Miguel Caballero
010040535
BIO 342L
Th 9-11:45AM

Lab Report 1: Introduction to Statistics and Graphing

Comparison of jump height between males and females

Figure 1: Comparison of avg jump (in CM) between males (n=11) and females (n=10) with a p-value of 0.00203. This p-value indicates a significant difference between the avg. jump heights of males and females. The bars are the avg. jump heights along with standard deviation of the mean.
Results: The p-value of 0.00203 is p<0.05 thus we reject the null hypothesis and conclude that there is a significant difference between the two means. A big part that contributes to this result (significant differences) is that males on average tend to have more muscle mass than females (largely due to higher testosterone levels) thus, are able to generate more power and hence a bigger jump height. Additionally, muscle to fat ratio is higher in males in males than in females. Physiologically, females tend to have more body fat hence decreasing their overall lower muscle to fat ratio and in a sense are weighed down versus the males which tend to have less body fat. Other sources of error could be that males tend to be more competitive versus females and that the measuring methods were not the best (eyeballing where the person’s hand landed on the ruler).

Comparison of calf circumference and jump height in males

Figure 2: Comparison of avg. calf circumference and jump height (both in CM) in males (n=11). A R2 value of .0001 (0.000102 in Excel worksheet) indicates a very poor relationship between calf circumference and jump height.
Results: The R2 value of 0.000102 shows a weak relationship between calf circumference and jump height. This means that one cannot predict jump height by knowing the calf circumference. Considering quads and hamstrings are bigger muscles and appear to generate much of the power