Quantitative Analysis - Science method
In chemistry, quantitative analysis is the determination of the absolute or relative abundance (often expressed as a concentration) of one, several or all particular substance(s) present in a sample.
Questions related to Quantitative Analysis
Hi, we are researching a Comparative Analysis between Personality Traits among Career Interests and Self- determination. We've been trying so hard to find a related literature for personality traits and self-determination. Unfortunately, we still can't find one and we need it. I hope that you can help us thank you so much
How are you using ChatGPT and other generative AI in your research? Can it be used for quantitative analysis, to interpret quantitative results, sharpen arguments, or find citations. I know with citations it often 'hallucinates', or makes stuff up. Let me know how it is aiding your research.
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.
I, an assistant professor and researcher in Finance and FinTech, extend a warm invitation for collaborative research projects. My expertise lies in conducting quantitative analysis using SmartPLS, a powerful tool for modeling and analyzing complex data relationships.
If you are working on groundbreaking research in Finance, FinTech, or related Administrative and Financial Sciences and wish to explore the realms of quantitative analysis, I welcome the opportunity to collaborate as a co-author. Together, we can produce impactful research that contributes to our fields.
Please check my Google Scholars and Scopus
Mousa Ajouz (Ph.D)
Palestine Ahliya University
Laptop / pc recommendations for efficient writing, endnote, spss, data storage?
Hi, I did a quantitative analysis for my transgenic and control plants. The statistical analysis (p<0.05, One Way ANOVA, Turkey) showed that there are no significant differences between both plants. May I know how to indicate that data on the graph? Should I use the same alphabet on both plants to indicate it? Or there are other ways to indicate it?
I have already revised some of the data streams (WDI, WID or world income inequality, Unctadstat, Ford) where quite a large number of data (yearwise) are missing. How to recover the data? Can I use data cleaning or other methods when many years of data are missing? Or, is there national data streams such as Department of Statistics which can provide the missing ones?
I am conducting a study on the retail e-commerce segment in Nigeria and planning to do quantitative analysis using PLS-SEM [to help test mediating effects] but the population is less than 20 and so is the sample size.
The data type is Primary, collected through survey.
1. Can I do an acceptable/adequate analysis with a sample size of 13 respondents?
2. If no, what are my options to proceed considering population size is limited?
3. Would switching to a qualitative/descriptive approach be an option, and why?
4. What data analysis tool should be most ideal for use in my situation and considering I need to test for mediating effects of variables?
A researcher has deployed a qualitative approach in the data collection phase of research but has later decided to spice the analysis with some aspect of quantitative analysis. What can such mixing be called? Literature references will be appreciated.
Up until now didn't need to quantify minerals, a qualitative analysis was enough, but I wonder if needed what are the best and more feasible/acessible methods to quantify the percentage(even approximately) of different phases in a mineral precipitate?
I know there is one method that if we know that one ion is only present in a mineral in our sample, ththenan we may infer how much of that mineral is present, but is still based on suppositions so I wanted to avoid it and doesn't give a full picture.
The other one I know of is the Rietveld method using X-Ray Diffraction that allows quantification. But I guess if the sample has amorphous materials it leaves those minerals out right? and is it common to be able to perform this method in any XRD devices or only the most recent ones?
What other methods are there that maybe of use, that aren't excessively expensive or hard to find where to perform them? Even if it mainly gives us a distribution of the percentage of each of the known phases.
What does it mean when quantitative analysis of the compositional elements (from EDS analysis) gives the weight percentage and Atomic percentage of the elements with a negative sign, for example( -1.05) while the existence of this element from XRD analysis and the elemental mapping images?
Have you worked with standard scales/measures/instruments and have modified them in any way?
What modifications are acceptable to standard scales?
What are the steps to be taken in order to ensure these modifications:
- dropping of scale item(s)
- Changing the likert scale for responses: adding anchors, changing what the anchors read, etc.
- splitting double barrelled items into two
- Changing the order of the items.
I have ten regions and I created dummy variables for them. When I run my model one of them shows omitted, so I had to exclude the one showing omitted,and then I got significant result. But I need "the coefficient value of the excluded variable" to estimate Total Factor Productivity.
If possible, could you please explain how I can calculate it,dear colleagues.
I'm currently looking on the expression of specific isoforms from multiple candidate genes.
In order to confirm the expression of these isoforms, my first reaction was to prepare PCR primers enabling to amplify these isoforms either specifically or in duo (two primers for two amplifications of different sizes) and see if the expression of these isoforms changes between my experimental conditions.
However, this method will require further analysis by qPCR and sequencing to confirm the identity of these amplifications and to quantify their changes, which will take a large amount of time.
