Determine the regression equation


Assignment:

Q: Big Mountain Power Company serves a region in which the following amounts of electricity are used annually (in millions of kilowatt hours).

Year

Consumption

Year

Consumption

1999

352

2004

382

2000

357

2005

389

2001

362

2006

391

2002

369

2007

394

2003

380

2008

405

1. Plot the data.           

2. Determine the regression equation and draw the line.

3. Forecast consumption for 2010 and 2011.                   

 

Low

Medium

High

Total

Homemaker

14

26

6

46

Blue Collar

16

42

16

74

White Collar

9

32

30

71

Professional

0

8

15

23

Total

39

108

67

214

Occupation

  Family income

Based on the above table

4. Find the probability that a person selected would:

a. Have a low income

b.  Be a professional

c. Have a high incomed. Be a white collar worker

5. Using the method of least square regression, construct an equation for the estimated regression line and draw it.

You are conducting research into the reasons for the high turnover among lab technicians in a large pharmaceutical company. You have theorized the amount of job satisfaction is related to turnover, that is satisfied people tend to stay. You use a standardized survey to measure job satisfaction and are interested in whether there are significant differences between individuals working in palliative drugs (improving the quality of life for terminal patients) and those working in therapeutic drugs (drugs that may cure terminal diseases).

You break the satisfaction scores into four categories: high satisfaction, moderate satisfaction, moderate dissatisfaction, and high dissatisfaction and create a cross-tabulation with the departments in which the technicians work.

 

High Sat.

Mod. Sat

Mod Dissat.

High Dissat.

Total

Palliative

8

12

30

22

 

Therapeutic

12

24

16

13

 

Total

 

 

 

 

 

6. Is there a significant difference between these two areas?

7.  What does it indicate about technicians satisfaction?  Explain why you think this is.

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Applied Statistics: Determine the regression equation
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