The ols() method in statsmodels was used to fit a simple linear regression modelusing "Exam4" as the response variable and "Exam1" as the predictor variable. Theoutput is shown below. A text version is available. What is the correct regressionequation based on this output? Is this model statistically significant at 5% level ofsignificance (alpha= 0.05)? Select one.(Hint: Review results of F-statistic)======Dep. Variable:Model:Method:Date:Time:No. Observations:Df Residuals:Df Model:Covariance Type:InterceptExam1Omnibus:Prob (Omnibus):Skew:Kurtosis:0000coef57.76270.2266OLS Regression ResultsExam4OLSR-squared:Adj. R-squared:F-statistic:Prob (F-statistic):Least SquaresFri, 16 Aug 201910:23:535048std err10.0520.1211nonrobust3.8590.1450.4283.784Log-Likelihood:AIC:BIC:t5.7461.876P>|t|0.0000.067Durbin-Watson:Jarque-Bera (JB):Prob (JB):Cond. No.[0.02537.552-0.016Exam4 = 57.7627 +0.2266 Exam1, model is not statistically significantExam4 = 57.7627+0.2266 Exam1, model is statistically significantExam4 = 77.973 +0.469 Exam1, model is statistically significantExam4 = 77.973 +0.459 Exam1, model is not statistically significant0.0680.0493.5180.0668-173.00350.0353.80.975]77.9730.4691.7232.8090.245753.

Given that Y Intercept = 57.7627 Slope of exam1 = 0.2266

Answered: Variable and "Exam1" as the predictor…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

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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-statistics) Exam4 = 68.9576 + 0.1028 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 = 76.85 + 0.206 Exam3, model is statistically significant
In the table below ratings data on x= the quality of the speed of execution and y= overall satisfaction with electronic trades provided the estimated regression equation y^= -0.9082 + 1.2404x (AAII website). Brokerage Speed Satisfaction Scottrade, Inc. 3.1 2.8 Charles Schwab 3.6 3.4 Fidelity Brokerage Services 2.9 2.6 TD Ameritrade 3.1 3.0 E*Trade Financial 3.6 3.9 Vanguard Brokerage Services 3.5 3.8 USAA Brokerage Services 3.3 3.7 Thinkorswim 3.8 3.8 Wells Fargo Investments 3.5 3.2 Interactive Brokers 3.1 2.6 Zecco.com 3.9 3.6 -select your answer choices- P-value is less than 0.01 between 0.01 and 0.02 between 0.02 and 0.05 between 0.05 and 0.10 between 0.10 and 0.20 between 0.20 and 0.40 greater than 0.40 Conclusion We (can not, can) reject H0: B1=0, we conclude that speed of execution and overall satisfaction (are, are not) related. Thank you!
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when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
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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) Dep. Variable: Model: Method: Date: Time: No. Observations: Df Residuals: Df Model: Covariance Type: Intercept Exam3 coef 68.9586 0.1028 Omnibus: Prob (Omnibus): Skew: Kurtosis: OLS Regression Results Exam4 OLS R-squared: Adj. R-squared: F-statistic: Prob (F-statistic): Least Squares Fri, 16 Aug 2019 10:29:37 50 48 1 nonrobust std err 3.925 0.051 Log-Likelihood: 5.557 0.062 0.659 3.621 AIC: BIC: t 17.568 2.002 P> |t| 0.000 0.051 Durbin-Watson: Jarque-Bera (JB): Prob (JB): Cond. No. [0.025 61.066 -0.000 0.077 0.058 4.010 0.0509 -172.76 349.5 353.3 0.975] 76.851 0.206 1.644 4.422…

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