Based on the Multiple Regression Output in Excel that you have created, using the data file provided to you, answer the following questions:
Note: In all questions, wherever needed, use the 10% level of significance to test the hypotheses (α = 0.10).
1. What is the Sample Regression Equation?
2. Which of the independent variables are significant? Why? Explain! Use α = 0.10 in ALL questions. Use only the p-value to explain your answers (No need to go to tables).
3. Test the overall significance of the model by relying on F Statistic.
4. What is the value of adjusted R-square? Verify its value, using the related formula in your Formula Sheet, for adjusted R-square and using the values in your Excel Printout.
5. Comment on the Normality assumption for the residuals for this model. In other words, has the normality assumption been satisfied? Explain your answer (Hint: you need to run Excel's Histogram feature for the column of the Residuals).
6. Do you see any indication of Autocorrelation? Using Excel Formula commands, calculate the value of the Durbin-Watson test statistics in Excel, based on the data, as you know, in the Residuals column, using the formula from your Formula Sheet or look below:
Durbin-Watson Test Statistics (Also: Use the chart for Durbin Watson test provided in the Formula Sheet, or below). For Durbin-Watson TABLE, you can use your textbook or the Internet.
The Durbin-Watson Test for Autocorrelation
0 to 4 scale:
0-dl: Autocorrelation
dl-du: Test is inconclusive
du to 4-du: No evidence of autocorrelation
4-du to 4-dl: Test is inconclusive
4-dl to 4: Autocorrelation
7. Do you see any evidence of Multicollinearity? Explain and provide evidence.
y x1 x2 x3
109000 0.19 133 7300
155000 0.41 13 18700
86060 0.11 20 15000
120000 0.68 31 14000
153000 0.4 33 23300
170000 1.21 23 14600
90000 0.83 36 22200
122900 1.94 4 21200
325000 2.29 123 12600
120000 0.92 1 22300
85860 8.97 13 4800
97000 0.11 153 3100
127000 0.14 9 300
89900 2 88 2500
155000 0.13 9 300
253750 2 7 49800
60000 0.21 82 8500
87500 0.88 17 19400
112000 1 12 8600
104900 0.43 21 5600
148635 0.32 1 6200
150000 0.03 24 5100
90400 0.36 16 5200
248800 4 28 5500
135000 1.83 126 6000
145000 3 26 4500
457000 0.43 53 2700
140000 0.44 56 19400
130000 1.24 51 24800
187000 0.46 3 15200
229000 0.87 9 41100
227000 1.8 201 25500
179900 0.46 1 15200
169900 0.91 19 20200
209900 0.46 1 15200
169900 0.59 10 17300
293000 7.24 43 36600
24590 0.19 2 20700
157000 0.46 45 20200
195000 0.41 32 27100
150000 0.78 54 24500
234900 0.89 9 41600
279550 1.34 60 44400
246500 1 70 17100
124000 1 98 15500
138000 0.27 54 8900
290000 0.71 73 61000
108000 0.9 48 19000
134900 0.24 10 8000
64500 0.06 16 1600
142000 0.55 20 13800
125000 0.34 32 11100
88000 0.19 15 3400
135000 0.23 135 8100
90000 0.07 14 1800
90100 0.09 15 2400
126900 0.25 10 8400
175000 0.47 15 27200
158000 0.36 10 12100
92000 0.07 14 1800
82800 0.11 225 3900
140000 0.23 25 8300
171000 3.16 15 24100
200640 0.08 4 32000
139000 0.57 30 7500
225000 0.5 12 15300
182000 1 16 26600
208767 0.5 8 32000
186000 0.55 17 4400
93000 0.1 14 2600
257386 0.5 90 32000
161000 0.31 10 10400
92000 0.28 18 6300
211002 0.06 12 32000
115000 0.06 14 1600