Can you provide detail explanation of each step and solutions please.This question require the use of MATLAB results are obtained from MATLAB.

Question 2

Attendance at 41 AFL matches played on different weekends at the MCG was recorded over the 1993 and 1994 seasons. The administration staff wanted to know if the total number of signed members for both clubs participating in each match (Members in the thousands) could be used as a predictor for the attendance (Attendance in the thousands) to better prepare the ground for each game.

(a) The data is afl.xls. and shown in the Table below the question (First column is members, second column is attendance). Let us assume, for part (a), that there IS a linear relationship between Members and Attendance.

i. Using MATLAB, calculate the equation of best fit, assuming a linear relationship between members and attendance. (Show all MATLAB commands).

ii. Perform an appropriate hypothesis test to determine whether there is a statistically significant linear relationship between Attendance and Members at the 5% level. Include the appropriate null and alternative hypotheses, test statistic, P-value, and conclusion. Define any parameters you use.

(b) Give the MATLAB commands to calculate the residuals, and to make a residuals' scatter plot (of Members versus residuals). From this plot, or any method, explain why one of our assumptions (about the linear regression errors) does NOT hold. Optional but not required: It may help to write an additional command to make a scatter plot of the Members versus the absolute values of the residuals. (You do not need to include the plots with your answers, but you must show the MATLAB commands used to generate them).

The data of afl.xls is shown as Table below:

Members	Attendance
12.601	8.653
25.991	49.856
16.948	24.362
27.046	46.588
22.874	29.296
51.646	34.372
13.015	17.781
29.945	37.119
21.643	44.094
21.464	19.057
17.296	20.543
25.597	40.819
21.485	44.303
25.991	67.035
22.351	34.439
24.363	30.874
23.024	40.229
36.327	85.054
18.329	31.109
43.253	39.492
22.001	27.195
32.36	19.609
29.346	61.193
39.164	74.33
34.486	27.022
20.579	34.601
31.942	35.851
13.673	19.333
33.102	75.129
28.265	52.199
18.33	26.917
18.453	32.528
29.223	50.141
17.36	49.878
38.083	85.381
30.768	38.858
29.346	43.132
19.875	33.503
30.52	49.872
34.276	66.555
36.909	61.231