confused Problem #1: The paired data below consist of the test scores of 6 randomly selected students and the number of hours they studiedfor the test. Round to four decimals.Hours4Scores789685807490a) Find the value of the linear correlation coefficientr.b) Find the P-valuec) Compare the P-value to a significant level of a=0.05, is there a linear correlation between the hours of studying and thetest scores?CAUTION: Know that correlation does not imply causality.Part 2: Hypothesis TestSTEP 1: We can identify the null and the alternative hypotheses as follow:H: p= 0 (there is no correlation)H:: p= 0 (there is a correlation)Step 2: Find rStep 3: Find the test statistic and P-valueStep 4: Decision about the null hypothesis. (P-value sa: Reject H: ; P-value >a: Fail to reject the H.)Step 5: conclusion about the claim.StatCrunch commands: stat < regression < simple linear < choose x and y < choose Hypothesis test< compute!

The test scores of 6 randomly selected students and the number of hours they studied for the test are, Hours Scores 4 78 8 96 6 85 5 80 4 74 9 90 The value of the linear correlation coefficient, We enter the given dataset in R studio and then compute correlation coefficient as, Therefore, the correlation coefficient r = 0.9115 (Round to 4 decimals) Hypotheses: H0: ρ = 0 H1: ρ ≠ 0 To test the above hypothesis we conduct the correlation significant test in R studio and find the test statistic and p value as, from the above R output of correlation significant test we can write, The test statistic = t = 4.4331 p-value = 0.01139 Decision: since the p-value 0.01139 is less than the significance level 0.05 we Reject the H0 (null hypothesis) Conclusion: There is a enough evidence to support the claim that there is a significant relationship between The test scores and the number of hours studied for the test.