Use the below data given to answer the below questions for a case report.

A. Data sources

B. Key results and tables (ANOVA table, regression plots, etc.)

C. A discussion of the data (for the final question, be sure to touch on possible multicollinearity)

Data Given

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

EXAMPLE

III. Data sources. Data for this study was obtained in our company's internal documents from the Operations Department (stated in the original problem). IV. Key results tables, interpretations and discussions [ together or separate] With the data obtained, we conduct the regression analysis using Excel's Linear Regression function, and attach the summary output and related figure below: SUMMARY OUTPUT Correlation Analysis Regression Statistics CcSpending Anincome Multiple R 0.xxxxxxx9 CcSpending R Square O.AB AnIncome -0.XYXYXY Adjusted R Square 0.XYZStandard Error 2.QQQ Observations 20 ANOVA df MS F Significance F Regression 1 ? ? 7 6.40178E-05 Residual 18 ? 6.0273634 Total 19 269.75 Standard Coefficients Error 1 Stat P-value Lower 95% Upper 95% Intercept 7.xyz D.ysz AnIncome -0.uyz The F test for the overall model is significant at .001 as is the t value testing the slope. The ~ of AB indicates that almost AB% of the variation of credit card spending is accounted for by the annual income. The standard error of the estimate is 2.QQQ which is a modest error. The regression equation has an intercept of 7.xyz which indicates that the model predicts that a household will have an average of AXYZ credit card spending if the household has no annual income. The significant t-Statistics at a=0.05 level for the annual income indicate that we could reject the null hypothesis that H.: b=0. The following figure also demonstrates the relationship between ABC and XYZ