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Quantitative Research - Science topic

This group is for quantitative researchers
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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 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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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 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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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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Natasha Chironda The face is also measured in three segments: from the hairline on the forehead to the region between the eyes, from the area between the eyes to the bottom of the nose, and from the bottom of the nose the bottom of the chin. When these measures are measured, a person is deemed more lovely if the numbers are equal.
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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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If you are interested in between place differences, your design will be very underpowered as you only have two places. If you want to ascertain whether place A is different on average from place B you will need lots of people in both places to draw conclusions with some certainty.
Jones, K. (1994). Analysing and designing extensive studies in which place matters: a comment on neighbourhood incivilities and the study of crime in place. Area, 79-81. https://www.jstor.org/stable/20003374
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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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Purposive sampling is an appropriate type of sampling in particular circumstances. It picks instances based on expert opinion or with a specific goal in mind. Purposive sampling is most commonly utilized when measuring a difficult-to-reach population.
Purposive sampling is used by researchers when they wish to reach a certain group of people, as all survey participants are chosen because they meet a specific profile.
Best Regards
Dr. Fatemeh Khozaei
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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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Dear All
Can you please, write some SSCI, SCI, and ESCI indexed journals which also CHARGE for publication? Number of issue per year and publication charges does not matter.
I really appreciate your suggestions.
Regards
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Generally, Paid Journals are not of good quality Index. However, I am providing list of publishers publish both paid and free but are of good Indexing
1. Elsevier
2. Taylor and Francis
3. Springer
4. Hindawi
5. Willey
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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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I agree with David L Morgan as well. Fallibilism is an important epistemological stance here (which you also find in American pragmatism, like the philosophical work of Charles Sanders Peirce). Also think about Karl Popper's criticism of logical positivism and the falsification principle he proposed to be used instead of the verification principle advocated by logical positivism. If you would like to read more about post positivism as a philosophical basis for doing social research (in this case, educational research), I can recommend a very helpful book (but remember that the term "post positivism" can be interpreted and used in different ways, as Kelvyn Jones above mentions): https://psycnet.apa.org/record/2000-08253-000 . Good luck with your work!
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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
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I am new in the research field. I haven't done any research yet before.
I am trying to do quantitative research on "Facebook addiction and its impact on academic performance". I have declared the variable (i think these are independent variables) for measuring addiction are:
  • Mood modification (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
  • Tolerance (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
  • Withdrawl (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
  • Conflicts (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
  • Relapse (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
  • Salience (5 Questions with 5 point Likert Scale -Strongly disagree to Strongly Agree)
(i have declared facebook addiction as a dependent variable (am I correct? please give a suggestion about this) )
  • And for academic performance, I have used 5 questions related to academic performance.
Some other information like age, qualification, marital status, gender, type of study, total spend time on Facebook per day, use of Facebook(for what?), time of usage (morning to night).
So, I am confused about which statistical analysis I need to choose. I want the suggestion about which tools I need to choose and how to complete my research? Please suggest to me the process of completing my research. I
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Before getting into all the technical details, please consider whether it makes common sense. If you are looking at the influence of something like Facebook addiction on academic performance then you need some way of measuring performance, and performance should be your dependent variable. If you are only measuring this once then there is a serious potential problem with your research: you appear to be assuming that there is no relationship between Facebook addiction and prior ability, which I suspect is not the case. For a variety of social factors I would expect that smarter people are less addicted to Facebook and therefore appear to perform better.
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I need the latest recommendations for using Krejcie and Morgan's (1970) formula.
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Hi Sidra. I think we still can use the Kriejie Morgan Table of Sampling. In my field town planning research..many of the researchers still using this table. I'm graduated my PhD with minor correction in 2019 & I used this table to justify my sample size.
