Statistical Hypothesis Tests and Statistical Power in Pure and Applied Science

Author(s):  
David F. Parkhurst
2017 ◽  
Vol 6 (6) ◽  
pp. 158
Author(s):  
Louis Mutter ◽  
Steven B. Kim

There are numerous statistical hypothesis tests for categorical data including Pearson's Chi-Square goodness-of-fit test and other discrete versions of goodness-of-fit tests. For these hypothesis tests, the null hypothesis is simple, and the alternative hypothesis is composite which negates the simple null hypothesis. For power calculation, a researcher specifies a significance level, a sample size, a simple null hypothesis, and a simple alternative hypothesis. In practice, there are cases when an experienced researcher has deep and broad scientific knowledge, but the researcher may suffer from a lack of statistical power due to a small sample size being available. In such a case, we may formulate hypothesis testing based on a simple alternative hypothesis instead of the composite alternative hypothesis. In this article, we investigate how much statistical power can be gained via a correctly specified simple alternative hypothesis and how much statistical power can be lost under a misspecified alternative hypothesis, particularly when an available sample size is small.


2017 ◽  
Vol 207 (4) ◽  
pp. 148-150 ◽  
Author(s):  
Michael P Jones ◽  
Alissa Beath ◽  
Christopher Oldmeadow ◽  
John R Attia

2021 ◽  
Vol 4 (2) ◽  
pp. p69
Author(s):  
Apostolou George ◽  
Papatsimpas Achilleas ◽  
Gounas Athanasios ◽  
Gkouna Ourania

The purpose of this study is to investigate the reaction of Greeks to this new educational reality due to the Covid-19 outbreak. Since the first restrictive measures were implemented in March 2020in Greece, distance learning has become a dynamic part of people’s daily lives with the prospect of remain in gas such in the future. A total of N=170 students, parents, teachers, civil servants, private sector employees who were involved in the distance learning process either as instructors or as students in the period of Covid-19 pandemic in Greece, were selected with the use of snowball sampling. A questionnaire using demographic and satisfaction related variables was completed by the respondents, namely citizens across Greece, based on a Likert scale questionnaire which is a useful and multidimensional instrument, to assess satisfaction within the time frame from July 7, 2020 to October 20, 2020; the period when there occurred a loosening in the restrictive measures between the two lockdowns in Greece. It was investigated how the demographic factors, specifically gender, age, occupation, and place of residence, influence the attitude of the respondents towards synchronous and asynchronous distance learning as well as their intention to continue using online education services in the future after the lifting of the restrictive measures. Additionally, the customers’ preferences concerning the most enjoyable distance learning experience were examined, so that they will be available to the distance learning program designers. Descriptive statistical analysis and non-parametric statistical hypothesis tests were conducted in SPSS and R. Most of the respondents had not participated in online courses before the Covid-19 outbreak, 46 % did participate in e-learning courses before the Covid-19 lockdown while 54 % did not and 34.1% respondents prefer face-to-face learning, while 15.9% prefer e-learning. Also, 50% respondents prefer a combination of face-to-face learning and e-learning. Hypothesis tests showed that there are statistically significant differences between users’ preferences as well as regarding their demographic characteristics. Undergraduate and postgraduate university students continue to participate in online learning courses and are willing to invest financial resources and time in this new educational process (?2(4)=10.440, p=0.034), unlike high school students who prefer face-to-face learning (p=0.042). The present study will lead to practical implications, such as the formation of e-learning programs which aim for the best user experience and the best learning outcomes. Also, private educational organizations can include the results in the key elements to implementing a strategic marketing mix.


2020 ◽  
pp. 28-63
Author(s):  
A. G. Vinogradov

The article belongs to a special modern genre of scholar publications, so-called tutorials – articles devoted to the application of the latest methods of design, modeling or analysis in an accessible format in order to disseminate best practices. The article acquaints Ukrainian psychologists with the basics of using the R programming language to the analysis of empirical research data. The article discusses the current state of world psychology in connection with the Crisis of Confidence, which arose due to the low reproducibility of empirical research. This problem is caused by poor quality of psychological measurement tools, insufficient attention to adequate sample planning, typical statistical hypothesis testing practices, and so-called “questionable research practices.” The tutorial demonstrates methods for determining the sample size depending on the expected magnitude of the effect size and desired statistical power, performing basic variable transformations and statistical analysis of psychological research data using language and environment R. The tutorial presents minimal system of R functions required to carry out: modern analysis of reliability of measurement scales, sample size calculation, point and interval estimation of effect size for four the most widespread in psychology designs for the analysis of two variables’ interdependence. These typical problems include finding the differences between the means and variances in two or more samples, correlations between continuous and categorical variables. Practical information on data preparation, import, basic transformations, and application of basic statistical methods in the cloud version of RStudio is provided.


Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 883 ◽  
Author(s):  
Luis Gustavo Esteves ◽  
Rafael Izbicki ◽  
Julio Michael Stern ◽  
Rafael Bassi Stern

This paper introduces pragmatic hypotheses and relates this concept to the spiral of scientific evolution. Previous works determined a characterization of logically consistent statistical hypothesis tests and showed that the modal operators obtained from this test can be represented in the hexagon of oppositions. However, despite the importance of precise hypothesis in science, they cannot be accepted by logically consistent tests. Here, we show that this dilemma can be overcome by the use of pragmatic versions of precise hypotheses. These pragmatic versions allow a level of imprecision in the hypothesis that is small relative to other experimental conditions. The introduction of pragmatic hypotheses allows the evolution of scientific theories based on statistical hypothesis testing to be interpreted using the narratological structure of hexagonal spirals, as defined by Pierre Gallais.


2017 ◽  
pp. 143-168
Author(s):  
David B. Speights ◽  
Daniel M. Downs ◽  
Adi Raz

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