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Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5%
- Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5% level of significance. See Step 5 in the Python script. Include the following in your analysis:
- Define the null and alternative hypothesis in mathematical terms and in words.
- Report the level of significance.
- Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).
- Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?
- What is the slope coefficient for the weight variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value,, for weight in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.
- What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value,, for horsepower in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.
- What is the purpose of performing individual t-tests after carrying out the overall F-test? What are the differences in the interpretation of the two tests?
- What is the coefficient of determination of your multiple regression model from Module Six? Provide appropriate interpretation of this statistic. **This is step 5
OL5 Regression Results Dep. Variable: mpg R-squared: 0.835 Model : OLS Adj. R-squared: 0. 823 Method: Least Squares F-statistic: 68.39 Date: Fri, 10 Jun 2022 Prob (F-statistic) : 2.70e-11 Time: 02 :14:02 Log-Likelihood: -69.855 No. Observations: 30 AIC: 145.7 Of Residuals: 27 BIC: 149.9 Of Model: 2 Covariance Type: nonrobust coef std err t P> t [0. 025 0.975] Intercept 37 .5934 1. 644 22.860 0.000 34.219 40.968 wt -3.9334 0.642 -6.123 0.090 -5.252 -2. 615 hp -0. 0324 0.009 -3.515 0. 002 -0.051 -0.013 Omnibus : 4.567 Durbin-Watson: 2.063 Prob (Omnibus ) : 0.102 Jarque-Bera (JB): 3.422 Skew: 0. 821 Prob (JB) : 9.181 Kurtosis: 3. 201 Cond. No. 590. Warnings : [1] Standard Errors assume that the covariance matrix of the errors is correctly specified
- Define the null and alternative hypothesis in mathematical terms and in words.
- Report the level of significance.
- Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).
- Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?
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