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quantitative research
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Research always is researching what we don't know. Thus, a research project always comes from a research question, a research problem. It does not come from any kind of previous "research design" which means the methodological or technical tools mobilized to address the research question or problem. Therefore, there are no easier or harder "research design" processes since they depend on your capacity to elaborate an original research problem. This is the most difficult. It is easier to replicate available research published through papers, books, etc., but this not scientific research but a copy and paste system that cannot be accepted in Ph.D. thesis, academic papers, or conference proceedings. Research design is a process as follow: 1. presenting the background of the research; 2. presenting the research question; 3. Statement of the problem; 4. theoretical and conceptual framework; 5. Significance of the research; 6. Scope and limitation of the research.
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Hello all,
Thanks a lot for taking the time to read and respond to my question.
For my quantitative research on VR and regional journalism i measure the impact of Virtual Reality on presence, narrative understanding/recall, interest, enjoyment and news follow-up.
For (news) follow-up I have not yet found an appropriate measurement tool on a 5 or 7 point lIkert scale.
Is there anyone among you with a good suggestion?
Kind regards,
Rene Sluijk
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Yes, i agree. Behaviour, or in other words: i want to measure the attention participants had in the week(s) after the experiment. Did they follow the shown news, and where, after the experiment. To see if there is a difference in this behaviour for participants between the 2D and 360 condition.
Anyone a good suggestion?
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The quantitative descriptive study is supposed to cover 60-100 target participants however due to the pandemic the research locale had been provincewide instead of regionwide. It only yielded 20 respondents. Would you recommend that the study be continued as statistical treatment had been used as planned?
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Try to use online tools for research during pandemic.
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In quantitative research.
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A well-known downward-bias, due to partial observability of circumstances that affect individual outcome, and an upward bias, which depends on the econometric method used and the quality of the available data.
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Since epistemology is concerned with what is knowledge and how knowledge is acquired. My question is, how does epistemology guide research? For example, if I want to do a mixed-method combine qualitative and quantitative research, how does epistemology guide the research?
Thank you for your answers.
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I cannot understand this point of 'old fashioned', any scientist does know that the attitude with which looks at the results has a deep influence on his/her conclusion. The example of PCA is only one of the infinite cases in which in my work I stepped into 'epistemological' crucial points. If I think philosophy has no relevance in science I will be condamened to adopt a bad phylosophy and not to grasp the meaning of what I am doing. It is the overlook of epistemology that generated the actual repeatability crisis of biomedical sciences. The data 'do not speak by themselves' but only when solicitated by a theory oriented perspective and any obtained model takes with it the strengths and limitations of an epistemological (even if often unconscious) perspective.
So said, we must not consider as epistemology the books of 'professional epistemologists' (that in many cases never stepped into a real laboratory) but the reflections of real concerned scientists about the sense of what they are doing.
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What are the emerging areas of HRM or OB ,you have found during your studies? I am planning to conduct a quantitative research for my BSc degree. Since this is my first experience, can anyone help me with suggestions?
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As this will be your first piece of serious academic research using quantitive methods you should begin by finding say five excellent and highly regarded previous studies using quantitative methods in HR areas and ask questions like ‘how was the unit of analysis determined?’ How was statistical validity ensured?’ ‘How was interpretation of data undertaken?’ Once you understand the strengths and weaknesses of quantative methods you will be better able to select your research question.
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This construct - government support - is used as one of the variable in a quantitative research that seeks to investigate the construct as one of the multiple mediating varibale in a model
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I totally agree with the opinion of @Idarmis Knight Soto
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One expert says, a quantitative research is more "scientist" than a qualitative. In opposite way, off course some experts say that a qualitative more comprehensive compare to quantitative ?
Other expert says, okay we can use both approach.
Base on your knowledge and experience, which much better and useful?
Give me your opinion and evidence.
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To answer this question, let me repeat what I have written in my recording sheet during my bachelor study:
  • While Quantitative data collection methods produce numbers, Qualitative data collection methods produce words.
  • While Quantitative methods are more structured and allow for aggregation and generalization, Qualitative methods are more open and provide for depth and richness.
  • Quantitative and qualitative each has its strengths and weaknesses. Sometimes numbers are more useful; other times, narrative (qualitative data) are more useful. Oftentimes, a mix of quantitative and qualitative data provides the most useful information.
