Science method

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.
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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
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In my research on college sports, boys who participate in team sports tend to have more wins. Girls who participate in individually competitive sports like tennis tend to win more. It fits Durkheim's so-called theory of Suicide. And the data set I worked with covered 12 years of college sports at one college.
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"Breaking the Issue: Quantitative Analysis of Public Perception and Reaction to Cancel Culture Incidents on Twitter"
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1. to explore the behavioural influential factors of public perception towards reaction on cancelling cultural incidents in the Twitter platform.
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Dear Colleagues
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.
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I am using ChatGPT to analyze my qualitative data. My goal is to find the key themes in the data without the time-consuming and tedious process of coding.
As for hallucinations, I have not encountered this problem, but there is no substitute for being familiar with your data and your field of research.
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If you were considering research in a developing import-dependent African country, what would be those contemporary areas of interest that hold both practical and theoretical contributions??? Your opinion is highly appreciated.
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marketing sensing, aligning organizational strategies, considering digital transformation and industry 4.0 perspectives considering customer 4.0, cultural orientation culture 4.0.
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Quantitative Analysis for PFAS Compound
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Yes, it is possible to assess Per- and Polyfluoroalkyl Substances (PFAS) using an Agilent 6420 LC/MS/MS system without the Jet Stream (AJS) ion source. The Agilent 6420 LC/MS/MS system is equipped with an Electrospray Ionization (ESI) source, which is commonly used for analyzing a wide range of compounds, including PFAS.
While the Jet Stream (AJS) technology can enhance sensitivity and performance, it is not strictly required for PFAS analysis. ESI is a widely used ionization technique that generates ions from a solution through the application of an electric field. It produces ions that are suitable for many compounds, including PFAS, without the need for Jet Stream technology.
Here are the steps to perform PFAS analysis on an Agilent 6420 LC/MS/MS system without the Jet Stream ion source:
  1. Method Development:Develop a suitable LC/MS/MS method for PFAS analysis. This involves optimizing the chromatographic conditions, mobile phase composition, and gradient profile.
  2. Sample Preparation:Prepare your PFAS samples according to established protocols. Sample preparation methods may include solid-phase extraction (SPE), liquid-liquid extraction (LLE), or other extraction techniques depending on the sample matrix.
  3. Instrument Setup:Set up your Agilent 6420 LC/MS/MS system without using the Jet Stream ion source. Ensure that the system is properly calibrated and configured for the chosen ionization mode (typically negative ion mode for PFAS analysis).
  4. Ionization Mode:PFAS are typically analyzed in negative ion mode due to their negative charge characteristics. This generates negatively charged ions that are suitable for ESI analysis.
  5. Tune Parameters:Optimize the ESI parameters such as capillary voltage, nebulizer gas flow, drying gas flow, and temperature to achieve the best ionization efficiency and sensitivity for your PFAS compounds.
  6. Calibration and Quality Control Samples:Prepare calibration standards and quality control samples containing known concentrations of your target PFAS compounds. These will be used to establish the calibration curve and assess the accuracy and precision of your analysis.
  7. Data Acquisition and Analysis:Inject your prepared samples into the LC/MS/MS system and acquire data using the optimized method. Process the data using appropriate software to quantify the PFAS compounds based on the calibration curve.
While Jet Stream technology can enhance sensitivity, it's not mandatory for PFAS analysis on the Agilent 6420 LC/MS/MS system. With proper method development, sample preparation, and optimization of ESI parameters, you can successfully analyze PFAS using the standard ESI ion source available on the instrument. Anika Nawar
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Attention Scholars,
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
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I am open for research collaboration
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Laptop / pc recommendations for efficient writing, endnote, spss, data storage?
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Processor: intel core 5 or Ryzen 5 or higher
RAM: 8 GB or more
Storage: 256/512 SSD and 1 or 2 TB HDD
SSD can be used for loading OS and programmes. HDD is the safer option for data storage.
Screen size: 14" or 15.6"
14" is more compact, but 15.6 provides enough screen space. Choose the size according to your convenience.
You can buy an additional screen (22" or higher) to connect externally and keep it in your office or home. That will be a great option when you are working with huge data, charts etc.
New laptops have enough features, including USB ports, card reader, backlit keyboard etc.
Graphics cards: A 2GB graphics card would be an additional option, and it will definitely help to handle graphics data if you need to work with 3D graphics and videos. The more 'GB' (4GB, 6 GB), the better the graphics performance. But the size of the laptop will be increased. If you need a slim laptop with greater graphics, you may need to pay a higher amount.
