Create a scatter plot of the data. This can be done within the correlation analy
ID: 3359088 • Letter: C
Question
Create a scatter plot of the data. This can be done within the correlation analysis in SAS. Briefly comment on what you see from the scatter plot.
What are the null and alternative hypotheses to test that flexion and extension velocities are correlated?
Perform the correlation analysis in SAS. What are the estimated correlation coefficient and p-value?
What is the conclusion using an alpha level of 0.05 to the test in part (ii) based on the results you obtained in part (iii)?
What is the 95% confidence interval for the true correlation between flexion and extension velocities? Interpret the confidence interval in the context of the problem.
Simple Statistics Variable flexion extension 18261.86667 109.87961 4710 100.00000 450.00000 Mean Std Dev Sum Minimum Maximum Pearson Correlation Coefficients, N = 18 Prob > Irl under H0: Rho=0 fexion extension 0.88219 4.0001 1.00000 flexion 1.00000 0.88219 .0001 extension Pearson Correlation Statistics (Fisher's z Transformation) H0: Rho=Rho0 Rho0 p Valu 0Explanation / Answer
From the scatter plot, it is evident that there is some kind of relationship between the two variables since with increasing flexion, extension is observed to increase. So there is a positive correlation between the two.
Null hypothesis -> H0 : = 0
Alternative hypothesis -> H0 : 0
Estimated correlation coefficient = 0.8763
p-value < 0.0001
Since p-value is very small, we reject the null hypothesis and conclude that there is significant correlation between extension and flexion.
95% CI : (0.69292,0.9532)
This interval gives an estimate of the interval where the actual population correlation coefficient may fall into based on the given sample data.
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