1. (0.8) two areas of a large city are being considered as the seat of
day care centres. Of 200 families interviewed in one section.
the proportion of mothers working full - time was 0.52. In
the other section, 40 % of the 150 families interviewed had mothers who
they worked full-time jobs. With a level of significance
of o =0.04. is there is a significant difference in the proportion of mothers
who work full - time in the two areas of the city?.

Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviors for a variety of firms. In one study, a client asked for an investigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on an annual income, household size, and annual credit card charges for a sample of 50 consumers. The following data are contained in the file below.

Managerial report:

1) Use methods of descriptive statistics to summarize the data. Comment on the findings

2) Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings.

3) Develop an estimated regression equation with annual income and household size as independent variables. Discuss your findings.

4) What is the predicted annual credit card charge for a three-person household with an annual income of $40,000?

5) Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?

***PLEASE SHOW HOW TO SOLVE IN EXCEL***

Case Problem 3:        Consumer Research, Inc.

(Copy the worksheet named “Consumer” in QMB3200-Homework#10Data.xlsx into your file for this problem)

Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviors for a variety of firms. In one study, a client asked for an investigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 50 consumers and are provided in the worksheet named “Consumer.”

Managerial Report

1. Use methods of descriptive statistics to summarize the data. Comment on the findings.
2. Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings.
3. Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings.
4. What is the predicted annual credit card charge for a three-person household with an annual income of $40,000?
5. Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?

1. For both stocks X and Y, calculate the holding period return (over one year) for both stocks.
2. If you continue holding these two stocks beyond the first year, which component do you think might not continue to be realised in future (explain)
3. Assuming that the two stocks have the same risk, which one would you prefer to own?
4. What factors could explain why the return of these two stocks is not in the same form?                                          

v

What type of organizations use flextime? What are the benefits of flextime? Are there disadvantages to using flextime? Explain.

See more information on flextime at: The Ups And Downs Of Flex Time

Discussion Requirements:

• You are required to make one original post and two classmate replies (one reply each to two different classmates) in each discussion.
• Your post to each discussion must be at least two full paragraphs and 200 words in length. It must contribute significantly to the discussion topic.
• Your replies must be at least 50 words in length and add meaningful contributions to the discussion.
• Explain your answers.
• You may use examples, experiences, cases and/or opinions to make your points.

A real estate Association in a suburban community would like to study the relationship between the size of a single-family house (as measured by number of rooms) and the selling price of the house (in thousands of dollars). Two different neighborhoods are included in the study, one on the east side of the community (=0) and the other on the west side (=1). A random sample of 20 houses was selected with the results given at left.

a. State the multiple regression equation that predicts the selling price based on the number of rooms in the neighborhood.

b. Interpret the regression coefficients in a.

c. Predict the selling price for a house with nine rooms that is located in an East-side neighborhood. Construct a 95% confidence interval estimate and 95% prediction interval.

d. Perform a residual analysis on the results and determine if the regression assumptions are valid.

e. Is there a significant relationship between the selling price and two independent variables at the 0.05 level of significance?
Price Rooms Neighborhood
309.6 7 0
307.4 8 0
340.3 9 0
346.5 12 0
298.2 6 0
337.8 9 0
324.1 10 0
313.2 8 0
327.8 9 0
325.3 8 1
308.5 6 1
361.3 13 1
337.4 10 1
346.2 10 1
342.4 9 1
323.7 8 1
329.6 8 1
343.6 9 1
360.7 11 1
348.3 9 1

1. Choose the t test (which mean pick ONE) you think is appropriate out of the three t tests listed below to determine the t-value for the data (you can copy the results from your SPSS output and past them here:
   1. One sample (Mean) test
   2. Two samples (independent t-test) test
   3. Paired/related sample t tests
2. From the t test you ran above, tell me the confidence intervals (look under 95% CI, lower and upper) for the data and interpret what they mean.

Quality of Marriage             Quality of the Parent–Child Relationship

76                                                                    43

81                                                                    33

78                                                                    23

76                                                                    34

76                                                                    31

78                                                                    51

76                                                                    56

78                                                                    43

98                                                                    44

88                                                                    45

76                                                                    32

66                                                                    33

44                                                                    28

67                                                                    39

65                                                                    31

59                                                                    38

87                                                                    21

77                                                                    27

79                                                                    43

85                                                                    46

68                                                                    41

76                                                                    41

77                                                                    48

98                                                                    56

98                                                                    56

99                                                                   55

98                                                                    45

87                                                                   68

67                                                                   54

78                                                                   33

Rates are 8% p.a. compounded semi-annually.

a. You are going to make 30 monthly deposits of $500 each into your bank account starting in exactly 1 month. How much will you have immediately after the last deposit?

b. You are going to make 30 monthly deposits of $500 each into your bank account starting in exactly 7 months. How much will you have immediately after the last deposit?

c. You made the first of 30 monthly deposits of $500 each into your bank account exactly 7 months ago. How much will you have immediately after the last deposit?