# Lowes, a home improvement retailer, has authorized its marketing research department to make a study of…

Lowes, A home improvement store has granted authorization for its
Market research department will conduct an analysis of customers who are currently in the market.
been issued Lowes Card. Market research
Department hopes to determine the important variables that explain
Variation in purchasing. After these variables have been determined
This department hopes to draw in new customers.
It is expected that there will be a large volume of sales. Twenty-five customers
These variables were randomly selected.
These were also recorded

=        Average monthly
purchases (in dollars) at Lowes

x1
=      Customer age

x2
=      Customer family income

x3
=      Family size

The Excel worksheet below shows a part of the data. A
These data were used in the development of a regression model. This partial
Below are data and Excel regression output (complete data).
All twenty-five of our customers were used in the analysis. You can find this here
Answer the following questions with output

 Observation Purchase Volume (\$) Age Family Income (\$) Families 1 75 42 \$ 29,000 4 2 129 36 25,000 2 3 105 38 25,000 2 4 42 54 17,000 3 5 17 49 15,000 5 6 ? ? ? ? 7 ? ? ? ? 8 ? ? ? ? 9 ? ? ? ? 10 ? ? ? ? 11 ? ? ? ? 12 ? ? ? ? 13 ? ? ? ? 14 ? ? ? ? 15 ? ? ? ? 16 ? ? ? ? 17 ? ? ? ? 18 ? ? ? ? 19 ? ? ? ? 20 ? ? ? ? 21 105 30 26,000 2 22 121 27 18,250 3 23 14 62 10,250 3 24 37 50 18,100 2 25 43 26 24,500 4
 SUMMARY EXPUT Statistical Regression Multiple R R Square Adjusted R Square Standard Error 32.27240363 Observations 25 ANOVA df SS MS F Regression Residual 21871.66876 Total 38517.76 Coefficients Standard Error t Stat P-value Intercept 87.78972947 25.46767899 Age X1 -0.970467501 0.586041665 Family Income X2 0.002334262 0.000745097 Family Size X3 -8.723322293 7.495492501

12.

Requirements

Examine
Below is the correlation matrix.

 Purchase Volume (\$) Age Family Income (\$). Families Purchase Volume (\$) 1 Age -0.41 1 Family Income (\$). 0.46 0.05 1 Families -0.24 0.50 0.27

Is there a problem with multicollinearity?
This regression model? Let’s briefly and clearly discuss the criteria.
You can use this method to find your answer. Multicollinearity may be indicated
Determine the variables that are relevant.

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