and statistical analysis, it can also be utilized for theory building. Theory building involves developing new concepts, frameworks, or models to explain a phenomenon. How quantitative research can contribute to theory building?
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You are correct that quantitative research is often associated with theory testing, but it can also be used for theory building. Theory building involves developing new concepts, frameworks, or models to explain a phenomenon. Quantitative research can contribute to theory building in several ways:
Identifying patterns and relationships: Quantitative research can help identify patterns and relationships between variables that can be used to develop new theories or refine existing ones.
Testing theoretical models: Quantitative research can be used to test theoretical models by examining the relationships between variables predicted by the model.
Generating new hypotheses: Quantitative research can generate new hypotheses that can be tested in future studies.
Developing new measurement tools: Quantitative research can be used to develop new measurement tools that can be used to measure constructs that are important for theory building.
Providing empirical support for theories: Quantitative research can provide empirical support for theories by demonstrating that the relationships between variables predicted by the theory hold up in real-world settings.
In summary, quantitative research can contribute to theory building by identifying patterns and relationships, testing theoretical models, generating new hypotheses, developing new measurement tools, and providing empirical support for theories.
I hope this helps!
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Converting concepts into variables is related to the field of quantitative or qualitative research?
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Qualitative approaches do not generally use the language of variables, and many of them would not agree with using pre-conceived concepts as your starting point. In contrast, quantitative research frequently "operationalizes" concepts into measurable variables.
I think you need to be clear about what your goals are before you reach the point of considering concepts versus variables. For example, are you testing hypotheses or generating them?
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Actually I need to do a research for my bachelor degree and I can't find any relevant issues. Can you help me.
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Thank you a lot. You gave me a nice idea. Ajit Singh
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What are quantitative research designs?
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You could have a look at chapters 4 (experimental) and 5 (Observational designs) in
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Kindly mention the proposed methodology and objective. Open to discussion.
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Impact of green financing on inflation
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As part of my research I have conducted two survey questionnaires where the first one has closed ended questions and the second one has both closed and open ended questions. My doubt was whether to call this a Quantitative or Mixed Methods approach?
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From your reference to 2 surveys, the first closed question survey is part of your sampling methods, checking participant eligibility, and the the second is a qualitative research survey.
This makes your research qualitative as it is seeking knowledge of a person's socially constructed experience.
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As part of my research I have conducted two survey questionnaires where the first one has closed ended questions and the second one has both closed and open ended questions. My doubt was whether to call this a Quantitative or Mixed Methods approach?
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It depends on how you use the open-ended questions. For example, if you convert them to dummy variables according to what was or was not mentioned, then the overall project would remain quantitative. Alternatively, if you use that data to interpret the quantitative results, this could be a sequential explanatory ( QUAN --> qual) mixed methods design.
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As part of my research I have conducted two survey questionnaires where the first one has closed ended questions and the second one has both closed and open ended questions. My doubt was whether to call this a Quantitative or Mixed Methods approach?
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. . . you are correct if you mean survey [quant] --> qual --> results. The key is you must pick a detailed qualitative methodology/methods.
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Please guide me as how to write quantitative research methodology of management sciences for PhD with any research papers references, online workship/webinar etc
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Writing a quantitative research methodology for a Ph.D. in management sciences involves outlining the procedures and techniques you will use to collect and analyze data. Writing a quantitative research methodology involves providing a detailed description of the methods, instruments, and techniques you will use to collect and analyze quantitative data.
Remember to consult relevant research methodology literature and consult with your advisor or committee members for further guidance and to ensure your methodology aligns with the requirements of your specific research field and program.
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Suggestion for Instrument of Interpersonal conflict for quantitative research. In the current context, interpersonal conflict is between individuals of different groups and their affect is needed to be tested on intra group cohesion of the members of in-group.