I think for your need, 2 GB graphics would be enough.
I recommend buying an external HDD (not SSD) for data backup. I think 2 TB would be enough. (WD or Seagate are good, ensure password protection feature)
The laptop brand is a personal choice.
If you are comfortable with Apple, go for Macbook. But in my personal experience, the device is so limiting yet efficient!!
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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?
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1- Use t-test to identify the statistical differences b/w your transgenic plants and WT, and use asterik if you find any sig differences.
2- Sometime transgenic plants cannot be the mutants and can behave like WT. So confirm their mutagenicity as well, along with their transgenicity.
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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?
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The best way to find data is to dig into the national bureaus of a country regarding any variable. You can use VPN and institutional email if they are not providing access.
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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?
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For a partial regression model, a number of 50 subjects is sufficient. However, for scientific research, I recommend respecting the ratio 1:10 (ie 10 subjects per variable).
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Do you believe that your understanding of qualitative or quantitative analysis brings you closer to the truth, given how you define truth? Please explain!
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Everything we see, think, feel, touch, etc. is false, only the truth knows itself.
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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.
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You do not say anything about where the quantitative data came from. Is it a quantitative analysis of the qualitative data? If so, this called quantizing (or quantizing) the qualitative data.
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Greetings.
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.
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Generally, qualitative and quantitative determination of mineral phases is performed by using X-ray diffraction (XRD) methods.
Even amorphous content can be quantified using an internal or external standard. Another variant to deal with even multiple semi-amorphous phases is the so called PONKCS method.
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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?
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Negative sign means absence of element (usually because of poor understanding of the method by operator). And "XRD analysis and the elemental mapping" usually cannot prove presence of an element. Use spectra to make a qualitative analysis before conducting a quantitative one.
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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.
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There are several guidelines, including:
• Using the least burdensome approach when developing, modifying, or adapting instruments.
• Obtaining permission from the developer of the scale before modifying it.
• Ensuring that the modifications do not affect the validity or reliability of the instrument.
• Conducting content and construct validation to ensure that the modified instrument is still measuring what it intends to measure.
• Following established standards and measurements to ensure the modified instrument is accurate and reliable.
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I am investigating the effect of environment on gca, sca and heritability degree. Line x tester = 4 x 5.
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There are several software options available for conducting line x tester analysis that can handle multiple environments, including drought and control treatments. Here are a few options:
  1. SAS (Statistical Analysis System): SAS is a powerful statistical software suite that is widely used in the field of agriculture and plant breeding. SAS can handle complex experimental designs, including line x tester analysis with multiple environments.
  2. R software: R is a free and open-source programming language that is widely used in statistical analysis and data science. There are several packages available in R for conducting line x tester analysis, including the "AGHmatrix" and "lineXtester" packages.
  3. GenStat: GenStat is a comprehensive statistical software package that is specifically designed for use in agricultural research. It includes a range of tools for analyzing complex experimental designs, including line x tester analysis.
  4. SPSS: SPSS is a statistical software package widely used in social science and other fields. It also has the capability to conduct line x tester analysis with multiple environments.
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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.
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See my answer to the same question that you asked at
it is about dummy variables that form a closed set.
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Dear all,
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.
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Actually, RT-qPCR and RNA-sequencing are the gold standards. Alternatively, Exome Microarray can be used, which is faster but much more expensive and suits more for large-scale studies.
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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.
Thanks!
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' Partial' correlation istead of correlation controls the confounding effect due to the variabe exposure of prejudices.
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*UPDATE*
Hello everyone!
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...
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Modifying Accounting Data For Managerial Decision
1 Oprating asset and total oprating capital
2 Net operating profit after taxes (NOPAT)
from pages 102 through 105.
Source:
Financial Management: Theory and Practice
Eugene F. Brigham and Michael C. Ehrhardt 2005.
I hope this helps you.
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I want to use NaBH4 to reduce some aldehyde compounds into alcohols.
If I directly inject the solution into GC, will it cause the column contamination?
If so, is there any better method to conduct quantitative analysis?
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If you use an injector liner designed to capture non-volatile components, such as a glass wool packed injector, the salts will be capture in the liner. The liner will need to be replaced more often but this is not a significant issue. Depending upon the quantity of salt injected, there may or may not be a significant difference in the rate of replacement. Peak widths and peak tailing would likely be indicators of the need to change the liners.
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Hi everyone,
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?
Many thanks!