Now, the following points can help you to choose between the two methodologies:
  • The purpose of your evaluation.
  • The respondents (i.e. audience): how can they be reached?
  • Resources available: The choice between them ultimately depends upon the available resources like time, money, and analytical tools.
  • The needed types of information.
Furthermore, there are other factors that have a great effect like cultural considerations.
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I often read research articles that do not appropriate describe the sampling procedure. For example, the authors mention that the sampling was accidental or purposive but they don’t explain why they had only 10 participants or they say that the sampling was theoretical and describe the a priori established socio-demographic characteristics of their subjects.
I think that the sampling procedure is one of the most important elements of a research. I think that the research should be evaluated according to this procedure and I think that many pieces of research should be rejected because of sampling not being appropriate.
Please help me to clarify this and correct me if I am wrong:
The sampling procedure should state the sampling criteria and should justify the number of participants.
There are two kinds of sampling in social research: statistical – probability or non-probability (when the sampling criteria and the number of participants are established before entering the field according to some rigid sampling rules) and theoretical (when the sampling criteria and the number of participants are flexible, decided in the research process according to relevancy and saturation rules).
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Very useful discussion. I remember, the saying "it is better to study one rat for 1000 hrs rather than studying 1000 rats for one hr if you need to study behaviors of rats". But that particular rat should be selected carefully; not to choose a 'mad' or 'disabled' rat. Now by studying this carefully selected rat (theoretical sampling) we can generalize certain behavioral patterns of rats, as well as can gain a deep understanding of the behavior of rats, in that time and space. Observing 1000 rats, randomly or even purposively (statistical sampling), for one hour would help to identify a single or couple of features of rats, in that particular context. So, the sampling technique depends on the nature (not the purpose) of the research.
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I am Asian and I wanted to study Western Film because the subject that I want to study about is not being covered in local films.
It's a quantitative research and I am planning to use Semiotic Theory to frame my research. But is it possible to do so? because from my understanding, if to use Semiotic Theory, we need to have full understanding on that culture if we want to study about them.
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I am from cinema field, and the fact of proposing cultural heritage presentation throw fiction movies, made me discover during the whole four years of my study, every thing that is related to cultural heritage, either material or immatrial
what i want to say is YES! Yes you should discover another field and link it to yours, it may appear a bit stange in the beginning, but with research advance, every thing will be alright, knowledge evolution will take place on your mind, which will make your viewpoint to make your study more profound
as a conclusion, all the sience fields could be related to one another , the prodigies of history are in most cases multidisciplinar:
1-Avicenna was at the same time physician, astronomer, thinker, writer, of the Islamic Golden Age and father of early modern medicine
2-leonardo da vinci was at the same time a polymath, painter, draughtsman, engineer, scientist, theorist, sculptor, architect... and so on
........
if you will face a new field of science, linking it to your yet acquired knowledge, be sure that the result would be amazing ;)
Best luck
FRR
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How would you defend that your quantitative research results are representing the population even though you're using non-probability sampling? (which not everyone has the same opportunity to be used as a sample)
Please correct me if i'm wrong. Thank you!!
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Rahmawati -
There is another approach, probably more often used for establishment surveys. The model-based approach. See for example Royall, R.M.(1992), "The model based (prediction) approach to finite population sampling theory," Institute of Mathematical Statistics Lecture Notes - Monograph Series, Volume 17, pp. 225-240.  Available under Project Euclid, open access:
Here are a couple of textbooks:
Chambers, R, and Clark, R(2012), An Introduction to Model-Based Survey Sampling with Applications, Oxford Statistical Science Series
And
Valliant, R, Dorfman, A.H., and Royall, R.M.(2000), Finite Population Sampling and Inference: A Prediction Approach, Wiley Series in Probability and Statistics
The idea is that you use regression. So you have to have another data source for an independent variable on everything. That is the hard part in many cases, having the auxiliary data.
