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20241010001853-0677d3e438f5704ff7d3114bd1c86020f00201cd + 20241010001853 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 10 + 2024 + + + 9 + + 102 + + + + Statmanager-kr: A User-friendly Statistical Package for +Python in Pandas + + + + Changseok + Lee + https://orcid.org/0000-0002-8825-5571 + + + + 10 + 10 + 2024 + + + 6642 + + + 10.21105/joss.06642 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.13901218 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/6642 + + + + 10.21105/joss.06642 + https://joss.theoj.org/papers/10.21105/joss.06642 + + + https://joss.theoj.org/papers/10.21105/joss.06642.pdf + + + + + + Statistics for the Social Sciences: Moving +Toward an Integrated Approach + Moon + 978-1516519613 + 2020 + Moon, S. M. (2020). Statistics for +the Social Sciences: Moving Toward an Integrated Approach. Cognella +Academic Publishing. ISBN: 978-1516519613 + + + Difficulties experienced by education and +sociology students in quantitative methods courses + Murtonen + Studies in Higher education + 2 + 28 + 10.1080/0307507032000058064 + 2003 + Murtonen, M., & Lehtinen, E. +(2003). Difficulties experienced by education and sociology students in +quantitative methods courses. Studies in Higher Education, 28(2), +171–185. +https://doi.org/10.1080/0307507032000058064 + + + SciPy 1.0: fundamental algorithms for +scientific computing in Python + Virtanen + Nature methods + 3 + 17 + 10.1038/s41592-019-0686-2 + 2020 + Virtanen, P., Gommers, R., Oliphant, +T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, +P., Weckesser, W., Bright, J., & others. (2020). SciPy 1.0: +fundamental algorithms for scientific computing in Python. Nature +Methods, 17(3), 261–272. +https://doi.org/10.1038/s41592-019-0686-2 + + + Statsmodels: Econometric and statistical +modeling with Python + Seabold + Proceedings of the 9th Python in Science +Conference + 61 + 57 + 10.25080/Majora-92bf1922-011 + 2010 + Seabold, S., & Perktold, J. +(2010). Statsmodels: Econometric and statistical modeling with Python. +Proceedings of the 9th Python in Science Conference, 57(61), 10–25080. +https://doi.org/10.25080/Majora-92bf1922-011 + + + Pingouin: statistics in +Python + Vallat + Journal of Open Source +Software + 31 + 3 + 10.21105/joss.01026 + 2018 + Vallat, R. (2018). Pingouin: +statistics in Python. Journal of Open Source Software, 3(31), 1026. +https://doi.org/10.21105/joss.01026 + + + + + + From bc3598fada0239a864a166849bbfe4662a8c9022 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Thu, 10 Oct 2024 01:19:16 +0100 Subject: [PATCH 3/3] Creating 10.21105.joss.06642.jats --- .../paper.jats/10.21105.joss.06642.jats | 283 ++++++++++++++++++ 1 file changed, 283 insertions(+) create mode 100644 joss.06642/paper.jats/10.21105.joss.06642.jats diff --git a/joss.06642/paper.jats/10.21105.joss.06642.jats b/joss.06642/paper.jats/10.21105.joss.06642.jats new file mode 100644 index 0000000000..86b3bfaafe --- /dev/null +++ b/joss.06642/paper.jats/10.21105.joss.06642.jats @@ -0,0 +1,283 @@ + + +

+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +6642 +10.21105/joss.06642 + +Statmanager-kr: A User-friendly Statistical Package for +Python in Pandas + + + +https://orcid.org/0000-0002-8825-5571 + +Lee +Changseok + + + + + +DYPHI Research Institute, DYPHI Inc., Daejeon, Republic of +Korea + + + + +15 +1 +2024 + +9 +102 +6642 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +statistical analysis +social science +null-hypothesis +user-friendly + + + + + + Summary +

Python is one of the most accessible and adaptable programming + languages, utilized in various research domains, including statistics. + However, few statistical packages inherit these characteristics of + Python, leaving researchers unfamiliar with programming languages + dependent on other expensive software. To address this gap, + Statmanager-kr has been developed to provide + non-programmers with convenient access to statistical functions. + Statmanager-kr is designed to be compatible + with Pandas.DataFrame and enables statistical + analyses using a single method with a relatively small number of + parameters. With SciPy and + statsmodels ensuring the validity of analyses, + Statmanager-kr offers functions for hypothesis + testing, comparing between-group and within-group differences, + regression, correlations, data visualization, and more.

+
+ + Statement of need +

Statmanager-kr is a statistical package for + Python in Pandas. This package provides methods + commonly used for null hypothesis significance testing (NHST), which + is of interest to researchers in various fields + (Moon, + 2020). It is also possible to test for normality or + equivariance using the Shapiro-Wilk, Levene, or Fmax tests.

