Influence On Health And Wellness: A Comparative Analysis

Results
Influence on Political Views
The female mean of 7.59 was slightly higher than the male mean of 7.07, with females also having less variability in scores. On a scale of 3 to 15 that has a neutral influence score of 9, these means fall just above a level of slight influence. To determine if the mean difference was statistically significant, an independent t-test was conducted between the two genders. The p-value of the Levene’s Test was .876, indicating that it is ideal to assume equal variances. The t-test p-value was .322. Because it is less than .05, the null hypothesis fails to be rejected; therefore, the influence of professional athletes on the political views of University of Michigan undergraduates does not differ between males and females.
Influence on Health and Wellness

The male mean of 11.61 is roughly one point higher than the female mean of 10.63.

Females have slightly less variability, but the interquartile ranges of both genders are identical. On a scale of 5 to 25 that has a neutral influence score of 15, the means fall just above a level of slight influence. An independent t-test was conducted to determine if the mean difference between the two genders was statistically significant. Because the p-value of the Levene’s Test was .315, it is appropriate to assume equal variances. The p-value of .068 does not fall below .05 and thus the null hypothesis cannot be rejected. The influence of professional athletes on the health and wellness choices of University of Michigan undergraduates does not differ between males and

females.
Influence on Product Use
The male mean of 9.50 was higher than the female mean of 8.12. Males had a smaller variability than females. Females had a larger interquartile range and a higher maximum value and lower minimum value. On a scale of 3 to 15 that has a neutral influence score of 9, the male mean falls slightly above neutral influence and the female mean falls just below a level of neutral influence. In order to confirm that this difference was statistically significant, an independent t-test was conducted between the two genders for their product use influence scores. The p-value of the Levene’s Test was .014, which is less than .05, so we cannot assume equal variance. The t-test p-value was .006, which is less than .05, so we reject our null hypothesis and conclude that we have statistically significant results. Therefore, we conclude that the influence of professional athletes on product use of University of Michigan undergraduates is greater on males than females.
Total Influence on Lifestyle Choices
The male mean of 28.18 is higher than the female mean of 26.14. However, their variabilities and interquartile range are similar. On a scale of 11 to 55 that has a neutral influence score of 33, these means both fall below a level of neutral influence. An independent t-test was conducted to determine if there was a statistically significant difference between the two genders and the overall influence professional athletes have on their lifestyle choices. The p-value for the Levene’s Test was .742, which is greater than .05, so we can assume equal variance. The p-value for the t-test was .069, which is greater than .05, so we fail to reject our null hypothesis and conclude that our results are not statistically significant. We conclude that the influence of professional athletes on the lifestyle choices of UM undergraduates does not differ between males and females.
When looking at the total influence on lifestyle choices for both males and females, the mean is 26.88 and median is 27. On a scale of 11 to 55 that has a neutral influence score of 33, this means falls below a level of neutral influence. This did not support the hypothesis that professional athletes have great influence on the lifestyle choices of University of Michigan undergraduate students.
Additional Findings
A Pearson correlation test was conducted on two independent variables to determine if there was a relationship between the two. The two variables measures were “interest in sports” and “total influence.” The test resulted in a p-value of .018, which is significant at the .05 level, and a positive complimentary Pearson correlation value of .269. This positive correlation indicates that as the level of interest in sports increase, the total level of influence also increases.

The last test conducted was to see if ethnicities were affected differently in regards to athlete influence. The non-White mean of 28.7 was slightly higher than the White mean of 26.61. To determine if the mean difference was statistically significant, an independent t-test was conducted between the two ethnicities. The p-value of the Levene’s Test was .958, indicating that it is ideal to assume equal variances. The t-test p-value was .195. Because it is greater than .05, the null hypothesis fails to be rejected; therefore, the influence of professional athletes on the lifestyle choices of University of Michigan undergraduates does not differ between Whites and non-Whites.

Limitations and Suggestions
Limitations
The study was not without its limitations. As mentioned in Data Collection section, the survey was limited to only 77 fully completed responses, as 32 were incomplete. In a student body undergraduate population of 28,983 this is indeed a small sample. The small sample is more indicative in the distribution in ethnicity and gender. With an undergraduate population ratio of males 50% and females 50%, this survey’s sampling was limited in the number of male responses, with a 36 to 64 ratio of males to females. While close, these sampling numbers do not accurately reflect the population. Further, the survey had limitations in the ethnicity apportions. The population of undergraduates claiming to be White are 65% with non-White at 35%. The survey’s respondents were largely White, at 87%, while non-White made up the remaining 13%. Again, this is not a correct representation of the undergraduate population. Another limitation was the operationalization of the key concept “Lifestyle.” Only three categories were surveyed while many others went unmeasured. Further complications lie in the definition of “lifestyle” alone, “The persistent conceptual and operational imprecision of the lifestyle construct has not only handicapped lifestyle research, but has undermined its usefulness as a segmentation variable” (Anderson and Golden, 1984). And lastly, as with all surveys, response bias is a factor in responses.
Suggestions
If the study were to be conducted again, or additional studies to be made in conjunction with this particular one some suggestions could be made. The biggest factor would be obtaining a larger sample by having more responses and therefore allowing for a more accurate representation of the undergraduate population. Further analysis could be conducted on the influence of male athletes versus the influence of female athletes. Independant tests could be ran testing hypotheses on the different genders, ethnicities, and in totality. One final suggestion would be to conduct a test to see the variations in athlete influence among different sports, namely the big five sports.
Conclusion
Professional athletes have a relatively small influence on the lifestyle choices of UM undergraduates. The tests ran showed insufficient evidence to suggest that professional athletes have a greater influence on the lifestyle choices of males than females in the three operationalized categories. In the category “political views” the data collected suggests there is no difference in the influence of males to females. In the category of “Health and Wellness” the data collected suggests there is no difference in the influence of males to females. In the category “Product use” the data collected suggests that males are influenced more than females. Further test’s evidence suggests a positive correlation between “interest in sports” and “influence of athlete”; ultimately the more interest one has in sports, the greater the influence an athlete will have on that particular individual. Lastly, there is insufficient evidence to suggest that professional athletes influence ethnicities differently; this is in part due to the sampling of respondents.