The output below estimates the following regressionTreat; = Bo + B1 · Female; + e;Based on the results, which statement is most accurate.• reg treat st femalelSourceSdfMSNumber of obs619%3DF(1, 617)0.01%3DModel.0030063511.003006351Prob > F0.9128R-squaredAdj R-squaredResidual154.71428617.2507524790.0000-0.0016Total154.717286618.250351595Root MSE.50075%3DtreatCoefficientStd. err.P>|t|(95% conf. interval]st femalel.0051549.04707890.110.913-.0872993.0976092_cons.5033557.041023212.270.000.4227937.5839177O In the treatment group, the fraction female is slightly lower than in the control groupIn the treatment group, the fraction female is slightly higher than in the control groupIn the treatment group, the fraction female is much lower than in the control groupO In the treatment group, the fraction female is much higher than in the control group

As the regression coefficient corresponding to female is 0.0051549 which much lower. Also from P…

Answered: The output below estimates the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Interpret the belavg coefficient. thank you
The attached images show linear regression analysis to evaluate the ability of independent variables full and part-time FTEs, number of Medicare certified beds and urban vs. rural setting to predict dependent variable, occupancy rate. How do you interpret these results, what are the basic assumptions for regression analysis?
A Bivariate Regression was conducted to evaluate the predictive relationship between total years of schooling and annual income. The results of the regression model were F(1,88) = 4.1, p < .05. What can be concluded about these results? Group of answer choices total years of schooling is a significant predictor of annual income. total years of schooling is not a significant predictor of annual income.
A student used multiple regression analysis to study how family spending (y) is influenced by income (x) family size (x2), and addition to savings(x3). The variables y, x1, and x3. The variables y, x1, and x3 are measured in thousands of dollars . The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficient Standard Error Intercept 0.0136 X1 0.7992 0.074 X2 0.2280 0.190 X3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significant. Carry out a test to see if X3 and y are significantly related. Use a 5% level of significance
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A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is…
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