+

Most of the statistical software available today is difficult to + use, as a previous study reported that one of the challenges students + face in statistics courses was “using software” + (Murtonen + & Lehtinen, 2003). Although there are basic statistical + libraries in Python, such as SciPy + (Virtanen + et al., 2020) and statsmodels + (Seabold + & Perktold, 2010), they are quite complex. While some + studies require complex and detailed statistical modeling and + analysis, there are also many studies that require only a few + hypothesis tests. Therefore, the development of an easy-to-use + statistical package would be of great benefit to these + researchers.

+

To achieve this, Statmanager-kr has been + designed to run analyses with only three lines of code: 1) read data + as a Pandas.DataFrame, 2) create a + Stat_Manager object, 3) execute the + progress() method. Therefore, users can use + Statmanager-kr as long as they know + Pandas functions to read the data, such as + read_csv() or + read_excel(). It also includes functions to + visualize the results depending on the analysis method.

+
+ + Related Work +

Recent advances in the field of statistics have been achieved + through the emergence of user-friendly packages, such as + Pingouin + (Vallat, + 2018). Pingouin is an easy-to-use statistics package that + offers a wide range of analytical functions. Like + Pingouin, Statmanager-kr + is similar in that it aims to be a user-friendly statistics + package.

+

However, Statmanager-kr and + Pingouin differ in their target users. Since + Statmanager-kr is designed for researchers with + limited programming experience, it focuses on keeping the workflow + short and concise; therefore, Statmanager-kr + was designed to allow users to apply analyses and obtain results by + always running a single method, progress(), in + a similar way. On the other hand, Pingouin was + developed for users with a relatively high level of programming + knowledge and experience; therefore, in terms of workflow, + Pingouin offers more comprehensive and + fine-tunable analysis methods and provides more detailed analysis + results. Also, Statmanager-kr only works with + Pandas.DataFrame, while + Pingouin has the advantage of being compatible + with a wider range of date types.

+

Another difference is related to post-hoc analysis and + visualiztion. When running an analysis that allows post-hoc analysis, + such as ANOVA, in Statmanager-kr, post-hoc + analysis like Bonferroni correction can be performed by adding the + posthoc parameter to the + progress method. It is possible to visualize + the results by using figure() as a method + chaining in Statmanager-kr. Although + Pingouin does not provide the functions to + directly visualize the results of an analysis, it does support the + generation of graphs that are very useful from a statistical + perspective, such as paired plots, shift plots, and circular mean + plots. Pingoin also has the advantage of + supporting a wider range of post-hoc analyses, although it requires a + separate method.

+

In conclusion, depending on the researcher’s programming experience + and the purpose of the study, Statmanager-kr + and Pingouin can be used differently. + Researchers who are familiar with programming may be better suited to + use Pingouin as it supports more analysis + methods and customization. On the other hand, + Statmanager-kr is designed to be used by + researchers who are not familiar with programming and coding, but want + to get quick results.

+
+ + Features +

Learn more about the features in the + official + documentation. The instructions for running each + analysis are also described in + the + manual section of the official documentation. + Korean + versions of the official documenation are also + available.

+
+ + Acknowledgements +

Author declares no conflicts of interests.

+
+ + + + + + + + MoonSimon M. + + Statistics for the Social Sciences: Moving Toward an Integrated Approach + Cognella Academic Publishing + 2020 + 978-1516519613 + + + + + + MurtonenMari + LehtinenErno + + Difficulties experienced by education and sociology students in quantitative methods courses + Studies in Higher education + Taylor & Francis + 2003 + 28 + 2 + 10.1080/0307507032000058064 + 171 + 185 + + + + + + VirtanenPauli + GommersRalf + OliphantTravis E + HaberlandMatt + ReddyTyler + CournapeauDavid + BurovskiEvgeni + PetersonPearu + WeckesserWarren + BrightJonathan + others + + SciPy 1.0: fundamental algorithms for scientific computing in Python + Nature methods + Nature Publishing Group + 2020 + 17 + 3 + 10.1038/s41592-019-0686-2 + 261 + 272 + + + + + + SeaboldSkipper + PerktoldJosef + + Statsmodels: Econometric and statistical modeling with Python + Proceedings of the 9th Python in Science Conference + Austin, TX + 2010 + 57 + 61 + 10.25080/Majora-92bf1922-011 + 10 + 25080 + + + + + + VallatRaphael + + Pingouin: statistics in Python + Journal of Open Source Software + 2018 + 3 + 31 + 10.21105/joss.01026 + 1026 + + + + + +