There are other books where the methods are "combined," as Ken Brewer has said, and he wrote this as well:
Brewer(2014), "Three controversies in the history of survey sampling," Survey Methodology, Dec 2013 -  Ken Brewer/Waksberg Award: 
When you can use regression, you have more choices for sampling because you have data on everything and know your population better. (You might look up "balanced sampling.") Sometimes auxiliary data are available from a recently past census. Sometimes there is administrative data available online for businesses, if you have that. But my guess is that you do not have the necessary auxiliary/regressor/predictor data available to you.
Best wishes - Jim
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Hello! I do regression analysis. I have predictor variables related to schools and students. For the output(dependent) variable Y I have marks of students for the specialized exam that they had in each year until 9th grade. So I have 9 output variables (they are the exam results of students in each grade). Can I make one predictor(dependent) variable out of those 9? If yes, how can I do this? Could you please give your recommendations)
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I was thinking about averaging all the marks and making one output out of them. But is it acceptable, or permitted? They are like:
Year 2 final exam mark
Year 3 fem
Year 4 fem
Etc...
I also have other output variables like PISA results for each school. I am going to do multivariate regression. I thougt that it would be better if I could lessen the number of Y variables for the same type of exams that were taken each year.
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Hi, can anyone recommend some textbooks on quantitative research in social sciences? I have the following three. Any one of them your favorite? Any others?
Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics
by Thomas R. Black
Quantitative Research Methods: From Theory To Publication 1st Edition
by Dr. Nicholas Harkiolakis (Author)
Quantitative and Statistical Research Methods: From Hypothesis to Results
by William E. Martin (Author), Krista D. Bridgmon (Author)
Thank you,
Shizuka
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I prefer a research-specific book for my quantitative inquiry. Tips;
For General-purpose:
1. Research Methods for Business-A skill-building approach-Uma Sekaran & Roger Bougie (Wiley).
2. Business research methods-Alan Bryman & Emma Bell (Oxford University Press).
3. Designing and using organizational surveys-Allan H. Church and Janine Waclawski.
For data analysis purpose:
1. Discovering statistics using SPSS-Andy Field (Sage), you can also consult Julie Pallant's Step by Step SPSS.
Hope this would be of help.
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Which of the methods (Qualitative or Quantitative) would you encourage upcoming scholars to use? Please, any reasons?
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Both are important for gaining different kinds of knowledge.
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I am currently conducting research and using a survey which contains 2 parts, 10 closed ended (Yes/No, multiple choice) questions and 5 open ended (opinions, follow on comments). Not all participants are required to complete the 5 open ended questions. I am aware that I am only using one research method so would assume this is primarily classed as quantitative research. However, after some reading, if my analyse on both sets of data collected are analysed separately (as quantitative data and qualitative) then combined/ compared, would this be classed as a mixed method?
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Robert Trevethan I disagree with you statement "that appending some open-ended questions to a set of fixed-choice questions on a survey in no way constitutes mixed-methods research."
In particular, if the qualitative content can be integrated with the quantitative content in ways that add to the overall understanding of the research question, then that is precisely the goal of mixed methods research. As I mentioned above, this is quite possible by using a QUAN --> qual explanatory sequential design in a survey that uses open-ended questions.
Ultimately, what matters most for mixed mentors is the purpose that the two types of data serve within the overall design, not when or how they were collected.
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15 Likert Scale Questions on a 5 Point Scale
Each Question can be grouped into 6 different industries or into 4 different groups.
Looking to analyze on an industry level and group level.
What methods are best ?
Looking to analyze on an individual question basis as well as a group level.
Im a beginner when it comes to qualitative research so any links that can help me find my way around the methods will help as well.
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I agree with the others about starting with factor analysis.
With regard to industry-level and group-level, a variable can only be included in an analysis once. So, if you want to conduct separate analyses at each level, that is one thing, but if you want to include both in the same analysis, that will not work.
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I am currently completing my dissertation on the the impact of salary expenditure on club performance using a quantitative research design.