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Very interested. My PhD dissertation abstract: "Principle-based dyadic skripts (PBDSs), as conceived in the Skripts Method described in this project, are proposed as an effective intervention in the prevention and resolution of interpersonal conflict and the promotion of relational well-being. The Skripts approach utilizes communication scripts that have been shown in the research literature and in clinical settings to prevent and resolve contention and improve relational connection. This project involves the development of a website (skripts.org) to facilitate dissemination of the Skripts communication tool. The resource is intended to train couples and individuals, as well as mental-health care providers such as therapists, clergy, and relationship coaches, in using PBDSs to facilitate low-conflict, high-affinity interactions. When launched, the website will provide a range of multimedia materials across a spectrum of interpersonal communication topics. This document describes implications of the findings, notes limitations of the project, proposes future avenues of research, and hypothesizes means for integrating the Skripts tool into faith-based contexts." Title: "A Program Resource Development Project Related to the Formation and Utilization of Principle-Based Dyadic Communication Skripts" (May 2023).
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Differences between Quantitative vs Qualitative Research.
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It can be mixed either qualitative first and then quantitative and vice versa.
Qualitative research as to do with trying to understand respondent perception about a particular focus of study. Meaning is open ended in nature. While the quantitative research is restricted to the researcher line of design. It is closed ended in nature and number driven.
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Hello
I am a new researcher in the fourth year of my PhD. I would like to know what career prospects we have after phD.
Skills: Qualitative research, Quantitative research.
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After completing a PHD, it is highly likely that one would end up as an Academic at a Higher Education or Research Institution. This can include Lecturer, Researcher, Mentoring etc. However there can be opportunities in Industry as well such as working in the Research and Development department, Consulting, Analyst, and any role that involves critical thinking. Seniority in positions will increase based on experience.
Also, immediately after completing PHD some students opt for what is known as a 'Post Doc' contract either at their university or another. This allows for them to gain academic experience whilst also being paid a salary.
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Do you believe that your understanding of qualitative or quantitative analysis brings you closer to the truth, given how you define truth? Please explain!
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As a pragmatist, I have wholly agnostic view toward issues of "truth." Instead, I would emphasize the classic research standard of a contribution to knowledge. So, if you have a meaningful research question and an appropriate way to answer it, then it doesn't matter whether you are doing qualitative or quantitative research.
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Could you help me in suggesting the topic or examples for my research for quantitative research that have four conceptual framework at least and their questionnaire? I could not find any of it and still have a lot to learn as i am still a students. Thank you for helping.
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Quantitative research is when you measure /quantity your observation. Like prevalence studies, proportion of male and female patients attending Dermatology opd etc.
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What sampling strategies are specifically for qualitative and quantitative research, respectively.
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Everything depends on your research questions and purposes. With that said, the gold standard in quantitative research is randomized and of sufficient power for the sampling frame/population. Qualitative research varies, though small samples and homogeneous are common [purposive is often used, but qualitative can also be many kinds of samples]. Again, look beyond rules of thumb--think sampling frame and population.
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Could it be an explanation, that qualitative research methods are cheaper (in Spain at least) than quantitative, and yield less profit for institutes? Or because is more simple, qualitative research is better understood by everyone?
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Quantitative research is not known or appreciated.
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There are two main types of research: Qualitative research and Quantitative research. Your research question will be based on the type of research you want to conduct and the type of data collection.
The first step in designing research involves identifying a gap and creating a focused research question.
Below is a list of common research questions that can be used in a dissertation. How research question can be created for a specific problem and a related data collection ?
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I am not sure that I would accept all of these as research questions. For starters, I see a hierarchy and redundancy there:
- Both your explanatory and evaluation questions are causal questions and thus explanatory. This is just hidden by the fact that "the impact of C" does not get a capital letter. Once you find the impact and name it "D", the question can be phrased (and answered) as an explanatory question.
- The exploratory questions you provide are also causal questions. I don't see how a strong distinction can be made between "What are the causes for C?" and "What factors affect C#s rate of growth?". The other one is obvious.
