ADMS 2320 Lecture Notes - Lecture 11: Dependent And Independent Variables

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Simple because there are only two variables, x or y. Linear is either positive, negative, or no relationship. Regression is analyzing the variability and relationship between x and y. Used to predict one value of y, given a certain value of x. Population least squares regression line; 0 is the y-intercept, 1 is the slope of a line. Sum of squared difference is the error; if there is less error, the points are closer to the line. Goal is to get a line that is closest to all the points. The least squares regression line population and sample equation differences: The error variable not in the equation for sample because we have a separate formula. Just y, whereas the other one is y-hat tells the person that it is an estimate and a sample. The beta are uppercase for the population and lowercase for sample.

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