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l2 12 multiple regression and issues in regression analysis

This class was created by Brainscape user Steven Popovic. Visit their profile to learn more about the creator.

By: Steven Popovic
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Decks in this class (15)

a formulate a multiple regression equation to describe the relation between a dependent variable and several independent variables, and determine the statistical significance of each independent variable;
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b interpret estimated regression coefficients and their p-values;
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c formulate a null and an alternative hypothesis about the population value of a regression coefficient, calculate the value of the test statistic, and determine whether to reject the null hypothesis at a given level of significance;
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d interpret the results of hypothesis tests of regression coefficients;
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e calculate and interpret 1) a confidence interval for the population value of a regression coefficient and 2) a predicted value for the dependent variable, given an estimated regression model and assumed values for the independent variables;
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f explain the assumptions of a multiple regression model;
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g calculate and interpret the F-statistic, and describe how it is used in regression analysis;
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h distinguish between and interpret the R2 and adjusted R2 in multiple regression;
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i evaluate how well a regression model explains the dependent variable by analyzing the output of the regression equation and an ANOVA table;
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j formulate a multiple regression equation by using dummy variables to represent qualitative factors, and interpret the coefficients and regression results;
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k explain the types of heteroskedasticity and how heteroskedasticity and serial correlation affect statistical inference;
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l describe multicollinearity, and explain its causes and effects in regression analysis;
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m describe how model misspecification affects the results of a regression analysis, and describe how to avoid common forms of misspecification;
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n describe models with qualitative dependent variables;
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o evaluate and interpret a multiple regression model and its results.
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l2 12 multiple regression and issues in regression analysis

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