- The descriptive, comparative and correlational questions must be answered anyway if you want to answer a causal question, in your terms an exploratory, explanatory or evaluation question. They can be considered as necessary steps to answering these causal questions. I advise PhD students against reducing their PhD to these 'lesser questions'.
- I am not sure that your action-based question is a research question at all.
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Initially I thought of using Simple Random Sampling. However, I will be conducting my survey via a crowdsourcing method. As a result I was informed I must choose convenience sampling as my sampling strategy. However, all I read about convenience sampling include the high probability of sampling bias because I may receive completed surveys from respondents that are not in my population of interest. By submitting the demographics for respondents and needing an equal response number from both populations my first thought was strata sampling strategy. The study is a Quantitative Comparative Study. Please chime in and share your recommendations. Thank you
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If you are crowd sourcing your data, I don't see anyway to avoid doing convenience sampling.
Stratified sampling usually involves random sampling in pre-defined strata, so it does not including setting quotas for non-random samples. If you are worried about some groups being over-represented and you know what the population characteristics are, then you can post-weight your sample.
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In quantitative research, it is a must to apply theory to understand which variables we can use and how to measure them. Therefore, how many theories we can use in one paper? Is any idea more?
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Two main theories; measurement theory for the content domain of construct capture (the relationship between items and construct) and for hypothesis support the structural (relationship between constructs) a parental paradigm.
The following link may help:
(22) (PDF) Specifying the Problem of Measurement Models Misspecification in Management Sciences Literature (researchgate.net)
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Hi everyone,
I am working on ATC about the topic: "The impact of entrepreneurship education on entrepreneurial intention and entrepreneurial behavior" used quantitative research and trying to find academic keywords related to "entrepreneurial environment".
Also, I have just found two related theories used to explain above topic are (1) the theory of planned behavior (TPB) and (2) human capital theory.
1. Any keywords refer to "entrepreneurial environment" academically?
2. Any other "theories" could be relevant to the above topic?
I need your support and expertise.
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See the following attachment
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Is it statistically correct to relate an independent variable describing a particular set of individuals (as unit of analysis and respondent) with a dependent variable describing another set of individuals (as another unit of analysis and respondent)?
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I am not at all sure what you are asking. Could you elaborate with an example - research question and the form of the data would be helpful.
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In addition when population is small for example 120 and we wanted to employ quantitative research then which procedure is appropriate to extract sample.
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David: By "available data" I suppose you actually mean the entire population. Yes, to the point where the variance from the sample of n=N is zero.
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I am also looking for guidebooks, or any reference articles as a starting point in doing the discourse analysis.
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A quantitative research will be relevant ( *but not exclusive* ) to highlight the many points of details making a difference in some linguistic aspect.
A guidebook:
Deborah Schiffrin, _Approaches to Discourse_ (1994).
Deborah Schiffrin et al.,
_The handbook of Discourse Analysis_ (2005).
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I am an international student and I am studying sociology at McGill University.
I am interested in the sociology of immigration (in particular, immigration in Canada) and have read research papers about this topic. However, I feel I'm stuck generating possible research topics for my final Master's research paper (it will be 30 to 40 pages long).
Does anyone have any exciting immigration study subjects in Canada for a Master's research paper? I am looking for both qualitative and quantitative research topics.
I also would appreciate it if you could introduce any interesting papers about immigration, mainly, in Canada
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(PDF) Immigration: analysis, trends and outlook on the global research activity (researchgate.net)
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Hello,
I am doing quantitative research into motivations (6 types) and values (4 types) for circular use of materials (10 types). So motivations and values are independent variables and circular use dependent variable. Also I have a moderating variable, homeownership (4 types).
I am using SPSS.
What kind of analysis should I run? I was thinking of GLM multivariate, but how to incorporate the moderating effect?