I was wondering if any faster method could exist to quantitatively analyse specific mRNA isoforms expression. The goal would be to not use omics strategy (as the candidate genes were identified this way) but to use a more targeted and precise approach to look at these specific genes of interest.
Thank you very much for your help.
I have some complex physiological data that varies quite a bit across participants. Best way to capture this variability? For more background...participants were exposed to different kinds of prejudice and some participants varied as to what type they responded more to. Any thoughts would be helpful.
I'm looking for papers that demonstrate/show how to quantitatively measure knowledge management (in general or part of it, like KM processes). In particular, I need to know which elements of a financial statement/balance sheet can be considered to offer an "objective measure" of KM within a company.
I really appreciate any help you can provide!
Please, note that I would like to study the relationship between servitization and KM. Given that I will measure servitization through panel data taken from companies' financial statements/balance sheets, I would like to find - in the financial statements/balance sheets - data that can allow me to measure the KM (or the CI, intended as a proxy for the KM). Do you have any suggestions according to this specific purpose? I was looking at the VAIC as well as the modified VAIC, but not sure it can be the best approach...
As part of my PhD I'm validating a patient-reported disease severity scale for patients with a rare condition. It assesses the severity across 5 symptom groups using a 0-5 likert rating. It's been adapted from a previously validated clinician-reported version to form a lay-reported version so that patients can report their own disease severity. The symptom groups are the same but the ways in which the response options are worded are different between the two questionnaires, which means this version needs validating. Initial testing done on the questionnaire suggests the isn't much differentiation across the response options on most of the items. I was thinking about interviewing patients, amending the questionnaire and then running some quantitative analyses to validate the scale.
I'm looking at using IRT, as the scale is not to be utilized in clinical settings, as there is already a validated clinician-reported tool to measure disease severity in the population. However the main problem I face is the patient population is incredibly small and I'm unlikely to get more than say 100 participants, all the stuff I'm reading on scale development says I need a lot more data otherwise the analysis won't have sufficient power.
Has anyone got any experience validating questionnaires using small sample sizes or has any advice regarding different validation strategies?
I read some nice articles explain the MSDO-MDSO for reducing number of conditions used within qualitative-comparative analysis. However, all of them lack the explanation for interpretation of tables created at the fourth phase of analysis - identification of relevant causal conditions - Outstanding pairs
The results were generated through online MSDO-MDSO software: version 1.1 - spring 2015 (jchr.be), available at the website https://compasss.org/software/
Thank you in advance!
I have panel data (T=10, N=26) where all variables are integrated I(1) with cross-section dependence. I applied Westerlund test and found no cointegration. So I proceeded with Pvar (Panel var) estimation. However, I want to confirm the robustness of my analysis by applying another estimation technique. Any advice?
I have bought a compound from macrocylics. I have analysed it using LC-MS where it shows multiple peaks. I have selected the peaks and did an area integration. The quantitative analysis of TIC gave be 85% purity whereas the product is endorsed as 95% pure.
I am attempting to perform XRD analysis on the 21R Sialon polytype, by seeing how much aluminium nitride is within each sample. Although, I cannot perform Rietveld refinements on this as I have no XRD data for pure 21R. I have been unable to find any data through research.
What data do I need to perform this task, and is it possible to perform Rietveld calculations if it does not exist within my Match database.
I am using Match! to attempt to perform these calculations.
If we use SmartPLS to analyse the structural equation modeling (SEM) then what could be the appropriate sample size? Is there any minimum and maximum sample size is required to analyse the PLS-SEM?
The synthesized hydroxyapatite powder can be doped with tricalcium phosphate. Can thermogravimetric analysis (TGA) be used for quantitative analysis of tricalcium phosphate in hydroxyapatite powders?
I have a set of items that would need to be slightly adapted to fit my research.
1) Let's assume I have the following item: "Introduce a new generation of products/services."
Is it possible to change the tense to: "introducED a new generation of products/services"?
2) Let's assume I have the following item: "We introduce a new generation of products/services."
Is it possible to change the personal pronoun from we to I: "I introduce a new generation of products/services."?
Are these two changes possible without any further testing?
If I use 320 sample size using a purposive sampling technique, how can validate the sample size for generalizing results? Are 320 responses could be statistically sufficient to generalize the results?
To define quantitative analysis as such in a mixed methods approach, is it necessary to include a regression analysis?
As we know, atomic and molecular emission lines of laser-induced breakdown spectra can be used for quantitative analysis, classification, etc. Does continuous radiation, which is usually subtracted in quantitative analysis, contain any useful physical information?Are there any applications for continuous radiation in LIBS?
