Statistical analysis

This is our correlation value.

Our variables are:
1) Length of left forearm-independent variable (scale data)
2) Length of left foot-dependent variable (scale data)

We will be using Pearson's R to compute the correlation coefficient, with the following assumption net.

Assumption 1: All observations must be independent of each other.

Assumption 2: The dependent variable should be normally distributed at each value of the indepedent variable.

Assumption 3: The dependent variable should have the same variability at each value of the independent variable.

Assumption 4: The relationship between the dependent and independent variables should be linear.

The diagram below is a scatter plot to check for linearity and homogenous variance in assumption 3 and 4.



The table below shows Pearson's correlation coefficient of 0.877 which indicates a very strong relationship between the length of arm and foot.