I have used a simple linear regression with my predictor variable as Salary to Revenue ratio and my dependent variable as Revenue. Is this allowed, or does it violate the assumption of independence because the variables inherently use the same measures, i.e. revenue, and therefore are effectively related?
Appreciate any help and advice.
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Basically, your model is y = x/y + other covariates. You can't have your dependent variable (revenue) both as dependent and independent variables.
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Hello, I'm a student at the Cooperative University of Colombia, I'm initiating an investigation about the contributions of qualitative and quantitative research in the teacher training process. Could you recommend me study material about that (studies, books, essays)?
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unfortunately it is different in different countries, and in different universities. in our republic, for example, the more the better ((
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What is the appropriate sample method for Quantitative research (a Questionnaire (Likert measure))?
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A lot depends on your purpose and what you are trying to learn, as well as your field. Random/representative samples from a defined population are best, but they typically require a lot of resources/cost. In some fields most academic studies use nonrandom approaches which can be much less expensive. There are many ways to get such samples. I would look at papers in your domain to see the kinds of samples that people generally use.
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In order to measure research engagement of academicians, will it be wise to use the JES (Job engagement scale) by Rich et al. (2010) with modifications in words like (Research activities instead of Job)?
Adding a file for reference.
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Thank you very much.
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While I was a referee, I came across a study where 50 theses were examined according to their subjects, years and methods. I have done a similar preliminary study in the previous periods. However, I am still not sure about his method. Some consider it as a descriptive method, some call it qualitative research case study, some say quantitative research screening? Which one is more suitable?
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If it is a literature review, it makes sense to organize data according to subjects and chronology. It is very common in historiography and other social sciences.
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some institutes are awarding PhD as a student publish a review paper in some journal. is it appropriate at this level rather they should be encouraged to publish quantitative research paper?
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Ph. D basically in my opinion research oriented. Review or research article both research oriented but distinction innovation or invention. If any research or review innovation or invention oriented then eligible for ph. D. Next que some people says review not consider reason behind consider no lab work true but if nnovation then consider in ph. D because all bioinformatics chemoinformatics have no wet lab work that is similar as review..
But review must be innovation oriented.
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I have three papers for a review and I would like to seek some guidance on the epistemological positions.
I believe the first two are of a realist ontology with a positivism epidemiology however the third paper is a mixed methods paper and at this point I find it hard to distinguish am I right in assuming this paper is critical realism with an interpritivism epistemology .
The other two papers are based on quantitative research with hypothesise and findings looking to prove these hypothesise based on literature. The mixed methods is below
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Having two different data (Quan &Qan) deliberately does not mean necessarily is a mixed method, since, mixed method has its own research design criteria, which is taking aspects from positivism and interpretive positions as pragmatic paradigm. What is the reality and how do we know reality, are two different stories. Seemingly, the objective of paper is misleading the audience. Having quantitative results, following by qualitative procedure is not a mixed strategy, is only corroboration between quantitative results with qualitative findings, which paper resulted no difference. So, in my perspective the third paper is dealing with objective realities that exist, concerning human’s behavior and actions in corona virus crisis. As results falls into realist ontology with a post - positivism epidemiology.
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Hi Colleagues- What do you think about the following methodological issues:
1. Is it methodologically wrong to formulate quantitative research questionnaire based on inductive reasoning?
2. Is it mandatory to test hypothesis and/or theory in quantitative research? if no -what are the justifications? (please suggest an example of exemption)
Thanks in advance
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To your first question, it is not right to look for quantitative data for inductive analysis. Inductive analysis is driven by reasoning based on the data emerging from observations and participants views. Inductive analysis is therefore based on qualitative data. Quantitative means you are either testing an hypothesis or a theory that you already know something about. My opinion.
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Dear All,
Hope you are staying safe and sound.
I`m conducting a quantitative research in my PhD to test and validate a conceptual framework that has been developed based on the data from 26 interviews. I`m struggling with finding participants to fill the survey for the quantitative phase of my PhD as the inclusion criteria are too specific and narrow. I`m looking for social entrepreneurs who are either Co/founder, CEO, or managing director of social enterprises in Australia and use online communities related to their enterprise. I know that generally, it is said that I need to find at least 100 and preferably 150 participants for the quantitative research, however, it is a very difficult and challenging task for me to reach these numbers considering my limited time and resources.