I have seen papers where PSM has been performed using cross sectional and panel data. I want to know if PSM can be used for time series data too.
I also have a question that which quantitative method should one use for analysing the impact of a policy intervention. The dataset is time series in nature.
Could you please elaborate on the specific differences between scale development and index development (based on formative measurement) in the context of management research? Is it essential to use only the pre-defined or pre-tested scales to develop an index, such as brand equity index, brand relationship quality index? Suggest some relevant references.
Usually, mediators and moderators are tested in quantitative studies. However, can we test them in a qualitative study such as a case study?
I have searched this question myself but I am still confuse about it. In one article, I read that such quantitative analysis of ethylene glycol was done via HPLC. I am using ethylene glycol as carbon source to grow a bacterial strain. Now I wish to do spectrophotometry to measure its quantity in culture media at different intervals but I am not sure whether it is doable and what wavelength should be selected. I really need guidance on it from relevant expert.
Thanks in anticipation!
I have six kinds of compounds which I then tested for antioxidant activity using the DDPH assay and also anticancer activity on five types of cell lines, so I got two types of data groups:
1. Antioxidant activity data
2. Anticancer activity (5 types of cancer cell line)
Each data consisted of 3 replications. Which correlation test is the most appropriate to determine whether there is a relationship between the two activities?
Hello Seniors I hope you are doing well
Recently I've read some very good research articles. In those articles datasets were taken from V-Dem, Polity and Freedom House. Though they have shared the link of supplementary datasets and the process of how they analyzed these datasets in SPSS or R in brief but I couldn't understand and replicate these findings. It may be because I am not very good at quantitative data analysis.
So I want to know how could I better understand this Datasets analysis easily like V-Dem etc. Is there any good course online, lectures or conference video etc. Or good book?
Any help would be appreciated.
Thanks in anticipation.
I am using the Imodpoly algorithm with python to fit very noisy fluorescence data. However, in a few instances, I notice that changing the polynomial degree or using arpls algorithm will fit my data better. If I am running many data sets and my goal is to perform quantitative analysis and comparison, do I have to use the same fitting algorithm for each data set or can I mix and match algorithms for better fitting?
I plan to develop a semi-structured assessment tool and further validate it on a relatively small sample of below 50 (clinical sample). I have been asked by the research committee to consider factor analysis.
So in this context, I wanted to know if anyone has used regularized factor analysis for tool validation which is recommended for small sample sizes?
Hello everyone! Currently I'm busy with finalizing my master's thesis and due to a high drop-out rate in my intervention I was not able to conduct the initial analysis to test one of my hypotheses. Instead of doing a quantitative analysis, I have analyzed the answers to the evaluation questions after each part of the intervention. The purpose of the evaluation questions was only to evaluate how the participant perceived the intervention and not specifically related to the central construct I am examining in my paper (Psychological Flexibility), whereas the initial quantitative analysis would test whether the scores on the Psy-flex (measure for Psychological Flexibility) would improve after the intervention (compared to the first measurement).
Since I modified the analysis for this part, I had the following questions:
1. Can I still formulate the initial hypothesis in the introduction and write down in the data-analysis that a qualitative analysis is conducted due to small sample size?
- My supervisor says this is not possible and that I should formulate a hypothesis for the qualitative analysis in the introduction (while in this case it is exploratory right?). According to her I should exclude this initial hypothesis from the paper, although this was part of the initial plan.
2. Is the qualitative part not based on a exploratory research design and am I therefore not obliged to formulate a hypothesis?
- The purpose of the evaluation questions were to evaluate the part of the intervention. I did not construct specific questions for the specific skills of Psychological Flexibility (as in an interview with themes & coding etc.). According to my supervisor there should be specific hypothesis for it formulated in the introduction, since I can't say that the study is based on a mixed-method design otherwise (is this true? As long as I report which analyses I conduct in the data-analysis even when modified, I can still say that it is based on a mixed-method design right?) IMPORTANT NOTE: I already did a quantitative analysis before the intervention procedure, so therefore I thought that the combination of quantitative and qualitative design can be seen as mixed-method design.
I hope this explanation is clear for you to give me some advice on how to approach this. If not, ask me some questions and I will try to elaborate on it.
Thank you in advance!
I read some articles about statistical robustness of SmartPLS. However, I am not sure about the appropriateness of SmartPLS in the case of survey study involving a representative sample with adequate sample size. Any suggestions?
If I use SmartPLS to test the structural model then how I can measure the Goodness of Fit Index (GFI). What are the indices I need to observe for validating the research model?