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Before testing the content domain, I will strongly suggest reading the following paper. If conceptualization is based on well-developed measurement theory, then a small sample size is sufficient for your scale validation:
(20) (PDF) Specifying the Problem of Measurement Models Misspecification in Management Sciences Literature (researchgate.net)
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Qualitative data indicates interviews, open-ended questions etc
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Analysis tool NVIVO is recommended...thematic analysis or IPA is also used for qualitative data analysis
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Hello guys,
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!
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Dear Andrei,
if you think you have too many variables for a reasonable application of Qualitative Comparative Analysis (QCA), you can use a much more direct approach to their selection straight from within QCA. In
Lankoski, Jussi, and Alrik Thiem. 2020. "Linkages between agricultural policies, productivity and environmental sustainability." Ecological Economics 178:106809
and
Haesebrouck, Tim, and Alrik Thiem. 2018. "Burden Sharing in CSDP Military Operations." Defence and Peace Economics 29 (7):748-65
I demonstrate the logic and application of a feasible variable selection procedure for QCA that it methodologically grounded (Occam's razor) and guaranteed to be computationally exhaustive. Since replication code for the R environment is available for both articles, you can easily adapt this procedure to your needs.
Best wishes
Alrik
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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?
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You can try AMG and CCMG for robustness.
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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.
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Your real question..... Additionally, you appear to be making an assumption that your results should equal the results obtained by the supplier for your sample ( a reasonable starting assumption, but the real question is far more complicated). There are thousands of variables present in any LC-MS analysis. Any "purity" values assigned to a compound are relative to the EXACT method of analysis used, on that system. With LC-MS (or MS, MS-MS) analysis, the instrument operator, the settings (and their are a LOT of settings), the HPLC method and the specific instrument used all contribute to the results obtain. Just as with your method, the original method used to determine "purity" may or may not be comprehensive (we have no idea). All methods need to be evaluated by professionals to insure they are fit-for-purpose and selective for the sample under analysis before any conclusions are drawn.
Any MS system can output data that is or is not accurate. The system is just a "dumb" tool and to obtain quality output requires a very skilled user with a great deal of practical experience.
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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.
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Yes I do, although onsite we do not have access too MS or XRF equipment, just XRD analysis. Appreciate the help!
Regards,
Luke
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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?
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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?
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Tru Nhut Quynh What exactly are you trying to quantify (e.g. percent TCP in the composite, change in mass of TCP vs HAp in composite with decomposition)? I don’t TGA will not offer much information if you are looking for specific information about the TCP in the composite, if you are only getting TGA on the pure powder mixture. If anything, I’d recommend doing the TGA of the powders separately and then together at whatever concentration you are aiming for. However, this data can easily be found in the literature as the thermal stability/decomposition properties of these materials are well documented in the research. It is your composite material that would be more unique.
There is a number of other methods you can use, such as XRD, in combination with the TGA that would provide a more comprehensive characterization/quantitative analysis of uour material.
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Hello,
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?
David
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Questionnaire adaption to suit research context is common.
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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?
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All due respect to you for this question
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To define quantitative analysis as such in a mixed methods approach, is it necessary to include a regression analysis?
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I agree with Muhammad Tanveer Afzal , i.e. you conduct apt statistically analysis for each approach, and then integrate the results. So you may or may not conduct regression analysis for your quantitative data, which is dependent on your research questions or hypotheses.
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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?
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Plasma emission occurs due to three types of transition in plasma that are free free, Free bound and bound bound transition. All the transitions provides various emission out of which bound bound transition provides line emission and others are continuum emission. All these processes are manly dependent on the plasma density and its temperature. Therefore, a continuum emission also can provide information about plasma density and Temperature.
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Im, a beginner at Raman analysis and anyone can help me to identify the E1 2g, A 1g,C and D peaks in the Raman spectrum of MoS2 and MoS2/rGO. and what is the importance of identifying them for a qualitative or quantitative analysis?
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Pasangi Premadasa The G peak is caused by the bond stretching of all sp2 atom pairs in both rings and chains. The D peak is caused by sp2 atoms in rings breathing.
In most cases, Raman spectra are plotted with the intensity, or "Count Rate," on the y-axis and the frequency of the "Raman Shift" along the x-axis. The difference in frequency between the laser light and the dispersed light is referred to as the Raman shift. This distinction is stated as wave numbers and has nothing to do with the wavelength of the laser.
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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.
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A way to deal with this problem is finding the trends before and after by fitting to a linear, quadratic, ... curves as well. However it is enough to confirm existence of change point using a test like Mann-Kendall.