I would appreciate if you could let me know how I can justify a sample size with between 50-70 participants and whether it is justifiable or not in a mixed-method research, in which interviews are the main data collection tool.
Thank you in advance for your assistance.
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Hi Behnam Abedin, you may consider using G*Power, a free power analysis program, to calculate your minimum sample size. Following is the reference article, download link and learning video. Hope it would help.
1. Reference article
Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior research methods, 41(4), 1149-1160.
2. Software Download (Windows and Mac)
3. YouTube: Using G*Power to Determine Sample Size
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In our research our title includes the impact of academic anxiety on academic performance. This one is a quantitative research. Our data is numeric.
Can someone suggest what can be the research design in this research given the fact that we are looking for the correlation coefficient and the regression coefficient...
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Thank you Mr.Morgan and Mr.Duffett!
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Can you sugggest a critique paper which is a quantitative research in live with Early Childhood Education?
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can quantitative research i.e. survey researches be exploratory in nature?
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The efa is quantitative and exploratory but generally exploratory researcg is qualitative and can be done through thematic or content analyis
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If we collect data through online survey (i.e. survey monkey, google form & etc.) then what should we called for sampling method? What are the sampling methods can be used for collecting data through online survey?
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I agree with Dennis Njung'e and Aruditya Jasrotia totally. Convenience sampling would do as well.
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When we can describe a Quantitative research or study as a PhD thesis?
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Dear Albandari Almutairi,
Your question has two (2) sides, relatively Quantitative Study and a PhD thesis.
If the findings of a study needs to be concretely supported with numerical findings from numerical data analyses, the study can be simply categorised as a quantitative study.
Generally, information can be in words and numerically transformed data. when a study has focused on numerical data to support its arguments, confirm hypothesis and explore the findings, such a study can be a quantitative study. On the other hand, if the study has focused on qualitative information to support its arguments, confirm hypothesis and explore the findings, such a study can be a qualitative study.
Whether the study can be considered for a PhD progression, it depends on the depth and quality of the investigation made in the study. If your quantitative investigation has sufficient depth of analyses and conclusion with well-designed research methods and approaches to explore new findings or methodology, such a study can be considered for a PhD dissertation purpose, subject to an authentication by acceptable scholars.
Hope this simple explanation can help you. Good luck in your studies.
Regards,
S. Senthilnathan.
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For non-natives, a manuscript is often rejected based on the reason that idea is not presented clearly. Please ask a native colleague to proofread it.
There is no offense to say that I am non-native and have been facing rejections for the same reason. Concerning this, please guide me 1): how do you ask someone from the same field to modify/proofread your manuscript? 2): how do you develop trust in that person? 3): if one agrees to proofread and modify, which rank he/she deserves on the authors' list? And 4): is it okay to approach a full professor to do this task?
Looking forward to answers and guidelines by experts
Note: I have a complete manuscript that requires a native speaker to work on it.
Details; quantitative research, time-lagged cross-sectional design, emotional labor, organizational behaviors, individual-level data, and bank employees.
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Dear Prof. Igor Gurkov,
Thanks for your guidelines and answers. Much appreciated your time and insights!
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Researchers are often in a dilemma: Which of research method, quantitative or qualitative, is better. Also, many of them argue the two terms can be used interchangeably. Qualitative research is explanatory and it is used to uncover trends in opinions. Quantitative research is used to quantify the issue by data which can be transformed into usable statistics. Do you feel qualitative research is better than quantitative research in predicting human behaviour in areas such as organisation behaviour ?
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We live in an age of quantification for profit.
Putting the economic interests aside, quantifying is about mass data, and qualitative data is about personal data. Predicting human behavior, in both cases, is about manipulating behavior to buy into something. As you also mentioned data (normal distribution), we should avoid to becoming captured by data.