I was given a role play as a financial analyst and the task is to perform a presentation on how to estimate the growth rate of a company by doing quantitative analysis using the company's financial statements.
Hence, which variables from the financial statement should I use to be able to estimate and calculate the projected growth rate?
There is a problem in my research with quantitative analysis of XRD patterns of glass-crystalline materials (including glass-ceramics and geopolymers).
Thanks to the discussion (https://www.researchgate.net/post/Does-anyone-know-how-to-quantify-C-S-H-in-cementitious-materials-using-XRD) I've found RieCalc program which calculate of rescaled phase fractions (including amorphous phases).
Unfortunately, I've faced two difficulties:
1. This program "could not be found" at http://www.geoscienze.unipd.it.
2. I'm not sure about its suitability for the analysis of geopolymers and glass-based materials.
Are there any other options to find a program for automatic quantitative analysis of crystalline and amorphous phases, and where can I find them?
I want to do quantitative analysis for vitamin A acetate raw material using HPLC method, but my sample cannot dissolve in many organic solvent such as methanol,ethanol,chloroform and hexane.
is there any recommended solvent that i can use for dissolve it ?
I have added 4 control variables namely firm size, board size, industry and firm age. do i have to collect data for the control variables? my research topic is impact of gender diversity on firm performance.
Let us suppose that we have an intervention, for example technology integration in the science classroom. Can we study what mediators could affect the results of the intervention, for example learning motivation? Can we study what moderators could affect the results of the intervention? And why.
For example, can we study how gender mediates the influence of the intervention on the learning otivation? or it would be better if we consider the interaction of gender and the intervention?
I am working on urban sustainability and my final objective is to propose a framework of urban sustainability. In this regard, I have used EFA first and want to use CFA, but I got to know that SEM has two methods i.e., CB-SEM and PLS-SEM. If I do not use CB-SEM or PLS-SEM, can I use just CFA in my study? If I can use it, please recommend me the procedures for conducting CFA.
I am looking for the latest data of population from authentic sources/government authorities for anytime between 2012-2021. It will be for my study area, South 24 Parganas district, West Bengal. Any leads/contacts for acquiring the same will be of great help for my research work.
hello every one
Can the independent variable be a constant
I want to Run MANOVA
I have the independent variable that is constant a budget during the year
and the opinion on the impact of the budget on quality of education (1 DV), on research (2DV), diplomatic rate (3dv), Employment rate(4DV) are the dependent variable
i Run the MANOVA but it looks like i have a lot of errors even if i tried to normalize Data,
SPSS gives me this message: this Box's Test of Equality of Covariance Matrices is not computed because there are less than two nonempty cells.
i tried to work with the discrim but i get the same errors
i get my data frow a survey it means that i can not change it , what other methods to analyse my data
I am trying to analyse the impact of quantified budgeting (historical budgeting, because it is the only method that is applicated in mycountry,the independent variable is historical budgeting>>its the budget>>> its continuous variable) on some universities performance indicators.
Thank you for the help
Hello Stata users. Please help.
When running Cronbach's Alpha test for internal consistency...
I have some missing values in the data set coded as 999.
Are they included in calculations or dismissed by Stata software as default?
Using other words do I have to mark some option in Stata before running Cronbach's alpha calculations so the software would dismiss missing values?
Could anybody clarify? Many thanks in advance.
Recently, I carried out some catalytic experiments of 1,2-dichlorobenzene, and I want to analyze the organic products from the catalytic process. And I want to make a mass balance base on the amount of Carbon. Actually, I had got some results with the help of Tenax adsorber/air pocket and a GC/MS with TD injection.
I can identify the abundant organic products with the help of GC/MS, however, I don't know their accurate amount, because I have no standard substances.
So, the question is coming. How to realize the quantitative analysis of organic products from the catalytic process of 1,2-dichlorobenzene?
Spatial and Temporal variations in Tea cultivation and Production in major tea growing regions in Sri Lanka. this is the research topic. under this topic, I hope to conduct mixed methodology both qualitative and quantitative. Can you give an idea of how to write the philosophy of this research? I mean can I mention this is a positivist approach. Because the major part is going to quantitative analysis.
My method for a quantitative analysis is ion pair chromatography with a gradient method. I tried to control any parameter that can affect on reproducibility, but my analysis is not reproducible. How can I have a reproducible analysis in this method?
I am writing an article where I am determining the effect of import substitution, should I include the diagnostic tests results. Or only the short run ECM and long run bound tests results are enough to interpret?
Imagine you have measured a series of curves, e.g. spectra of a dissolved compound of various concentrations, films with different thicknesses etc. Before you can retrieve the data, someone meddles with it, i.e. multiplies it with an unknown factor (or, alternatively, assume that your empty channel spectrum changes within the series), large enough so that it matters, but small enough that the data still seem to make sense.
