Statistical Analysis

Variables:

Independent: Average leg length (Scale)
Dependent: Walking speed (Scale)

Extraneous Variables:

1) Motivational level of the participants

2) Footwear of the participants

3) Weight of the participants (before and after a meal)

4) Fitness level of the participants

5) Current illness/ Previous medical history of the participants

Since our research question is a correlation question, and our data is scale, Pearson’s R was chosen to be the statistical test.

Selection of Statistics Test from Statistics In Health Sciences 5th Edition Appendix 1

Symmetric Measures
		Value	Asymp. Std. Errora	Approx. Tb	Approx. Sig.
Interval by Interval	Pearson's R	.269	.113	1.933	.059c
Ordinal by Ordinal	Spearman Correlation	.281	.134	2.026	.048c
N of Valid Cases		50
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation. Ho Hypothesis: There is no relationship between the average leg length and walking speed.

H1 Hypothesis:  There is a positive relationship between the average leg length and walking speed. Assume significance level, α= 0.05. From the table, a Pearson's correlation coefficient (r = 0.269) indicates a poor relationship between the average length of lower limb and walking speed. Since the p-value is 0.059, which is > 0.05, H1 hypothesis is rejected. Therefore, we conclude that there is NO relationship between the average leg length and walking speed.