CJUS-K300 1nd Edition Lecture 21Outline of Last Lecture I. Bi-Variate Regression (Correlation) part 2Outline of Current Lecture II. Bi-Variate Regression (Correlation) contd. Current LectureBivariate linear regression analysis is the simplest linear regression procedure; simple leanera regression:- Explores the explanatory relationship for 2 variables - Examines only linear relationships- Simple linear regression focuses on explaining and predicting the dependent variables based on the information we know about he independent variable. The regression model examines the changes in the dependent variable as a function of changes or differences in values of the independent variable. This is what we would consider the interpretation of the answerDependent variable (DV) – variable that we are trying to explain or predict, it is usually very easily identifiable, we denote this as YIndependent variable (IV) – used to predict systematic changes in the dependent variable, we denote it as XThe regression aims to determine how and to what extent the dependent variable (Y) varies as afunction of changes in the independent variable (X)Best fitting straight line = least squares regression line: the extent to which the data points do not lie on the straight line indicate individual errors. Intercept (denoted as a): this is the point where the regression line crosses the Y axis Slope (denoted as b): this tells you how much a 1-unit increase in X affects the value of YThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a
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