Do you think the variables are appropriately used? Why or why not? Does the addition of the control variables make sense to you? Why or why not?

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Respond to your colleagues’ posts and comment on the following:

  1. Do you think the variables are appropriately used? Why or why not?
  2. Does the addition of the control variables make sense to you? Why or why not?
  3. Does the analysis answer the research question? Be sure and provide constructive and helpful comments for possible improvement.
  4. If there was a significant effect, comments on the strength and its meaningfulness.
  5. As a lay reader, were you able to understand the results and their implications? Why or why not?

 

Andrews, D., & Banks, C. (2020). An Assessment of the Benefits of Off-Season Training Among Teenage Basketball Players. Physical Educator, 77(5), 801–812. https://doi-org.ezp.waldenulibrary.org/10.18666/TPE-2020-V77-I5-9279

In a quantitative study, the correlational research design determines the extent of a relationship between two or more variables using statistical data. This type of research design measures or describes existing conditions that have occurred in the past. In this study, a correctional analysis was conducted on a group of people who are quantitively measured on two or more variables that have happened to them. This type of design was an appropriate choice for this study because, through the correlation analysis, the researcher evaluated the correlation coefficient, which told them how much one variable changed when the other did.

 

Again, in this quantitative study, the research design known as correlation was used. Twenty participants were assigned to the control group, and the twenty remaining participants were assigned to the test group. The focus was to establish the development of athletes’ rebounding, passing, scoring, and dribbling skills at the end of the off-season training (Andrews, D. et al., 2020). A correlation of the test and control groups in the pretest and post-test assessment stages was entailed in the correlation analysis. Tables 8 and 9 below show the r value for each skill pre-assessment and post-assessment.

The results did stand alone as the results added to existing statistical knowledge of the study. The study results provided a significant contribution to the body of knowledge regarding aerobic and anaerobic conditioning for off-season training. The correlation analysis results indicated that off-season training was a positive predictor of better performance among teenage basketball players. No, the authors did not report effect size. Effect size is a statistical concept that measures the strength of the relationship between two variables on a numeric scale (Statistics Solutions, 2020). To find the effect size of the population, the researcher should divide the population mean differences by their standard deviation.

 

Andrews, D., & Banks, C. (2020). An Assessment of the Benefits of Off-Season Training Among Teenage Basketball Players. Physical Educator, 77(5), 801–812. https://doi-org.ezp.waldenulibrary.org/10.18666/TPE-2020-V77-I5-9279

 

Statistics Solutions. (2020, June 29). Effect Size. Retrieved January 21, 2021, from https://www.statisticssolutions.com/statistical-analyses-effect-size/#:~:text=Effect%20size%20is%20a%20statistical,variables%20on%20a%20numeric%20scale.&text=In%20statistics%20analysis%2C%20the%20effect,%2C%20(3)%20correlation%20coefficient.