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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. The following data are contained in the file named Consumer.   Use methods of descriptive statistics to summarize the data. Comment on the findings. 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. Develop an estimated regression equation with annual income and household size as the independent variables. Test the significance of the overall model at 95% confidence. Write your hypothesis. Test the significance of regression parameters at 95% confidence level. Comment on at least two of the regression assumptions for your multiple regression equation. Do you think there might be any violations of regression assumptions? What is the forecasted annual credit card charge for a three-person household with an annual income of $40,000? Create 95% prediction interval for your prediction. Income($1000s) HouseholdSize AmountCharged ($) 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

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. The following data are contained in the file named Consumer.   Use methods of descriptive statistics to summarize the data. Comment on the findings. 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. Develop an estimated regression equation with annual income and household size as the independent variables. Test the significance of the overall model at 95% confidence. Write your hypothesis. Test the significance of regression parameters at 95% confidence level. Comment on at least two of the regression assumptions for your multiple regression equation. Do you think there might be any violations of regression assumptions? What is the forecasted annual credit card charge for a three-person household with an annual income of $40,000? Create 95% prediction interval for your prediction. Income($1000s) HouseholdSize AmountCharged ($) 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

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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  1. 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. The following data are contained in the file named Consumer.

 

  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. Test the significance of the overall model at 95% confidence. Write your hypothesis.
  4. Test the significance of regression parameters at 95% confidence level.
  5. Comment on at least two of the regression assumptions for your multiple regression equation. Do you think there might be any violations of regression assumptions?
  6. What is the forecasted annual credit card charge for a three-person household with an annual income of $40,000? Create 95% prediction interval for your prediction.
    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
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can you explain more in detail what you would input in excel for part 3. I keep getting an error message. Would the excel sheet look different if I don't include the 95% confidence interval

 

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