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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.
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Kishalay Adhikari, you might find some useful information in Chapter 12 of the following book:
Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2019). Multivariate data analysis (8th ed.). Cengage.
I think that some of this chapter could have been written a bit more effectively, but overall it is helpful in drawing distinctions between scales and indexes.
All the best with your research.
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I'm doing a structured observation tallying how many times a teachers does a certain practice in 10 minute intervals. How would you analyse this data?
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You have count data which can be modelled as a log NBD regression. There are book length treatments by Hilbe.
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Usually, mediators and moderators are tested in quantitative studies. However, can we test them in a qualitative study such as a case study?
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The basic answer is that if you test anything, it would not be a qualitative study, but a mixed methods study. Testings as it is understood in quantitative analyses does not exist in quantitative studies. Potential mediators and moderators could be examined using qualitative methods. I hope this is helpful!
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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!
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Ethylene glycol can not be observed by UV analysis using HPLC. It must be derivatized to detect using UV. To measure it, you will need to resolve it away from all of the other compounds present in your sample so UV/VIS spectrophotometry is not select enough. Depending on what types of compounds are presnet in the mix, sample prep procedures will need to worked out, then methods using techniques such as HPLC with derivatization or GC may be used.
When researching basic questions, skip these web forums. Instead, try perform a simple keyword search on the web (via Google, Bing etc...) to find additional info on the topic and/or question. You can easily answer your own question(s) by looking up the structure of the compound, its UV absorbance, examples of papers describing analysis of the same compound in mixtures using different analytical techniques etc. Learning HOW to research a question is one of the most important skills you can learn.
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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?
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Just do logistic regression is what I had in mind. The DV might be antcancer activity (yes /no) same for antioxidant activity. Best wishes David Booth
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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?
Article links
Any help would be appreciated.
Thanks in anticipation.
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Please find some online course for learning R on Edx and Coursera platforms.
Thanks ~PB
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Some of parameters such as LT50 & LD50 needs to evaluate insecticide.
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Use
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Dear all,
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?
Thanks
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Polynomials fit better with everything, but they don't explain anything.
What is the expected relationship between your variables?
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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?
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The sample size is relatively quite small but if the size is above 100 then you can try. There had been studies who have opted for exploratory factor analysis on such smaller sample. But you got to check the KMO and Bartlett's Test of Sphericity to see the adequacy of your data. Try reading the following research papers who support smaller samples for EFA.
De Winter, J.C.F., Dodou, D., & Wieringa, P.A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44, 147–181.
Wirth, R. J., & Edwards, M. C. (2007). Item factor analysis: current approaches and future directions. Psychological Methods, 12, 58-79.
Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42, 815-824.
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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!
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Good discussion question and explanation. Thank you for sharing.
All the best,
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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?
Thank you!
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It's my understanding that PLS works better with smaller samples. But, let's hear it from the experts.
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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?
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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?
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Dear Anh H, I agree with Fatemeh Khozaei. To estimate the company growth rate, the income statement is the most essential variable, which with other variables should include Gross profit and Gross sales of the company.
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I need an all in one software that could handle quantitative analysis aside R and also easy to operate
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Hi
In my experience, XLSTAT is a good option, as it installs within MS Excel so the data can be directly analysed within the excel file. Plenty of tutorials are available, GUI based, quite versatile and easy to learn. Student pricing is also available. I used XLSTAT in my PhD.
Hope it helps
Sudhir
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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?
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Dear Boris,
ceramics like grès porcelain after cooking sintering so they have high Temperature crystalline minerals and very little amount of glass. You can use XRF analysis to check these minerals like mullite, Cristobalite and other feldspar just to say the most common you can find.
Geopolymer materials instead aren’t crystalline so XRF isn’t the best technology to study.
But normally reversal engineering cannot be easy to do with Geopolymers because what was the mineral amorphous allumino silicate, used as precursor, after geopolymerization process becomes new mineral thanks the combination with partially reactive aggregates and will have typically the mineralogy depending on the type of reagent used (alkaline or acidic medium) and the quality of the aggregates. Newborn minerals at early stage of geopolymerization are still amorphous structures then passing time will crystallize about feldspar like minerals.
Remember that it’s possible to create a ceramic-like geopolymer material using specific raw materials to increase at best the Flexural strength even at quite low temperature of curing (alkaline GP or acidic phosphate GP from room temperature to below 200°C). But isn’t possible to use the ceramic powder (micronizing grès tiles) as precursor for Geopolymerization because it isn’t amorphous and so enough reactive.
