Physiology Intro to Stats

624 Words3 Pages
Miguel Caballero
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
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Maybe calves do play a roll but one that causes a relationship between the two. Other factors could have affected the overall results could be that the jumping was not standardized, lack of a bigger sample size, and the fact that when measuring the jump height it had to be predicted where the person’s hand reached, thus leading to huge assumptions on the measuring part.

Comparison of calf circumference and jump height in females

Figure 3: Comparison of avg. calf circumference and jump height (both in CM) in females (n=10). A R2 value of 0.0426 (0.042592 in EXCEL) indicates a weak relationship between calf circumference and jump height.
Results: Obtaining a R2 value of 0.042592 means there is no relationship between calf circumference and jump height. One cannot determine the jump height by having the calf circumference. Similarly with the calf circumference and jump height in males, physiologically, it would make more sense for the hamstrings and quads to play a bigger role in jumping height as they are bigger muscles and generate most of the force to jump. Even if calf circumference did have a role it might be insignificant. Additionally, there could have been other factors that contribute to the end results: everyone not jumping with the same intent (max effort versus minimal effort), possible injuries, or soreness. Another source that could have contributed to end results for being what they are is the lack of a big sample size. Additionally, measuring the

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