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Hello Karismi,
Much of the answer depends on how you quantify scores for each of the ten circular use outcomes. As your question and Kelvin Jones' answer imply, the basic framework sounds like an anova (6 levels of IV motivation, 4 levels of IV values, 4 levels of proposed moderator, home ownership), with 96 cells and either 10 DVs or 10 univariate analyses or a repeated measures factor with 10 levels (scores). However, that requires your DV scores are rightly quantified as at least interval strength values.
If your attention is genuinely focused on the ensemble of 10 scores (and possible profile differences), then multivariate is likely the useful path. However, if your interest is really that of "which, if any, of these 10 scores is significantly influenced by IV1, IV2 & moderator," then univariate analyses, while repetitive, are likely the better option.
If there's something that we've missed here, please feel free to elaborate your query.
Good luck with your work.
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Use of questionnaires to collect basic information, mainly interviews are qualitative or quantitative?
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In general, a questionnaire that relied on open-ended items would be considered qualitative, but I agree that it is important to emphasize things such as interpretation and meaning as purposes in qualitative research.
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Knowing that variables normally examine in quantitative research, shall we use the term 'variables' in qualitative research as well? or better to use the term "concepts"?
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A variable usually implies something that has been measured, and which has variance. Neither of these apply to qualitative research in general, but if you are doing a form of content analysis where you count how often codes occur, then you are essentially treating those codes as variables.
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Is any body interested to be a co-author for this title article? I need some friend who knows quantitative research and systematic literature review. I would appreciate if anyone are interested. Please kindly email me at s40125@glos.ac.uk.
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Can you please send me your email?
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Kindly, professors..
Is it permissible to write the researcher’s opinion in the discussion part of the quantitative research results..
Please participate in the response, mentioning the scientific certificate obtained and the place of work in any educational institution.
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Thank you Burhan Hadi for the excellent question and experts for the good answers.
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why and how do we calculate Power calculation in quantitative research?
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This free manual provides an overall guide - it stress using a simulation approach to estimating power which is a very general one:
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I feel that most of the research on the digital marketing skills gap is qualitative (interview) research. I am looking for papers on quantitative research. Best,
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I don't know a paper about it, but we recently did a project with Kings Business School to address this quantitative skills gap.
The marketing students were challenged to optimise a digital shop to maximise sales for a product of their choice. Each group of students implemented different nudges within the simulated shop and create different adverts for participants to go through before the shopping simulation.
The top-performing student group increased sales for their chosen product by 3X, by a series of nudges, and adverts, compared to the control condition. It was really impressive work from the students, pulling together all the theories they had learnt to influence the 'shopper' experience.
The practical was supported by Gorilla Shop Builder, which makes it easy for students to do create this type of shopping simulation.
The lecturer and students are going to present their work at the BeOnline conference on Tuesday July 5th:
You might find it interesting!
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I am doing a qualitative research with interview as primary data and using thematic analysis. This is my first time doing investigator triangulation. I plan to code the transcriptions independently then compare the results afterward. However, I predict there will be some differences in results from each of the coders. How I resolve this? and which data should I use? in quantitative research, we can say the validity is for example 0.7. How can we say the validity in qualitative research?
Thank you.
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Oduneye Adenike. Discourse analysis : full narrative.
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I would be interested in what you see as the advantages and disadvantages of mixed-methods research in the social sciences. Do you do research with a mixture or combination of e.g. qualitative and quantitative research? Do you combine different quantitative or qualitative methods?
What challenges do you face (e.g., sampling, implementation, scope) and where do you see the limitations of the combination?
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mixed method design is time and resource consuming, budget constraints is another limitation...on the other hand mixed method research design brings in depth insights to the addressed research problem
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In an Exploratory Sequential Mixed Method Research, I have done qualitative research in stage 1.
I found some new construct, and discover linkage between the new found construct and the constructs under study. After that, based on the findings of qualitative research, I proposed a conceptual framework and I was able to offer some hypothesis.