Maybe using ceramic filler you can obtain an alkaline activated material (AAM) using very corrosive pH, but will be very difficult to stabilize the material because its own over saturation of cations, then durability (high instability under water immersion and the high amount of efflorescence and leaching) cannot to be obtained . In this case XRF can also be used because hardened AAM are compose by hydrated, close to Portland like material.
Best
Alex Reggiani
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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 ?
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Some raw material fo vitamins can not dissolve directly like other APIs because these are added some other components for stability. You need to investigate how this raw material is and in base on that create a method for a selective extraction of the vitamin. Good luck
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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.
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Hi Nabeel,
If you have added the control variables in the equations, the data needs to be collected for that. This would help you see if the relationship between your variable of interest and dependent variable still holds in the presence of the controls.
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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?
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You can probably mix up between moderator and mediator. You may google these terms. Interaction terms are for moderators and path analysis is for mediation.
To answer your question on whether mediation or moderator can be tested for intervention studies, yes you can. However, it should be theoretically sound and the type of analysis is mentioned above.
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Respected Researchers,
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.
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In addition to the above answer, after conducting EFA (generally using SPSS), the next step i.e. CFA can be done via AMOS graphics which is an add-on for SPSS. It is relatively simple to perform, and there are tons of YouTube tutorials also available.
I personally would recommend this link
The instructions are very clear, and generally for CFI, the chi square value, GFI, AGFI, CFI, NFI, TFI, RMSEA etc values should be within the specified values. Below is the link for reference of values. It is important to note that for samples more then 200, the chi square value might not be of significant value.
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Hi,
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.
Thank you.
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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
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use the SPSS program to analyze your data
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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.
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use the SPSS program to analyze your data
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Hi, all,
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?
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Mr. Ma,
Via emoplyment in our (own-authored approach to me and my co-author according to the shown authorship, below) innovative stochastic dynamic mass spectrometric method and model equation shown in references [1,2].
Our method is applicable to exact quantitative analysis of analytes in solution (via ESI-MS) or in solid-state on surface (MALDI-MS [3].)
[1] Analytical Chemistry Letters, 10 (2020) 703-721; Stochastic Dynamic Mass Spectrometric Approach to Quantify Reserpine in Solution; Bojidarka Ivanova, Michael Spiteller.
[2] Steroids, 164 (2020) 108750 Stochastic dynamic mass spectrometric quantification of steroids in mixture — Part II; Bojidarka Ivanova, Michael Spiteller.
[3] B.Ivanova, M. Spiteller, Stochastic dynamic quantitative and 3D structural matrix assisted laser desorption/ionization mass spectrometric analyses of muxture of nucleosides, (2022) in preparation.
(Consider, some results from reference [3] shown as attachment, herein.)
NB! ITOT data, shown in the attached figure, accounts exactly for the analyte concentration in initial solution used to prepare MALDI-MS solid-state sample.
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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.
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Traditional activities like historic tea forests and diverse agroforestry systems help to increase natural biodiversity. Tea monocultures that retain environmental diversity and complexity can be "nudged" toward biodiversity management.
Check out this article as well: https://www.mdpi.com/1999-4907/10/10/856/pdf
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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?
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thanks for your guidance. I am separating oligonucleotides from a digested RNA on a PerfectSil 100 ODS-3 5um (4.6*150 mm) column. I want to calculate amount of one of oligonucleotide in the chromatogram. several injection of same sample show different area. so I do not have reproducibility for that. I can not have a quantitative analysis.
another problem in this area is about decreasing oligonucleotide peak resolution. after several injections I lost the first resolution and peaks became wider. the peaks retention time are Okay, only resolution was changed.
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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?
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Another way to look at ARDL is that the software can produce nonsense results even after you have done everything correctly. That is, all your variables may be statistically insignificant. It is these diagnostic tests plus most importantly, your eyes that will show you that something else is needed. Always run ARDL as an OLS model before accepting what software generates.
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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?
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When original data is modified, then information content is lost. The missing information may or may not be critical to the parameter estimates of interest.
Suppose one data set was modified and you have a series of unmodified data sets, now objective prior information is available and it might be possible to develop a statistical model for the lost information in the modified data set. For example, if one data set was modified to remove a constant (such as a DC baseline offset). You could create a statistic to model the DC offset using the unmodified data sets. Now the estimates for the original data is based on objective prior information.
If someone alters the data and you have no idea whatsoever about the changes they made, then there is no hope. Any method that attempts to recreate the original data is subjective.
