OLS Regression Results Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: Exam4 OLS R-squared: Adj. R-squared: F-statistic: Prob (F-statistic): Log-Likelihood: 50 0.077 0.058 4.010 0.0509 -172.76 349.5 353.3 Least Squares Fri, 16 Aug 2019 10:29:37 AIC: 48 1 BIC: nonrobust coef std err t P>[t| [0.025 0.975] Intercept Exam3 68.9586 0.1028 3.925 0.051 17.568 2.002 0.000 0.051 61.066 -0.000 76.851 0.206 Omnibus: Prob(Omnibus): Skew: Kurtosis: 5.557 0.062 0.659 Prob(JB): 3.621 Cond. No. Durbin-Watson: Jarque-Bera (JB): 1.644 4.422 0.110 271. Exam4 = 76.85 + 0.206 Exam3, model is statistically significant Exam4 = 76.85 + 0.206 Exam3, model is not statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is not statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is statistically significant
OLS Regression Results Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: Exam4 OLS R-squared: Adj. R-squared: F-statistic: Prob (F-statistic): Log-Likelihood: 50 0.077 0.058 4.010 0.0509 -172.76 349.5 353.3 Least Squares Fri, 16 Aug 2019 10:29:37 AIC: 48 1 BIC: nonrobust coef std err t P>[t| [0.025 0.975] Intercept Exam3 68.9586 0.1028 3.925 0.051 17.568 2.002 0.000 0.051 61.066 -0.000 76.851 0.206 Omnibus: Prob(Omnibus): Skew: Kurtosis: 5.557 0.062 0.659 Prob(JB): 3.621 Cond. No. Durbin-Watson: Jarque-Bera (JB): 1.644 4.422 0.110 271. Exam4 = 76.85 + 0.206 Exam3, model is statistically significant Exam4 = 76.85 + 0.206 Exam3, model is not statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is not statistically significant Exam4 = 68.9576 + 0.1028 Exam3, model is statistically significant
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
The ols() method in statsmodels is used to fit a simple linear regression model using “Exam4” as the response variable and “Exam3” as the predictor variable. The output is shown below. A text version is available. What is the correct regression equation based on this output? Is this model statistically significant at 10% level of significance (alpha = 0.10)? Select one.
(Hint: Review results of F-statistic)
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