Question

What is the relationship between the amount of time statistics students study per week and their final exam scores! The results of the survey are shown below The ruil and alternative hypotheses for correlation are The preluet: 1.0024 Round to four decimal places c. Use a level of sigrice -0.05 to state the conclusion of the hypothesis test in the context of There la statistically significant evidence la conclude that there a carrodation between the time sent studying and the score on the final exam. Thus, the regression Une s uclul. There is statistically imignificant evidence to conclude that student who spend more time studying will score higher on the final exam than a student who sends less time studying There is statistically incipicant cvidence to conclude that there is a correlation between the Cimen slutlying and the screen the firul exam. Thus, then the region line is real appropriate There is statistically significant evidence to condude that a student who spends more time studying will wore higher on the oxam than a student who spend less time studying ---x Round to two decimal places 74 of all students will reochuc the average score on the final can. There is a 74% chance that the regression Une will be a good predictor for the final exam score Based on the time spent studying Given any youp that spend final amunt af time studying per work, 74% of all of the students will receive the predicted score on the hal exam. There is a large nation in the final scores that students receive, but if you try look students who spend the amount of time studying per week, this waration an are i recuced by 245 1. The cquation of the near Pression line is IPC ILE sin lwn cemal ple) ? Use the model to predict the final ser score for a student who spends 11 hours per week studying, Finalem score - (Please round your answer to the nearest whole number

please correct red error boxes

Answer 1

S.No х y (X-X)? (1-7) 3 1 2 3 4 5 6 10 15 5 12 0 15 9 9 58 75 89 77 79 54 96 84 92 704 32.1111 1.7778 40.1111 13.4444 11.1111 75.1111 40.1111 0.1111 0.1111 214.0000 SSX 408.94 10.38 116.16 1.49 0.60 586.72 316.05 33.38 189.83 1663.5556 SSY (X-X)(y-7) 114.5926 -4.2963 68.2593 4.4815 2.5926 209.9259 112.5926 1.9259 4.5926 514.6667 7 8 9 Total Mean 78 8.667 78.2222 SXY sample size n. 9 = 214.000 8.6667 y = 78.2222 Son (X-X)= Sw Z(X-7)(y-Y)= slope- . 5./5.- intercept B. - V-B,x= 514.667 2.4050 со 57.3790

a)

correlation r='Sxy/(√Sxx*Syy) =

0.86

d)

r² =0.74

f)

y^ = 57.38+2.40x