Graduation Rates. Where we considered the regression analysis of graduation rate on the 25th percentile of SAT scores for entering students, the 75th percentile of SAT scores for entering students, the percentage of freshmen in the top 10% of their high school class, the student-to-faculty ratio, the percentage of applicants accepted, and the percentage of alumni giving to the college. Use the technology of your choice to do the following. a. Use the forward selection method to obtain a regression equation for the data. (Take tenter = 2.00, αenter = 0.05.) b. Use the backward elimination method to obtain a regression equation for the data. (Take tremove = 2.00, αremove = 0.05.) c. Use stepwise regression to obtain a regression equation for the data. (Take tenter = tremove = 2.00, αenter = αremove = 0.05.) d. Are the regression equations obtained in parts (a), (b), and (c) the same? e. For the regression equation selected by stepwise regression in part (c), obtain plots of residuals versus fitted values, residuals versus the included predictor variables, and a normal probability plot of the residuals. Perform a residual analysis to assess the appropriateness of the regression equation, constancy of the conditional standard deviations, and normality of the conditional distributions. Check for outliers and influential observations.
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.
Graduation Rates. Where we considered the
a. Use the forward selection method to obtain a regression equation for the data. (Take tenter = 2.00, αenter = 0.05.)
b. Use the backward elimination method to obtain a regression equation for the data. (Take tremove = 2.00, αremove = 0.05.)
c. Use stepwise regression to obtain a regression equation for the data. (Take tenter = tremove = 2.00, αenter = αremove = 0.05.)
d. Are the regression equations obtained in parts (a), (b), and (c) the same?
e. For the regression equation selected by stepwise regression in part (c), obtain plots of residuals versus fitted values, residuals versus the included predictor variables, and a normal probability plot of the residuals. Perform a residual analysis to assess the appropriateness of the regression equation, constancy of the conditional standard deviations, and normality of the conditional distributions. Check for outliers and influential observations.
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