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.
|
Income ($1000s) |
Household Size |
Amount Charged ($) |
| 54 | 3 | 4,016 |
| 30 | 2 | 3,159 |
| 32 | 4 | 5,100 |
| 50 | 5 | 4,742 |
| 31 | 2 | 1,864 |
| 55 | 2 | 4,070 |
| 37 | 1 | 2,731 |
| 40 | 2 | 3,348 |
| 66 | 4 | 4,764 |
| 51 | 3 | 4,110 |
| 25 | 3 | 4,208 |
| 48 | 4 | 4,219 |
| 27 | 1 | 2,477 |
| 33 | 2 | 2,514 |
| 65 | 3 | 4,214 |
| 63 | 4 | 4,965 |
| 42 | 6 | 4,412 |
| 21 | 2 | 2,448 |
| 44 | 1 | 2,995 |
| 37 | 5 | 4,171 |
| 62 | 6 | 5,678 |
| 21 | 3 | 3,623 |
| 55 | 7 | 5,301 |
| 42 | 2 | 3,020 |
| 41 | 7 | 4,828 |
| 54 | 6 | 5,573 |
| 30 | 1 | 2,583 |
| 48 | 2 | 3,866 |
| 34 | 5 | 3,586 |
| 67 | 4 | 5,037 |
| 50 | 2 | 3,605 |
| 67 | 5 | 5,345 |
| 55 | 6 | 5,370 |
| 52 | 2 | 3,890 |
| 62 | 3 | 4,705 |
| 64 | 2 | 4,157 |
| 22 | 3 | 3,579 |
| 29 | 4 | 3,890 |
| 39 | 2 | 2,972 |
| 35 | 1 | 3,121 |
| 39 | 4 | 4,183 |
| 54 | 3 | 3,730 |
| 23 | 6 | 4,127 |
| 27 | 2 | 2,921 |
| 26 | 7 | 4,603 |
| 61 | 2 | 4,273 |
| 30 | 2 | 3,067 |
| 22 | 4 | 3,074 |
| 46 | 5 | 4,820 |
| 66 | 4 | 5,149 |
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?
In: Statistics and Probability
***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.”
| Income ($1000s) | Household Size | Amount Charged ($) |
| 54 | 3 | 4016 |
| 30 | 2 | 3159 |
| 32 | 4 | 5100 |
| 50 | 5 | 4742 |
| 31 | 2 | 1864 |
| 55 | 2 | 4070 |
| 37 | 1 | 2731 |
| 40 | 2 | 3348 |
| 66 | 4 | 4764 |
| 51 | 3 | 4110 |
| 25 | 3 | 4208 |
| 48 | 4 | 4219 |
| 27 | 1 | 2477 |
| 33 | 2 | 2514 |
| 65 | 3 | 4214 |
| 63 | 4 | 4965 |
| 42 | 6 | 4412 |
| 21 | 2 | 2448 |
| 44 | 1 | 2995 |
| 37 | 5 | 4171 |
| 62 | 6 | 5678 |
| 21 | 3 | 3623 |
| 55 | 7 | 5301 |
| 42 | 2 | 3020 |
| 41 | 7 | 4828 |
| 54 | 6 | 5573 |
| 30 | 1 | 2583 |
| 48 | 2 | 3866 |
| 34 | 5 | 3586 |
| 67 | 4 | 5037 |
| 50 | 2 | 3605 |
| 67 | 5 | 5345 |
| 55 | 6 | 5370 |
| 52 | 2 | 3890 |
| 62 | 3 | 4705 |
| 64 | 2 | 4157 |
| 22 | 3 | 3579 |
| 29 | 4 | 3890 |
| 39 | 2 | 2972 |
| 35 | 1 | 3121 |
| 39 | 4 | 4183 |
| 54 | 3 | 3730 |
| 23 | 6 | 4127 |
| 27 | 2 | 2921 |
| 26 | 7 | 4603 |
| 61 | 2 | 4273 |
| 30 | 2 | 3067 |
| 22 | 4 | 3074 |
| 46 | 5 | 4820 |
| 66 | 4 | 5149 |
Managerial Report
In: Statistics and Probability
|
Stock X ($) |
Stock Y($) |
|
|
Investment Value |
||
|
1 January |
30 |
50 |
|
31 December |
29 |
56 |
|
Dividends received |
||
|
Q1 |
1 |
0 |
|
Q2 |
1.2 |
0 |
|
Q3 |
0 |
0 |
|
Q4 |
2.3 |
2 |
In: Finance
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:
In: Operations Management
Mr. L.V. is a 68-year-old male admitted to the coronary care
unit 24 hours ago with an anteroseptal myocardial infarction (MI).
His past medical history includes two other MIs within the last 5
years, obesity, hypertension, hyperlipidemia, and sleep apnea. L.V.
had chest pain at home for 12 hours before seeking medical
treatment. Lab results note troponin I at 5.2 mcg/L.