Do you know a method that not only indicates that the curves have been altered, but also allows to retrieve the original/unflawed data?
Would you please share your kind opinion regarding this issue?
I am analyzing a Nationally representative survey and I wonder if I recode the categorical variables like gender or education, it would mess the weights!
each row of the data has a weight, strata, and PSU. does recoding the categorical variables impact the results of my regression analysis?
Hello Every one I just need a help for choosing the write test for my Data I have 2 quantitative dependant variable and one qualitative variable with one level modalities ( normally the variable has 4 modalities but what is Applicable in Morocco is one of them I am speaking about the funding method of research) can I use in this way A MANCOVA test or Not???
If not what test should I use ? And why
- 2 dependent quantitative variable
- 1 independent qualitative variable with one level ( or one modality)
I want to count these fragments for image analysis of autolysis. Please suggest good software, it is so critical in my work.
Generally HPLC, we can use it for qualitative and quantitative analysis.
What is the main difference while using it with PDA or with MS detector?
What are the advantages of MS to PDA and vis-versa?
Dear RG community,
I have analysed several flat sections of romanechite (Ba,H2O)2Mn5O10 by EPMA to have quantitative analyses. Romanechite would normally have about 15-17wt.% BaO but instead we have 2-3 wt.% BaO (see analysis bellow), which is a huge difference. We have rather the same results using EDS analysis of the same samples (4-5 wt.%Ba). Finally, when we did ICP-MS (whole rock sample of romanechite), the Ba content is "normal" with 14 wt.% (14,000 ppm) Ba.
I'm wondering why we have such a big upset when using EPMA. Maybe it is due to the standard (benitoite) we used or the ZAF calculation method. If you have any idea...
Thank you !
Element Standard Mass(%) ZAF Fac. Z A F
BaO Benitoite 37.08 0.9158 1.0078 0.9087 1
No. SiO2 Al2O3 BaO As2O5 Fe2O3 MnO2 Na2O MgO CaO K2O PbO SrO ZnO WO3 CuO CoO Total
Sample1 0.051 0.358 2.854 0.123 0.232 62.265 0.01 0.004 0.2 0.02 0 0.166 0 1.937 0.078 0.089 68.387
I have heard some academics argue that t-test can only be used for hypothesis testing. That it is too weak a tool to be used to analyse a specific objective when carrying out an academic research. For example, is t-test an appropriate analytical tool to determine the effect of credit on farm output?
I hope you had a wonderful weekend. At the moment Im in the later stages of planning a hopefully good quantitative article in entrepreneurship. I will use connections in the industry (to do the dirty work of actually convincing people to participate )where Im active and my question is, what do you deem to be an acceptable sample size for a questionnaire about decision making, connecting into other areas?
It is a relatively small business community in our country so sample size can not be 1000, if yes there must be a discussion about expanding the geographical area.I know what the literature says but what is your experience regarding minimum sample size in different level journals. No need to say Im a qualitative researcher seeking to make an excursion into enemy territory :-)
Thank you so much for your input in advance.
Best wishes Henrik
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.
Thank you very much in advance!
Power and gas retailers, are exposed to a variety of risks when selling to domestic customers. Many of these risks arise from the fact that customers are offered a fixed price, while the retailer must purchase the gas and power to supply their customers from the wholesale markets. The risk associated with offering fixed price contracts is exacerbated by correlations between demand and market prices. For example, during a cold spell gas demand increases and wholesale prices tend to rise, whilst during milder weather demand falls and wholesale prices reduce.
I'm trying to design a questionnaire that gets at two constructs for educational practitioners: 1) beliefs about teaching and learning, and 2) interpretations of an educational reform.
For the latter, I'm not trying to get at attitudes (what do you think of the reform?) but rather the beliefs, logics, assumptions that practitioners think inhere in the reform (why is the reform happening/what is it about/what does it propose, educationally?)
Now, I realize this is a bit confusing. As an example, I'd hope to juxtapose something like: "students should learn/learn best through memorization". For (1), the respondent would answer "I believe this is true." For (2), though, I'm struggling -- something like "I think this is the case for/intention of X new reform."
I've been trying to find examples of such comparative surveys focusing on perceptions/interpretations of innovation, reform, change, etc. But I'm coming up short.
Would it be fare to frame interpretations, cognitively, as "expectations" ("with X new reform, I expect this to be true") or social demands ("I think my school wants me to do this")?
Any thoughts are much appreciated!
(PS - To complicate this further, I intend to make a similar survey for students!)