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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
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
2.0
28
2.7
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
Exercise 1, 3 and 6 needs to be done only, 3 exercises which should be solved. Straight forward, as there are examples in the attached pdf for guideline. Give examples when you expect a positive correlation, negative correlation or no correlation.
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