After that I empirically verified few hypothesis by conducting a Quantitative research.
Now the thesis reviewer criticized that in Literature Review, I should discuss the conceptual framework and the relationships (proposed in the hypothesis). But I found that relationships after I concluded my qualitative research. How should I supposed to know them when I was writing the Literature review.
Please, someone guide me, where I am wrong.
Someone, please guide me, how to write literature review for Mixed method Research.
Regards,
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It is not unusual to discover links to the existing literature, once you have the results from an exploratory qualitative study. Unfortunately, there is no standard solution to how you should report this in either the qualitative or mixed methods fields.
I recommend to my students that when this occurs, they present it in the Discussion section. If your thesis supervisor is not willing to accept that as a compromise, then you will probably have to accept the power differential and do what you are being told to do -- for your thesis. Then, you will be free to do as you wish when you publish your research.
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I am conducting a research to assess whether or not skin tone influences the perception of facial attractiveness in people. I need help with the quantitative research instruments I can use.
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Generally for facial attractiveness people use single ratings (e.g., a 1 to 5 or 1 to 7 scale). These can be stable and consistent with relatively few raters. See:
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I have conducted a survey whereby I am looking at the differences in attitudes between university students and non-university students. I am now beginning to analyse the data but I'm not sure if I should have had a hypothesis and if it is necessary for analysing the data?
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Yes and No! For a quantitative study, you are going to test relationships. It is widespread among scholars to state hypotheses, however, as long as you study the associations, you can dismiss the statement of the hypotheses directly (but you must have some sorts of research question or study purpose to see relationships) as long as you can prove these associations are significant or not. Stating hypotheses can help readers understand what you mean and prevent confusion.
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We have a quantitative research study title of "The Effects of the COVID-19 Pandemic on the Online Purchasing Behavior of Senior High School Students".
In this study, our goal is to determine the effects as well as certain factors that make up for the changes in online purchasing behavior due to the COVID-19 pandemic on senior high school students.
What I would like to ask is what would our quantitative research design would be: descriptive, correlational, ex post facto, quasi-experimental, or experimental?
I would appreciate your thoughts and suggestions, thank you.
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You may consider the TPB model or the UTAUT model explaining online purchase intention among students. Also, mediators should be considered, such as satisfaction or brand image. The COVID-19 pandemic could be considered as a moderator.
All the best,
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I am a University student seeking support on the kind of research topic related to MBA -HROD for Hotel Industry. I am also looking for someone whom I can collaborate and can be my co-author of my study.
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The question about HR management in the hotel industry is very attractive to solve HR issues. Sometimes, ethical change management and talent management could be applied in this sector. Kindly visit the RG links.
All the best,
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I'm doing a research targeting primigravida teenage childbearing mothers in terms of knowing their coping strategies to correlate it with their demographic profile. I have also created a specific criteria regarding the respondents I am aiming for.
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Yes, I support the responses of Sachin Suknunan and Rodney Duffett .
Kind Regards,
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Hi everyone,
I have two study areas with the same characteristics same objectives. My target population is urban communities that visit the urban parks. In my study, these two urban parks suit my research scope.
What should be my sample size? For example, do I need to have the same sample size for both study areas etc.?
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It depends on your research question and the statistics you plan to run. If you want to compare means between the two parks, then perhaps 20-25 people per park would provide adequate power, depending on how much variability exists among people in each park. You can estimate the sample size needed for a given level of statistical power with a power analysis. If you want to compute more complex statistics, you will need larger, and in some cases much larger, samples. No, the sample sizes do not have to be the same per group.
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I am writing my thesis about stances and attitudes of mathematicians, regarding the use and utilization of Historical notes in secondary education mathematics school textbooks, in their teaching practices
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Reliability of a questionnaire means consistency of the results it renders. On the other hand, validity denotes the accuracy of the results’ inferences. A reliable and valid questionnaire is attained by ensuring the research concepts and models of selected questions/items are grounded in theory/experience, aligning with a study purpose.
