Linear Regression and the "fitting-line"
Exercise 1: The following table shows how many weeks six persons have worked at an automobile inspection station and the number of cars each one inspected between 3 p.m. and 5 p.m. on a given day:
|
Number of weeks employed
|
Number of cars inspected
|
|
5
|
15
|
|
2
|
13
|
|
9
|
23
|
|
7
|
21
|
|
12
|
21
|
|
1
|
14
|
(a) Given that, ∑x = 36; ∑y = 107; ∑x2 = 304; ∑xy = 721. Use the computing formulas to find a and b, and hence the equation of the least-squares line.
(b) Draw a scattergram of this data; then draw the straight line computed here above.
Correlation Analysis and "goodness of fit"
Exercise 3: The following data show the average number of hours that a sample of 6 MBA students spent on homework per week and their grade-point indexes for the courses they took in that semester: Calculate r.
|
Hours scent on homework x
|
Grade-point index y
|
|
15
|
2.0
|
|
28
|
2.7
|
|
13
|
1.3
|
|
20
|
1.9
|
|
4
|
0.9
|
|
10
|
1.7
|
Exercise 6: Give examples when you expect a positive correlation, negative correlation or no correlation.
Attachment:- Assignment.rar