The retail company XYZ is conducting a study trying to explain and predict custo
ID: 3305966 • Letter: T
Question
The retail company XYZ is conducting a study trying to explain and predict customer spending in their retail stores. They compiled the database from their own records and customer surveys, which contains the following information organized per transaction:
Customer spending per store visit (dependent variable) – measured in $
Season when purchase is completed (summer, spring, winter, and fall). For every season there is a variable that indicate the season (0 – no, 1 – yes).
Customer’s gender – 0 male, 1 – female
Marital Status – 0 – single, 1 – married
Household income – the total income of the household measured in $
Retired status – 0 – no, 1 – retired
Education – number of years that customer spent on education.
Coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std. Error
Beta
(Constant)
0.865
7.025
-7.24
0.60
Education
1.113
2.995
.004
.37
0.04
Household income
5.957
5.622
.413
-1.23
0.00
Retired
-8.737
5.009
-.050
4.14
0.01
Marital status
13.497
4.338
.454
35.86
0.00
Gender
11.305
5.812
.362
31.19
0.60
Winter
11.640
4.120
.002
.15
0.03
Fall
6.975
3.715
.017
1.33
0.44
Summer
-5.010
4.012
.016
1.24
0.21
Population in the store area
2.964
5.345
.361
33.85
0.71
a. Dependent Variable: Customer spending per store visit in dollars
****Based on the output above, answer the following question: describe the demographics and geographics of the most profitable market segment.****
Note: please review the segmentation theory from your marketing classes to make sure that you consider appropriate variables.
Coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
B
Std. Error
Beta
(Constant)
0.865
7.025
-7.24
0.60
Education
1.113
2.995
.004
.37
0.04
Household income
5.957
5.622
.413
-1.23
0.00
Retired
-8.737
5.009
-.050
4.14
0.01
Marital status
13.497
4.338
.454
35.86
0.00
Gender
11.305
5.812
.362
31.19
0.60
Winter
11.640
4.120
.002
.15
0.03
Fall
6.975
3.715
.017
1.33
0.44
Summer
-5.010
4.012
.016
1.24
0.21
Population in the store area
2.964
5.345
.361
33.85
0.71
a. Dependent Variable: Customer spending per store visit in dollars
Explanation / Answer
Rolling a single die
1) probability of rolling divisors of 6 :
Since its a single die, the possible outcomes are 1,2,3,4,5,6. All have equal probability(1/6) since its a fair die
Out of these divisors of 6 are 1,2,3,6. So P(divisors of 6) = 1/6*1/6*1/6*1/6 = 1/1296 = 0.0008
2) probability of rolling a multiple of 1: Since all(1,2,3,4,5,6) are multiples of 6 = 1/6*1/6*1/6*1/6*1/6*1/6= 1/46656 = 0.00002
3) probability of rolling an even number : There are 3 even numbers between 1-6 i.e. 2,4,6
Hence probability of rolling an even number = 1/6*1/6*1/6 = 1/216 =0.0046
4) List of all possible outcomes of rolling a single die ={1,2,3,4,5,6}
5) probability of rolling factors of 3 : Factors of 3 are 1,3
Hence probability of rolling factors of 3 = 1/6*1/6 = 1/36 = 0.0278
6) probability of rolling a 3 or smaller : 3 or smaller are 1,2,3. Hence the probability = 1/6*1/6*1/6 = 1/216 = 0.0046
7) probability of rolling a prime number: Prime numbers between 1-6 are 2,3,5 hence probability = 1/6*1/6*1/6=1/216=0.0046
8) probability of rolling factors of 4 : Factors of 4 are 1,2,4 hence the probability = 1/6*1/6*1/6 = 1/216 =0.0046
9) probability of rolling divisors of 30 : Divisors of 30 are 1,2,3,5,6 = 1/6*1/6*1/6*1/6*1/6 = 1/7776 = 0.0001
10) probability of rolling factors of 24: Factors of 24 are 1,2,3,4,6 = 1/6*1/6*1/6*1/6*1/6=1/7776=0.0001
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