Mr. L.V. is currently pain free with stable VS. The heart monitor
shows sinus rhythm with occasional, unifocal premature ventricular
contractions and a heart rate (HR) in the 90s. His blood pressure
(BP) is 130/70, respiratory rate (RR) is 24 breaths/minute and
O2 saturation is 93% on O2 via nasal cannula
at 2 L/min. He has a heparin drip infusing at 1200 U/hr and IV
nitroglycerin infusing at 20 mcg/min. You are assigned to care for
L.V. as part of a two-patient assignment.
Question: Cardiogenic shock can result from a variety of initiating events. In addition to L.V.'s obvious myocardial infarctions, identify other potential contributing causes that you will assess in L.V.
In: Nursing
In: Chemistry
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
In: Statistics and Probability
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
In: Math
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?
In: Finance
Using the following dataset, conduct a one-way ANOVA and post-hoc comparisons if necessary. A real estate developer is considering investing in a shopping mall on the outskirts of Atlanta, GA. Three parcels of land are being evaluated. Of particular importance is the income in the area surrounding the proposed mall. A random sample of four families is selected near each proposed mall. The following are the sample results. At the 0.05 significance level, can the developer conclude there is a difference in the mean income?
|
Southwyck Area (in $1,000’s) (Group 1) |
Franklin Park (in $1,000’s) (Group 2) |
Old Orchard (in $1,000’s) (Group 3) |
|
64 |
74 |
75 |
|
68 |
71 |
80 |
|
70 |
69 |
76 |
|
60 |
70 |
78 |
1. (2 points) What is the F-value for the one-way ANOVA test:
a. 18.14
b. 14.18
c. 138.25
d. None of the above
2. (2 points) What is the p-value:
a. 0.0071
b. 14.18
c. 0.0017
d. None of the above
3. (2 points) What is the mean for Group 1:
a. 65.5
b. 71.0
c. 77.3
d. None of the above
4. (2 points) What is the mean for Group 2:
a. 65.5
b. 71.0
c. 77.3
d. None of the above
5. (2 points) What is the mean for Group 3:
a. 65.5
b. 71.0
c. 77.3
d. None of the above
6. (2 points) Is there a difference mean income between at least two of the areas?
a) TRUE b) FALSE
7. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 1 significantly different from Group 2?
a) TRUE b) FALSE
8. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 2 significantly different from Group 3?
a) TRUE b) FALSE
9. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 1 significantly different from Group 3?
a) TRUE b) FALSE
Using the following dataset, conduct a one-way ANOVA and post-hoc comparisons if necessary. The following is sample information. Test the hypothesis that all treatment means are equal at the 0.05 significance level.
|
Treatment 1 (Group 1) |
Treatment 2 (Group 2) |
Treatment 3 (Group 3) |
|
8 |
3 |
3 |
|
6 |
2 |
4 |
|
10 |
4 |
5 |
|
9 |
3 |
4 |
10. (2 points) What is the F-value for the one-way ANOVA test:
a. 21.94
b. 14.18
c. 31.083
d. None of the above
11. (2 points) What is the p-value:
a. 0.01
b. 0.05
c. 0.03
d. None of the above
12. (2 points) What is the mean for Group 1:
a. 3.0
b. 4.0
c. 5.1
d. None of the above
13. (2 points) What is the mean for Group 2:
a. 3.0
b. 4.0
c. 5.1
d. None of the above
14. (2 points) What is the mean for Group 3:
a. 3.0
b. 4.0
c. 5.1
d. None of the above
15. (2 points) Is there a difference mean income between at least two of the treatment groups?
a) TRUE b) FALSE
16. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 1 significantly different from Group 2?
a) TRUE b) FALSE
17. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 2 significantly different from Group 3?
a) TRUE b) FALSE
18. (2 points) Using the results of the Tukey test (alpha = 0.05), is Group 1 significantly different from Group 3?
a) TRUE b) FALSE
Use the following dataset for the next four questions:
X: 5 3 6 3 4 4 6 8
Y: 13 15 7 12 13 11 9 5
19. (3 points) What is the Pearson correlation value r(x,y)? r = _________
a. -0.98
b. -0.89
c. 0.89
d. None of the above
20. (3 points) Is the “r” signifcant at alpha = 0.05?
a) TRUE
b) FALSE
21. (4 points) Identify the regression equation below
a. Y = 19.12 + 1.74(X)
b. Y = 19.12 – 1.74(X)
c. Y = -4.802 – 1.74(X)
d. None of the above
22. (3 points) Calculate the value of Y when X is 7:
a. 9.64
b. 4.96
c. 6.94
d. None of the above
Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the Y column shows the value of sales (in thousands $) last month for each client sampled.
|
Number of Contacts (X) |
Sales (in thousands $) Y |
|
14 |
24 |
|
12 |
14 |
|
20 |
28 |
|
16 |
30 |
|
46 |
80 |
|
23 |
30 |
|
48 |
90 |
|
50 |
85 |
|
55 |
120 |
|
50 |
110 |
a. Sales = -12.2 + 2.19(Contacts)
b. Sales = 2.19 – 12.2(Contacts)
c. Sales = 6.56 + 0.176(Contacts)
d. None of the above
24. (3 points) Calculate the estimated sales if 40 contacts are made:
a. Approximately 57
b. Approximately 75
c. Approximately 85
d. Approximately 105
In: Statistics and Probability