A questionnaire’s reliability and validity can be assessed by examining its psychometric properties, encompassing reliability evidence (e.g., internal consistency) and validity evidence (e.g., content validity). It is recommended that you follow the psychometric evaluation standards established in your discipline. As an example, you might go through the standards by the Joint Committee on the Standards for Educational and Psychological Testing of AERA, APA, and NCME (2014), referenced below.
Joint Committee on the Standards for Educational and Psychological Testing of AERA, APA, and NCME. (2014). Standards for educational and psychological testing. American Educational Research Association. https://www.apa.org/science/programs/testing/standards#
Good luck,
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This is for a PhD-level Quantitative Research class, and I am confused over what test to run on the G*Power software.
It has to be an a priori, but would it be bivariate normal modal, multiple regression, t-test, etc...)
Do I need to determine the variables that will be measured, (depression, anxiety, obesity, etc...) before doing the test?
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I suggest to use t Test..in SPSS
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Hello,
I am writing a quantitative paper with some colleagues based on cluster analysis. The questionnaire had two open-ended questions and some of the quotes left by participants capture really well the "spirit" of each cluster.
However, I am not sure how to write about this in the methodology section, because it's not as if we've done a thematic or content analysis of all the quotes (well, we could do that, though our focus in the paper really is the quantitative part). Any ideas of we should frame this use of quotes in the methodology section? Should we just write that we included some quotes to better illustrate each cluster? Or would that not be acceptable in a top-tier tourism journal? Thank you in advance!
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Thank you Prof. Ines Carvalho then the way forward is to use the quotes as supplementing the quantitative results. Hope this helpful.
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We are currently doing correlational research (quantitative) about the gaming habits and academic performance of grade 6 pupils in just one school, that only consists of 150 grade 6 pupils. And we estimated that out of 150 only 35 pupils are only playing online games. Originally our research is about qualitative research. But our panelists suggested that we better conduct quantitative research.
We are not good at conducting quantitative research.
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Yes, you can, but I agree with Lasni Buddhibhashika Jayasooriya in that you could try a mixed method. For example, start off with systematic sampling, which would increase the generalization of your results as mentioned by David Eugene Booth
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I use eviews and SPSS for my research processing software. But which is the best among stata, eviews, SPSS, minitab, SEM, lisrel, ect.
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there is a lot of software for quantitative research. but this is dependent on you what do you want to do? and what level do you want to work at?
Generally, I think Eviews for Time series and Stata for Panel data for usual quantitative research are enough. but Python is better for more advanced quantitative research.
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Let us suppose that you do a SLR on topic A, and you do another SLR on topic B, and you'd like to bridge your findings, and try to relate the two to deduce conclusions? what are some available qualitative and quantitative research methodologies available for this ?
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The four basic steps: Define, Appraise, , Synthesis ,and Analysis.
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I've been asked to give feedback on a study that used a survey with the option for comments in each question. Some participants decided to share additional observations and thoughts for some questions. I've found that these additional comments carry rich qualitative data so I'm suggesting they analyze them and integrate them into the results (since they're currently not).
However, I'm not sure how to justify this methodologically (or even if it's appropriate). Even though these comments add insightful information about the participant's perceptions, they only account for a portion of them.
Options I'm currently considering:
(1) Use a common theme analysis for the qualitative data and relabel the study from quantitative to mixed-methods.
(2) Still define it as quantitative, but mention that some qualitative data was gathered as optional comments and analysed as well (would this be methodologically correct?).
(3) Do not use the qualitative data for the results, since it doesn't come from all participants.
Any thoughts?
Thank you very much in advance!
