Quantitative Analysis - Science method

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.

1. to explore the behavioural influential factors of public perception towards reaction on cancelling cultural incidents in the Twitter platform.

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.

marketing sensing, aligning organizational strategies, considering digital transformation and industry 4.0 perspectives considering customer 4.0, cultural orientation culture 4.0.

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:

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

Syeda Zahra

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!!

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.

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.

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).

Everything we see, think, feel, touch, etc. is false, only the truth knows itself.

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.

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.

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.

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.

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:

See my answer to the same question that you asked at

it is about dummy variables that form a closed set.

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.

' Partial' correlation istead of correlation controls the confounding effect due to the variabe exposure of prejudices.

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.

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.

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)

Analysis tool NVIVO is recommended...thematic analysis or IPA is also used for qualitative data analysis

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

You can try AMG and CCMG for robustness.

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.

Johannes M. Meusburger

Yes I do, although onsite we do not have access too MS or XRF equipment, just XRD analysis. Appreciate the help!

Regards,

Luke

Also check please the following useful link: https://cits.tamiu.edu/kock/pubs/journals/2018/Kock_Hadaya_2018_ISJ_SampleSizePLS.pdf

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.

Questionnaire adaption to suit research context is common.

All due respect to you for this question

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.

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.

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.

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.

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.

You have count data which can be modelled as a log NBD regression. There are book length treatments by Hilbe.

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!

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.

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

Dear Aziz Ur Rehman ,

Please find some online course for learning R on Edx and Coursera platforms.

Thanks ~PB

Use

Polynomials fit better with everything, but they don't explain anything.

What is the expected relationship between your variables?

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.

Shikha Ahuja

Good discussion question and explanation. Thank you for sharing.

All the best,

It's my understanding that PLS works better with smaller samples. But, let's hear it from the experts.

GUI type -https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwja6ezvsfr2AhX1zTgGHRL0C1AQFnoECD4QAQ&url=https%3A%2F%2Flink.springer.com%2Fcontent%2Fpdf%2F10.1007%252Fs00180-012-0317-1.pdf&usg=AOvVaw31Y9KGVr-UESpSL097bzkL

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.

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

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

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

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.

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.

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.

Tazyeen Alam

Take a look:

1. https://censusindia.gov.in/pca/cdb_pca_census/houselisting-housing-wb.html

2. https://www.census2011.co.in/census/state/districtlist/west+bengal.html

use the SPSS program to analyze your data

use the SPSS program to analyze your data

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! I^TOT data, shown in the attached figure, accounts exactly for the analyte concentration in initial solution used to prepare MALDI-MS solid-state sample.

P.W.s Fernando

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

William Letter

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.

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.

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.

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.

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.

Preeti Nirala

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.

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.

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

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.

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.

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

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.

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.

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.

that is to do research!