Q3. Perform and Interpret a Bivariate Linear Regression

This analysis will be performed on a data set collected by a national company on their 27 chain stores. The marketing department would like to know how various factors contribute to the net sales (Netsales) amount for a chain store. Create an SPSS data file by importing the Q3Q4 data. Configure the "measure" for each variable.

Q3A. Perform bivariate (Pearson's) correlations among all the variables in the data set. Report the correlation coefficient for each of the following pairs of variables:

Storesize and Netsales: r =

Adcost and Netsales: r =

Area and Netsales: r =

Competitor and Netsales: r =

Q3B. Create a scatterplot for the strongest correlation from Q1A, with Netsales plotted on the Y axis.

Q3C. Perform a bivariate (simple) linear regression with Netsales as the outcome variable. Use the variable that has the strongest correlation with Netsales as the predictor. Report the omnibus regression results.

F( , ) = , p = , Adjusted R² =

Q3D. Use the result from Q3C to answer the following questions:

• Can we reject the null hypothesis?
• Does the regression model significantly predict Netsales?

Group of answer choices

(a) Yes; No

(b) No answer text provided.

(c) Yes; Yes

(d) No answer text provided.

(e) No; Yes

(f) No; No

Q3E. What percentage of the variance in "Netsales" can be predicted by this regression model?

Data:

Netsales	Storesize	Adcost	Area	Competitor
10.00	0.50	3.00	4.30	1
15.00	0.60	2.50	2.50	8
20.00	1.20	3.30	2.10	5
50.00	1.10	3.10	1.60	13
65.00	1.20	4.70	3.30	8
68.00	0.60	4.90	4.70	5
98.00	1.60	4.60	2.70	10
99.00	0.80	2.80	6.50	12
156.00	2.20	6.90	4.10	0
161.00	2.60	7.20	6.30	11
195.00	2.50	7.70	8.40	4
231.00	3.00	8.20	8.20	0
299.00	3.10	8.10	10.10	4
341.00	3.50	9.80	11.50	14
347.00	3.60	9.60	11.30	14
397.00	3.80	10.40	13.90	11
398.00	4.30	5.50	16.00	10
400.00	8.60	7.00	12.00	15
428.00	4.20	10.50	14.00	7
437.00	4.40	10.60	14.10	1
464.00	4.70	11.30	15.00	7
487.00	4.80	11.80	12.70	3
497.00	5.30	11.50	16.30	12
507.00	5.10	12.00	15.70	15
519.00	5.50	12.00	16.10	1
528.00	5.60	12.30	16.00	12
570.00	5.40	17.40	12.30	6