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Of course, they should be added and used (qualitatively) -- it's data, and respondents felt a need to add them, so we should report them. Since the researcher did not ask for comments, it doesn't make sense to call it a mixed method study. It's a quant study with supplemental comments. You add a section to the report describing qualitatively, what was said, including areas of convergence and divergence if the sample is large enough, and with some representative verbatims in any case. You should also include the % of respondents who added comments, for context.
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Hello dear fellow researchers. I am conducting a quantitative study (exploring causality between the dependent and independent variables) in which I have provided a theoretical framework informed by SLA research. Should a hypothsis (based on theory to account for any causality claims) be stated or would it be better to dispense with the theoretical framework at all if no hypothesis is stated? Advise please.
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My dissertation is on analysing particular processes/technology for the specific field and my suggestions for improvement.
  • What are the challenges if my study uses a descriptive research approach through a narrative review using thematic analysis?
  • Does it come under a theoretical or conceptual framework?
  • Any suggestion on alternative research methods that can be done in a short time?
N.B. I am new to research and sorry if I mentioned anything wrong.
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secondary sources become important if the study contribute to previous literature. It all depends on your research questions or objectives.
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It doesn't matter if it is in English or Spanish.
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As you are Spanish, I recommend classic manuals, understandable and unless it is Spanish (some, although they say as "Experimental Psychology", are valid for their objectives):
-Psicología Experimental; McGuigan; Ed. TRillas
-Diseño y Cálculo de Tests Estadísticos para Ensayos Clínicos y de Laboratorio; A. González; E.U.E de la Univ. Complutense de Madrid
-INvestigación Científica en CC de la Salud. Polit-Hungler. McGraw-Hill Interamericana
-Psicología Matemática I y II. Julio Seoane et al.Editorial UNED
-Fundamentos de Psicología Matemática.L. Jañez Escalada. Pirámide
-Psicología Matemática. Francis Isidro. Pirámide
-Los clásicos del Prof. Dr. Yela y los Clásicos del Prof. DR. Amón
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Hi,
I'm fairly novice in statistical inference and hypothesis testing and I have a basic understanding of regression models. I'm working on my first quantitative research in organizational behavior. My research model consists of 4 variables of interest and 3 hypotheses. Suppose we have the following:
H1: increase in X has a negative effect on Y
H2: Y and Z are correlated
H3: W moderates the negative effect of X on Y and therefore Z
Suppose I gather sufficient quantitative data for each of these variables for each subject. How do I formulate each of these hypotheses to test with statistical models? More broadly, what should I be learning to understand how to design and conduct a test for each of the hypotheses.
Do you recommend any straightforward topic or material so I can focus on learning the vital concepts? Most books and online courses tend to cover everything which means it would take a lot of time for me to just know which and which I should have studied and used.
Any advice would be really appreciated
sincerely,
Ashkan
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H1 and H2 could be examined by computing correlation coefficients and testing the null hypothesis that each correlation is zero in the population.
H3 (moderation) could be tested by using moderated regression where you regress Y on X and W and in addition include the interaction (product) term XW as a third predictor/independent variable to test the hypothesized moderation effect. (You can do the same for Z as an outcome variable.)
When the regression coefficient for the interaction term XW is significant, this means that there is a statistically significant moderation effect. To understand the meaning of the interaction, it useful to plot the relationship between X and Y at different levels of W. This is described in great detail with SPSS examples in Aiken & West's (1991) book on interactions in multiple regression. The procedure is somewhat complicated, also due to the fact that centering the predictors prior to forming the interaction term is often necessary for meaningful results. You therefore might want to study this topic in somewhat more detail before proceeding with your own analyses. You want to be sure that the results are correct and that they make sense and are easily interpretable.
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Hello,
I am planning to conduct a larger study in a male-dominated/masculine work environment. It will be a survey with several instruments to conduct quantitative research. May I ask for recommendations on surveys about gender equality, attitudes, violence etc.
