QBAchapt 1 and 2 study guide
QBAchapt 1 and 2 study guide 2305
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This 2 page Study Guide was uploaded by Nikita Hendricks on Tuesday September 20, 2016. The Study Guide belongs to 2305 at Baylor University taught by Prof. Turner in Fall 2016. Since its upload, it has received 5 views. For similar materials see QBA in Business at Baylor University.
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Date Created: 09/20/16
QBA 2 STUDY GUIDE Least squares point estimates Values if b0, b1, b2... that minimize SSE Mean Square Error (s2) The difference between the estimator and what is estimated Standard Error (se) Measures the accuracy with which sample represents a population the smaller the better Explained variation (SSR) A quantity that measures the amount of the total variation in the observed values of y that is explained by the predictor variable X Total variation (SST) Measures the total amount of variation exhibited by the observed values of the dependant variable y Unexplained variation (SSE) Measures the amount of variation in the values of y that is not explained by the predictor variable Multiple coefficient of determination (R2) SSR/SST The proportion of variability in the dependant variable Y that is explained by the regression model (values range from 0 to 1) Adjusted multiple coefficient of determination (Rline^2) Takes into account the number of independent variables and their contribution Leverage value (distance value) Lies away from the rest of the data on the x-y plane but lies close to the regression line If large have substantial leverage in determining least squares prediction estimation Dummy variable (indicator variable) Model qualitative variables either take onto values a value of zero or one Use these variables to describe the effects of different levels of the qualitative independent variable in a regression model Interaction The relationship between the mean value of the dependent variable y and an independent variable X is dependent on the value of another independent variable Multicollinearity Exists among the independent variable's in a regression situation if these independent variables are related to or dependent upon one another Correlation matrix Dependents between multiple variables of the same time Variance inflation factor Quantifies the severity of Multicollinearity in an ordinary least squares regression analysis Stepwise regression Meet certain criteria in order to make it into the model
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