In your example - " assumes(s) 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" - this could be objective prior information. If the model for the data could be modified to represent the missing data, then Bayesian analysis would account for the missing data (empty channel) using objective prior probability distributions for all the parameters in the model for the data. If the resulting parameter estimates of interest turn out to have very large uncertainties, at least you would know the unmodified data was inherently uninformative.
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Would you please share your kind opinion regarding this issue?
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You can calculate the mean of any set of numbers. e.g., 1,2,3, (1+2+3)/3 = 2. Being non-normal is different than wanting to estimate a parameter. If you mean something different please specify this.
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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?
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for descriptive narration recoding of categorical data not recommended. But for testing significance or association some times merging of categories is advised to make tests applicable and satify assumption of the tests.
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to get the final value in mg/ g
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The tannins are determined in four steps: I assessment of total phenolic material in plant sample extracts using the Folin-Denis technique, (ii) manufacture of hydrated, chromed hide-powder, (iii) tannin absorption onto hide-powder, and (iv) analysis of phenolic materials in the solution remaining after tannin absorption.
The Folin-Ciocalteu technique is a widely used method for quantifying phenolics. If you need more comprehensive phytochemical measurement, HPLC-UV or LC-MS is advised for quantification and identification.
The powdered plant leaves of the test plant (1.0 g) are weighed into a beaker, and 10 ml of distilled water is added. For five minutes, the mixture is brought to a boil. Then, two drops of 5% FeCl3 are added. The presence of tannins is shown by the formation of a greenish precipitate.
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hello every one
I have an independent quantitative variable and two dependent quantitative variables is MANCOVA suitable for quantitative analysis in this case?
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Hello Fatima,
You most likely can use man(c)ova or multivariate regression, but the real key hinges on your specific research question(s), and whether you have other IVs beyond the lone one you mention. If the only IV is quantitative, it likely makes more sense to think about multivariate regression.
Good luck with your work.
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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)
Thank you
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Hi Fatima,
With only one level of your independent variable, there is nothing to be compared. Thus, I don't see how you could use a multivariate analysis of variance (MANOVA). The appropriate test would depend on what your research question is. For example, if you are interested in the relationship between the two quantitative variables, you could look at correlation (Pearson or Spearman). Since your independent variable has only only level, it is not a variable, but a constant. MANOVA or ANOVA is used to compare multiple levels of an independent variable based on dependent variable(s).
I hope this is helpful.
J. McLean
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I want to count these fragments for image analysis of autolysis. Please suggest good software, it is so critical in my work.
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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?
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A photodiode array detector, or PDA, is a type of absorbance detector (such as a UV detector) that is able to detect light-absorbing compounds at the PG level. However, PDA detects an entire spectrum simultaneously. UV and VIS detectors visualize the obtained result in two dimensions ( optical density and time), but PDA adds the third dimension (wavelength). The analyte or related impurities peak can be determined simultaneously during separation at all wavelengths, which is convenient for choosing the most suitable wavelength and determining the purity of the analyte or related impurities.
But you must inject a standard to make a standard curve for qualitative and quantitative analysis (without a standard curve, we can not identify the analyte)
MS Mass Spectrometer
The analytes are detected based on their MW (Mass: charge). The obtained information is especially useful for compound structure and identification (based on the Mass: charge ratio (without standard injection)). By constructing a standard curve, a very low detection limit of analyte can be quantified.
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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 !
The standard:
Element Standard Mass(%) ZAF Fac. Z A F
BaO Benitoite 37.08 0.9158 1.0078 0.9087 1
Analysed romanechite:
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
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For what i can see, all the EMP analysis is bad.
Romanechite should show 0.5-1.0 wt% SiO2
MnO should be up to 68-70 wt%
In your analyses also these elements are underestimated.
Therefore I think it is matter of both quality of the section and wrong correction to standards.
cheers
Federico
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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?
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Depending on you objective statement, if your objective is to compare variables that influence a particular problem, you can use the t- test to compare and them give justification.
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Dear all!
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
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Dear Henrik,
For such quantitative size of survey as You want the best thing is to use Paniott formula. Please, take a glance on Paniott formula on Google.
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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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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.
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Examples of uncertainty-based risks include:
  • damage by fire, flood or other natural disasters.
  • unexpected financial loss due to an economic downturn, or bankruptcy of other businesses that owe you money.
  • loss of important suppliers or customers.
  • decrease in market share because new competitors or products enter the market.
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Hello, all,
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!)
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that is to do research!
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