Explain summary statistics. For example, what does this statistics tell you about each variable?

[Title of Research]

Names

Dependent Variable	MPG	Weight (Ton)	Drive Ratio	Horsepower	Displacement (litres)	Cylinders
Minimum	15.50	1.92	2.26	65.00	85.00	4.00
Maximum	37.30	4.36	3.90	155.00	360.00	8.00
Mean	24.76	2.86	3.09	101.74	177.29	5.39
Median	24.25	2.69	3.08	100.00	148.50	4.50
Standard Deviation	6.55	0.71	0.52	26.44	88.88	1.60
Range	21.80	2.45	1.64	90.00	275.00	4.00
Number of Observations	38	38	38	38	38	38

Summary Statistics

(Explain summary statistics. For example, what does this statistics tell you about each variable? What is the shape of the distribution of each variable?)

Correlation Coefficients

(Find correlation coefficient between the dependent variable and each of the independent variables)

Dependent Variable	MPG	Weight (Ton)	Drive Ratio	Horsepower	Displacement	Cylinders
MPG (Miles)	1
Weight (Ton)	-0.90	1
Drive Ratio	0.42	-0.69	1
Horsepower	-0.87	0.92	-0.59	1
Displacement	-0.79	0.95	-0.80	0.87	1
Cylinders	-0.81	0.92	-0.69	0.86	0.94	1

(Explain the correlation coefficients. What does it tell you about the relationship between the dependent and each of the independent variables?)

Scatter Plots

(Explain the scatter plots. What does it tell you about the relationship between the dependent and each of the independent variables? Does there exist any outliers?)

Regression Results

Y = 69.22 – 11.38x – 3.35x + .45x + .03x - .53x

Dependent Variable	Coefficients	t Stat	P-value
Intercept	69.22	14.96	0.00
Weight (Ton)	-11.38	-5.60	0.00
Drive Ratio	-3.35	-2.63	0.01
Horsepower	-0.04	-1.30	0.20
Displacement (liters)	0.03	1.65	0.11
Cylinders	-0.53	-0.78	0.44

(Interpret the coefficients for each of the independent variables, and t-statistic and p-value for each coefficient. For example, does Variable 1 have a significant impact on the dependent variable? Why or why not? How much impact does Variable 1 have on the dependent variable?)

Assess the Model’s Fit

[From Excel regression output, identify and interpret the measures for the fit of the model,

including the Standard Error of the Estimate (Se), Coefficient of Determination (Rsquared),

Adjusted R-squared, and F-statistic. What do these measures tell you about the

model’s fit?]

Regression Diagnosis

[Insert residual plots and histogram of residuals. Based on residual plots, explain

whether the required conditions for the residuals are satisfied. Comment on the

Goodness-of-Fit and validity of the model. Identify outliers if there exists any. Is your

model a valid model?]

Estimation

[Use the regression equation to estimate. For example, given certain values of the

independent variables, what is the predicted value for the dependent variable?]

Recommendations

[Based on the above regression analysis results, provide managerial decisions and/or