Thank you,
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Here I attach something about it:
-Social Perception of Gender Violence; © MINISTRY OF HEALTH, SOCIAL SERVICES AND EQUALITY. Publications Service. E-mail: publications@msssi.es;
htpp: // Wwww. official publications.boe.es.
In it you will find a lot of documentation about it.
-The Questionnaire of Attitudes towards Gender Equality (CAIG): elaboration and psychometric study, by Benlloch, IM. . Yearbook of Psychology; 2003. vol. 34, 1: 101-123;
htpps: //www.raco. cato.article. download.
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How  am I going to highlight, that i have used the post positivism approach of philosophy in a quantitative based research related to Human resource?(i.e Literature? Methods? Hypothesis? Testing? Framework?) Means What sort of areas i will have to look to highlight, that this is the post positivism approach?
Please advice
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Post positivism can mean many different things and critical realism is very different from postmodernism which is itself differentiated.
I have written this piece on the practice of quantitative methods from a critical realist perspective
"A critical realist believes that there is an independent reality that science can study–each of us is not making it all up! It aims to develop deeper levels of explanation as causal necessity, not just regularity [a distinguishing feature of positivism] . It provides a logic of enquiry based on the fundamental formula:
Mechanism + Context = Outcomes
Mechanisms are not regularities but are potentially causal generative processes that operate in particular historical, local, or institutional contexts to produce particular patterns of outcomes."
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Hello everyone,
I'm currenlty writing my bachelor's thesis about the impacts of COVID-19 on the hotel sector in Germany, with the goal of developing a training manual for hotel management and entrepreneurs on how to cope with future pandemics.
One of my sub RQs is: What is the correlation between hotels responses to the pandemic and their occupancy rates?
How can I answer that questions if the hotels responses are based on qualitative data (interviews about entrepreneurial behaviour, e.g. one hotel said that in order to cope with the pandemic they increased their social media presence and improved their online appearance) and the occupancy rates are quantitative data?
Basically, my goal is to support my recommendations - which will be a training manual for hotel management and entrepreneurs on how to cope with future pandemics - by saying Hotel A did this and their occupancy rate increased (I'm obviously aware that correlation doesn't mean causation and this will also be one of the major limitations of my research, only using one hotel KPI).
Best,
Felix
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Suggestion: Code your qualitative data into a small number of categories that reflect the main ways hotels cope. Assuming there are several hotels that fall in each category, you could do a one-way analysis of variance to see if the mean occupancy rates differ among the category groups.
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For my dissertation, I asked my participant to estimate the weekly income of different occupations. As I did not provide a predetermined set or income range, I would assume that these open-ended questions as the participants could give any answer that came to their mind.
I am going to use the means for each occupation and see whether participant's social class or participant age has an effect on their income estimates (two-way ANOVA). For my method section I am trying to explain what types of questions I used but after doing some research, I am very unsure if I can use open-ended questions for quantitative analysis like that.
Hope anyone has advice for me :)
Thanks a lot,
Kristina
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One of maxims is proper prior planning Prevents Poor Performance. In this case if any number could be guessed what is the point of the question? Personally I don't think ANOVA on essentially random guesses is going to help. If the experiment is worth doing it is worth doing well. There are no Stati methods that can make bad data.good. My advice is go.to your advisor discuss it and if it's important redo the experiment. This happened to one of our students thanks.to last minute changes by a faculty member that destroyed her data. There was nothing to do but repeat it correctly.. Recall the above maxim. This is sometimes harsh but GIGO is another maxim in research. Best of luck, David Booth
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I need to do healthcare providers' compliance to the standard performance with observation, but difficult to get a reference for sample size determination.
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without knowing your intended calculations, this is impossible to determine. I would refrain from using often unattainable "rules of thumb" like x participants per variable. You will not only find a number of threads on RG that have dealt with this question, but a mountain of literature on the topic of statistical power. One of the most precise, yet difficult procedures would be a Monte Carlo simulation - I am struggling with those myself at the moment.
Good luck!
Marcel