Gift Card Sales. For the holiday season of 2017, nearly 59 percent of consumers planned to buy gift cards. According to the National Retail Federation, millennials like to purchase gift cards (Dayton Daily News website). Consider the sample data in the file GiftCards. The following data are given for a sample of 600 millennials: the amount they reported spending on gift cards over the last year, annual income, marital status (1 = yes, 0 = no), and whether they are male (1 = yes, 0 = no).

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Gift Card Sales. For the holiday season of 2017, nearly 59 percent of consumers planned to buy gift cards. According to the National Retail Federation, millennials like to purchase gift cards (Dayton Daily News website). Consider the sample data in the file GiftCards. The following data are given for a sample of 600 millennials: the amount they reported spending on gift cards over the last year, annual income, marital status (1 = yes, 0 = no), and whether they are male (1 = yes, 0 = no).

 

  1. Write out the regression equation. Discuss each For example do the signs of the coefficients make sense to you.  For example ,what is  the impact of an additional  $10,000 of  annual income , etc.                                                                                                                                                               
  2. What is the value for Coefficient of Determination?. Interpret .
  3. Using original equation, part a. What would be the estimated spend of a single male with annual income of $100,000?  

 

 

Regression Statistics
Multiple R
0.870273871
R Square
0.757376611
Adjusted R Square
0.756155352
Standard Error
14.69324313
Observations
600
Rectangular Snip
ANOVA
df
SS
MS
F
Significance F
Regression
3
401662.0627 133887.3542 620.1606832
8.7083E-183
Residual
596
128671.2707
215.8913937
Total
599
530333.3333
Coefficients
Standard Error
t Stat
P-value
Lower 95% Upper 95% ower 95.0%pper 95.0%
Intercept
-3.999536938
3.059355275 -1.307313659 0.191610315 -10.00796465 2.008891
-10.008 2.008891
Annual Income
0.000213202
3.1402E-05 6.789441558 2.72685E-11
0.00015153 0.000275 0.000152 0.000275
Married
45.78086953
1.202031639
38.08624336
8.444E-162
43.42013677
48.1416 43.42014
48.1416
Male
21.91756988
1.201226252 18.24599641 2.00455E-59 19.55841886 24.27672 19.55842 24.27672
Transcribed Image Text:Regression Statistics Multiple R 0.870273871 R Square 0.757376611 Adjusted R Square 0.756155352 Standard Error 14.69324313 Observations 600 Rectangular Snip ANOVA df SS MS F Significance F Regression 3 401662.0627 133887.3542 620.1606832 8.7083E-183 Residual 596 128671.2707 215.8913937 Total 599 530333.3333 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% ower 95.0%pper 95.0% Intercept -3.999536938 3.059355275 -1.307313659 0.191610315 -10.00796465 2.008891 -10.008 2.008891 Annual Income 0.000213202 3.1402E-05 6.789441558 2.72685E-11 0.00015153 0.000275 0.000152 0.000275 Married 45.78086953 1.202031639 38.08624336 8.444E-162 43.42013677 48.1416 43.42014 48.1416 Male 21.91756988 1.201226252 18.24599641 2.00455E-59 19.55841886 24.27672 19.55842 24.27672
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