percent of the variation is explained by the regression equation? What is the standard error of regression? What is the critical value of the F-statistic? What sample size is used in the print out? What is the variance of the slope coefficient of income? Conduct a global test of hypothesis to determine if any of the regression coefficients are not zero. SUMMARY OUTPUT
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Use the following regression equation and alpha =0.05 to fill in the missing values and answer the following questions.
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What percent of the variation is explained by the regression equation? |
What is the standard error of regression?
What is the critical value of the F-statistic?
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What |
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What is the variance of the slope coefficient of income? |
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Conduct a global test of hypothesis to determine if any of the regression coefficients are not zero. |
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SUMMARY OUTPUT |
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Regression Statistics |
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Multiple R |
0.910670783 |
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R Square |
0.829321275 |
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Adjusted R Square |
0.819839124 |
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Standard Error |
___________ |
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Observations |
___________ |
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ANOVA |
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df |
SS |
MS |
F |
Significance F |
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Regression |
1 |
6016.725851 |
_________ |
87.46129882 |
2.47832E-08 |
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Residual |
18 |
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Total |
______ |
7255 |
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Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
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Intercept |
13.91891892 |
4.916351942 |
2.831147787 |
0.011071519 |
3.590046767 |
24.24779107 |
3.590046767 |
24.24779107 |
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X(Weekly Income) |
0.076378621 |
0.008167024 |
___________ |
2.47832E-08 |
0.059220339 |
0.093536902 |
__________ |
__________ |
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