Implementation of a Weight Loss Program

Introduction 

The study focused on assessing if the number of sessions attended for a weight loss program were related with the pounds that the participants upon a successful completion. Based on this program, the weight loss was treated as the dependent variable with the number of sessions attended being treated as the predictor or independent variable. Therefore, manipulation of the sessions attended (measured by the changes in the number attended by the participants) was hypothesized to influence the ponds that these participants lost by the end of the program. In this case, the sessions Therefore, the research hypothesis claimed that the number of sessions had an impact on the weight loss. Statistically, the hypothesis statement can be restated as follows: 

H0: There is no relationship between sessions attended and pounds lost 

H1: There is a relationship between the sessions attended and pounds lost 

Test approach and assumptions 

Each of the variables was measured independently and recorded for analysis. For instance, the weight loss was measured in pounds and this assumed a continuous ratio scale. On the other hand, the sessions attended were measured by the physical counts that the participants registered in their attendance and successful completion for each session. Again, this is an example of discrete data was measured in a ratio scale (Cronk, 2012). According to Allen and Seaman (2007), a ratio scale is a quantitative scale that has an absolute zero value that makes comparison for different score easy and meaningful. 

The data for nine weeks on these two variables for each of the ten participants were recorded pairwise for easy analysis. The Pearson Correlation analysis technique was adopted for this study to assess the potential linear association between the sessions attended and weight loss. For instance, the correlation test analysis assumed that the two distributions were normally distributed, had no outliers, the pairs were related (Cronk, 2012). Based on the data collected, all these assumptions were met – making the Pearson Correlation suitable. Additionally, a 5% significance level was adopted to test the study hypothesis. 

Findings 

The study found that, there was a strong positive correlation between sessions attended and the pounds lost during the program, R = 0.756, p < 0.05. Based on the p-value approach, the H1 was rejected since the p-value was less than the alpha indicating that the correlation coefficient was statistically significant. It was concluded that the sessions attended by the participants influenced the quantity of pounds that they lost. 

Table 1 Correlations Table 

Discussion and conclusion 

The study findings suggest that more attendants on weight loss programs may subject individuals to shedding off excess pounds in their bodies. Clinically, the results can be adopted in recommending patients to enroll in induced weight loss programs and encourage them to attend them as scheduled. However, correlation does not imply causation indicating that there are chances that the sessions attended does not influence the weight lost (Dawson, Trapp, and Trapp, 2004). Such an aspect proves one of the most salient weaknesses of correlation as a measure of linear association. There may be a false-cause fallacy between sessions attended and weight lost – where the association is by coincidence (Cronk, 2012). Therefore, any further research on this topic may consider stronger techniques such as regression to prove the causation effect. 

References 

Allen, I. E., & Seaman, C. A. (2007). Likert scales and data analyses. Quality progress , 40 (7), 64-65.

Cronk, B. C. (2012). How to use SPSS: A step-by-step guide to analysis and interpretation (7th ed). Glendale, CA: Pyrczak Publishing. 

Dawson, B., Trapp, R. G., & Trapp, R. G. (2004). Basic & clinical biostatistics (Vol. 4). New York: Lange Medical Books/McGraw-Hill.

Appendix 

Appendix I 

Data Used for Analysis