Edmonds, W. A., & Kennedy, T. D. (2017). An applied guide to research designs: Quantitative, qualitative, and mixed methods (2nd ed.). SAGE. This resource will explain randomization, pretest/posttest, time-series, or factorial design, population, and sample. Please read and focus on pp. 13-26, 29-92 this week.
* There is a "Show Page Numbers" function available when you access the book's chapters. It is above the title of the chapter, off to the right. This is an example:
G*Power: Statistical Power Analyses for Windows and Mac. (n.d.). G*Power: Statistical power analyses for Windows and Mac. HHU. Download G*Power software from this resource, which is a statistical tool for sample size justification.
Kadam, P., & Bhalerao, S. (2010). Sample size calculation. International Journal of Ayurveda Research, 1(1), 55–57. This resource will help explain the importance of and how to calculate sample size. *Note: a researcher can’t just ‘guess’ sample size. In a quantitative study you must statistically measure minimum sample size.
Lenth, R. V. (2001). Some practical guidelines for effective sample size determination. The American Statistician, 55(3), 187-193. This resource will help you further your understanding of sample size justification.
Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149-1160. This resource provides you with a better understanding of sample issues such as sample size justification.
Hoenig, J. M., & Heisey, D. M. (2001). The abuse of power: The pervasive fallacy of power calculations for data analysis. The American Statistician, 55(1), 19-24. This article includes an example of statistically supporting sample size.