Here, we arrive, at the moment of statistical learning theory.
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Dear all,
I am doing research into sexual harassment incidents among hotel employees. I will use quantitative research by using questionnaires and qualitative research by doing interviews. However, I am not sure which sampling method I should use for quantitative questionnaires.
I am thinking of simple sampling method or stratified sampling (both probability sampling since every person who is currently working in a hotel has an equal chance to participate in this questionnaire). However, probably more women have experienced sexual harassment. Therefore, I thought a stratisfied would be more reliable to use. however, I am curious of what you think.
I will use purposive sampling for the interviews since I would like to conduct interviews with only hotel en hr managers, to compare their perspectives with those of hotel employees
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Daniel Wright I will do research into the hotel industry in general, located in the Netherlands. I do think I will use stratisfied sampling for my online questionnaire to get an equal result from female and male and purposive sampling for my interviews with hotel managers. My sampling size is 382 respondents (95% confidential rate, 5% margin error. I am not familiar with non-respondents.. will take a look into this.
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I would like to study the effectiveness of counterterrorism strategies and I would like to know whether there is any quantitative and empirical method to do it.
Thank you!
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Thank you Cristian Ramos-Vera, your information was so valued for carrying my research project.
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I have observed two types of questionnaires in quantitative research.
First are Unidimensional and the second lack unidimentionality.
Questionnaire having Unidimensionality are passed through factor analysis to reach the status of scale such as effective leadership scale, but, is this a good practice to apply factor analysis when the questionnaire is not based on unidimentionale sub-variables such as leadership style (authoritative, democratic etc).
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Shamas Suleman Arshad, I'm sorry, but I don't understand your question, and I'm not sure that the above posts address it for you. I wonder whether you would consider rewriting your question a little bit so that it might be easier to help you.
Apart from that I hope it's OK if I point out that using the Kaiser criterion (eigenvalues > 1) to identify the number of factors in a dataset has been criticised for at least 30 years. For some reason, however, the Kaiser criterion keeps getting used (do researchers simply follow each other like sheep?) despite the scree test, or, better, parallel analysis being much more helpful.
In my experience, the Kaiser criterion often suggests there are more items in the data than is reasonable / interpretable, and the scree test is sometimes too ambiguous. As a result, I much prefer to use and recommend parallel analysis - particularly because it's very easy to perform.
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I am currently doing quantitative research that measures the impact of medical misinformation on the self-medication habits of millennials. It ha 2 independent variables which is the medical misinformation and the age bracket while my dependent is the self-medication habits.
My questionnaire are composed mostly of a Likert scale that measure the respondents exposure to a certain information that is answerable by always, sometime never.I also have another 5- point one that measure patients perception with agree, neutral,disagree type.
In this research I like to find out if exposure can impact their perception and incur change to their habit.
I'm currently confused on what test should I do
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Good point David
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Good day everyone. Regarding my question above, may i know how we can validate a WTP questionnaire in a quantitative research? The WTP questionnaire involve an open - ended question and some are choices questions.
If there is any experts here who has gone through the process, may i request if you could share your experiences here?
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Thank you Glenn Wayne Jones .
I think I can proceed from what you have mentioned above.
May i know if there is any papers/articles which have done the process, if you can suggest a few?
Thank you
Shamsinar
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Am looking for the research papers/articles/materials that someone tested validity in quantitative research.
Cheers!
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Can also refer to the article below :-
Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The qualitative report, 8(4), 597-607.
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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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If I understand your planned analysis correctly, there will be two main steps in the analysis, namely, the formation of the codes/categories (commonly dummy variables that indicate the presence of a particular idea or theme) that will be used in the content/theme analysis, and secondly the coding of each participant's response against each of these codes. It will be difficult to determine in any systematic manner the level of agreement between coders unless they are using the same set of coding categories.
To derive a commonly agreed upon set of coding categories, a common approach is for coders to use a randomly selected set of responses to separately form a set of coding categories, that are determined, not only by the responses, but also by the purpose of the research or any specific hyp