A US consumer lobby wishes to develop a model to predict gas

A US consumer lobby wishes to develop a model to predict gasoline usage, as measured by miles per gallon, based on the weight of the car in pounds. The Excel data file AUTO.xls (contained in a folder under the CML Quizzes tab) contains data on this for fifty recent models. Use Excel Data Analysis to estimate a linear model for the relationship, a 95% confidence interval for the slope coefficient and a residual plot. State all numerical answers below correct to four decimal places using the Excel output results.
1. the intercept Blank 1
2. the slope coefficient Blank 2 ,
3. the standard error of the estimate Blank 3
4. Using this model, predict the gasoline usage for a car weighing 1200 pounds. Use all decimal places in your calculation by selecting and using the values of b₀ and b₁ in the output generated by Excel.Blank 4
5. Does the prediction involve extrapolating the relationship? Type yes or no.Blank 5

State the

6. lower bound Blank 6 and
7. upper bound Blank 7 for the 95% confidence interval for the slope coefficient.

Gasoline usage (miles per gallon)	Horsepower	Weight (pounds)
43.1	48	1985
19.9	110	3365
19.2	105	3535
17.7	165	3445
18.1	139	3205
20.3	103	2830
21.5	115	3245
16.9	155	4360
15.5	142	4054
18.5	150	3940
27.2	71	3190
41.5	76	2144
46.6	65	2110
23.7	100	2420
27.2	84	2490
39.1	58	1755
28.0	88	2605
24.0	92	2865
20.2	139	3570
20.5	95	3155
28.0	90	2678
34.7	63	2215
36.1	66	1800
35.7	80	1915
20.2	85	2965
23.9	90	3420
29.9	65	2380
30.4	67	3250
36.0	74	1980
22.6	110	2800
36.4	67	2950
27.5	95	2560
33.7	75	2210
44.6	67	1850
32.9	100	2615
38.0	67	1965
24.2	120	2930
38.1	60	1968
39.4	70	2070
25.4	116	2900
31.3	75	2542
34.1	68	1985
34.0	88	2395
31.0	82	2720
27.4	80	2670
22.3	88	2890
28.0	79	2625
17.6	85	3465
34.4	65	3465
20.6	105	3380

Solution

SUMMARY OUTPUT Regression Statistics Multiple R 0.82480863 R Square 0.680309276 Adjusted R Square 0.673649053 Standard Error 4.668104259 Observations 50 ANOVA df SS MS F Significance F Regression 1 2225.864326 2225.864326 102.1451 1.78744E-13 Residual 48 1045.977474 21.79119737 Total 49 3271.8418 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 57.7972526 2.968970159 19.46710459 2.01E-24 51.82773811 63.76676709 Weight (pounds) -0.010613111 0.001050108 -10.10668657 1.79E-13 -0.012724494 -0.008501728 Intercept 57.7972526 Slope coefficeint -0.010613111 Standard error of the estimate 4.668104259 Gasoline when car weight 1200 pounds 45.06151946 Extrapolating the relation ship? NO Lower bound 51.82773811 upper bound 63.76676709