Exercise Habits of University Students Case Study

This is very clear from the consistently over 50% level of activity for cardio training for example. It is noteworthy this is the first time activity levels across the respondent base have stayed over 50% for any factor. This leads to the conclusion that the greater the concentration on a given area or specialized fitness program the greater the commitment over time.

The fourth question is which type of activity is least likely to lead to a high level of commitment on the part of respondents. Previous analysis indicates that the more specialized the activity the greater the long-term commitment. The contrarian view is supported through nonparametric correlation analysis of the activities measured in the response. When aerobics and basketball are combined by the same respondent there is a very high negative correlation of -.306, significant at the .01 level of confidence.

The fifth question is whether respondents participate in more than one activity is next analyzed in the study. Analyzing the joint frequency distributions of each of the exercises respondents participate in, it was found that groupings of comparable exercises were engaged in by respondents at a relatively high frequency. 34.3% of respondents overall participate in aerobics and cardio machines, activities which can be completed year-round within a gym. Using non-parametric bivariate correlation analysis it is also found that aerobic activity and cardio machines have an R=.228 at the .01 level of significance. The combination of football and basketball are the two most popular sports played by respondents with an R=.443 at the .01 level of confidence. This supports the finding that respondents are more multidimensional in their pursuit of exercise than the initial results indicated.

The sixth question is to determine which combination of motivators for staying with an exercise program are the most effective when used in conjunction with each other. Using a Pearson bivariate correlation analysis to evaluate all factors in question 18, the strongest combination of motivators are the self-reinforcing beliefs of exercise making the respondent look better and also feel better about themselves (.590) at the .01 level of confidence. Respondents then are self-motivated by changes they see in their appearance and how they feel about themselves much more than the goal of just losing weight or improving cardiovascular condition. This analysis also shows that the more important the factor in why a respondent exercises the greater the dimensionality of it. In other words, these top factors in motivating to respondents to work out are interlinked.

Appendix

Descriptive Statistics: All Variables

Variable NN* Mean SE Mean StDev Median

X1 261-0-0.4981-0.0310-0.5010-0.0000

X2 261-0-3.2146-0.0609-0.9845-4.0000

X3 261-0-2.5632-0.0392-0.6331-3.0000

X4 261-0-2.9234-0.0764-1.2349-3.0000

X5 255-6-0.4863-0.0314-0.5008-0.0000

X6 257-4-2.2918-0.0852-1.3652-2.0000

X7 259-2-0.6602-0.0295-0.4745-1.0000

X8 259-2-0.4826-0.0311-0.5007-0.0000

X9A 260-1-0.4192-0.0307-0.4944-0.0000

X9B 111-150 2.640-0.135-1.426-2.000

X10 259-2-0.2548-0.0271-0.4366-0.0000

X11 259-2-0.3552-0.0298-0.4795-0.0000

X11A 84-177 0.5714-0.0543-0.4978-1.0000

X11B 79-182 0.0886-0.0322-0.2860-0.0000

X11C 80-181 0.2000-0.0450-0.4025-0.0000

X11D 84-177 0.3929-0.0536-0.4913-0.0000

X12 255-6-0.7255-0.0280-0.4471-1.0000

X13 200-61 0.1900-0.0278-0.3933-0.0000

X13A 43-218 0.4651-0.0770-0.5047-0.0000

X13B 42-219 0.4048-0.0767-0.4968-0.0000

X13C 39-222 0.0256-0.0256-0.1601-0.0000

X13D 42-219 0.2143-0.0641-0.4153-0.0000

X13E 41-220 0.0732-0.0412-0.2637-0.0000

X14 196-65 2.4643-0.0676-0.9467-2.0000

X15 188-73-64.87-1.90-26.04-60.00

X16A 185-76 0.2595-0.0323-0.4395-0.0000

X16B 178-83 0.0843-0.0209-0.2786-0.0000

X16C 181-80 0.2541-0.0325-0.4366-0.0000

X16D 181-80 0.1436-0.0261-0.3517-0.0000

X16E 185-76 0.5459-0.0367-0.4992-1.0000

X16F 179-82 0.0447-0.0155-0.2072-0.0000

X16G 180-81 0.1611-0.0275-0.3687-0.0000

X16H