Statistical Analysis using IBM SPSS Statistics Version 20
Here is the raw data from our data collection:
Here is the raw data from our data collection:
We used a scatter plot to determine the correlation between the length of the forearm and the length of the foot
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
From the above table, Pearson’s R = 0.736, p = 0 and N = 30.
Since p <0.05, we can reject the null hypothesis. From Pearson’s R value of 0.736, there is a strong, positive and significant relationship between length of forearm and length of foot.
To compute the regression equation, we use IBM SPSS Statistics Version 20 to generate the table:
Hence, the linear equation is (length of the foot) = 0.860 x (length of the forearm) + 3.302. This equation will be useful if we wanted to estimate the length of the foot when we know the length of the forearm, vice versa.
Now that we know that a relationship between the length of the forearm and the length of the foot exists, let us further analyze this relationship by breaking the respondents down into their different gender
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
From the results:
For males, there is a strong, positive and significant relationship between the length of the forearm and the length of the foot
(Pearson’s R = 0.726, p = 0.002, N = 15).
For females, there is a moderate, positive and significant relationship between the length of the forearm and the length of the foot
(Pearson’s R = 0.551, p = 0.033, N = 15).
Conclusion
Conclusion
In conclusion, the results support our hypothesis. There is a strong, positive and significant relationship between the length of the forearm and the length of the foot. This relationship is stronger in males compared to females. Upon knowing that this relationship exists, we can use the findings to estimate and tailor make the prosthesis for amputees according to an individual’s specifications. However, if we wanted to use the regression line to calculate either the length of the foot or the length of the forearm, we must take caution as this regression line is obtained from a small sample size of 30. To better reflect this relationship, more studies about the subject matter and a larger sample size are warranted.