Math homework due date 2-27-2015

Assignment 3: Problems

Exercises

From your textbook, Statistics for Management and Economics, complete the following exercises:

· "Multiple Regression": Exercises 17.39, and 17.42

· "Time-Series Analysis and Forecasting": Exercises 20.19 and 20.35

Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet. Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text box.

Submit your workbook to this W5: Assignment 3 Dropbox by Friday, February 27, 2015.

Cite any sources using the APA format on a separate page.

Assignment 3 Grading Criteria	Maximum Points
Completed the exercises for "Multiple Regression" and imported the required data in a Microsoft Excel workbook.	25
Completed the exercises for "Time-Series Analysis and Forecasting" and imported the required data in a Microsoft Excel workbook.	25
Total:	50

17.39 Refer to Exercise 17.16. Calculate the correlation between the father's and the mother's years of education. Is there any sign of multicollinearity? Explain.

· 17.16 GSS2012* How does the amount of education of one's parents (PAEDUC, MAEDUC) affect your education (EDUC)?

· a. Develop a regression model

· b. Test the validity of the model

· c. Test the two slope coefficients

· d. Interpret the coefficients

· 17.42 Refer to Exercise 17.20.

· a. Calculate the correlation matrix.

· b. Are there signs of the presence of multicollinearity? Explain.

· c. Test the correlation between each independent variable and the dependent variable. Which independent variables are linearly related to the dependent variable?

· 17.20 GSS2008* Use the General Social Survey of 2008 to conduct a regression analysis of income (INCOME) using the following dependent variables:

· Age (AGE)

· Years of education (EDUC)

· Hours of work per week (HRS)

· Spouse's hours of work (SPHRS)

· Occupation prestige score (PRESTG80)

· Number of children (CHILDS)

· Number of family members earning money (EARNRS)

· Years with current employer (CUREMPYR)

· "Time-Series Analysis and Forecasting": Exercises 20.19 and 20.35

· 20.19 Xr20-932 Plot the following time series to determine which of the trend models appears to fit better.

Period	1	2	3	4	5
Time Series	55	57	53	49	47
Period	6	7	8	9	10
Time Series	39	41	33	28	20

MINITAB

INSTRUCTIONS

Follow the instructions on page 846. For Seasonal Length type 12, check Generate forecasts, type 12 for the Number of forecast, and type 60 for Starting from origin

· 20.35 The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the 7 values for next week.   ŷ = 120 + 2.3t    t = 1, 2, … , 28

Day	Seasonal Index
Sunday	1.5
Monday	.4
Tuesday	.5
Wednesday	.6
Thursday	.7
Friday	1.4
Saturday	1.9