STAT 301 Study Guide - Final Guide: Linear Regression, Null Hypothesis, Dependent And Independent Variables
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2 b1: hypothesis test: reject the null hypothesis if our p-value is less than 0. 05. If we do: "the observed slope is large enough that it would be unlikely to occur by chance, if the population slope were 0. " Y-hat: an estimate for the populaton mean value of the response variable at x = x* Simple: linear regression with only one predictor variable. Multiple regression model: yi = the response (or dependent) variable for observation i i = the index of the data. it accounts for individual observations in a dataset of size n. = normally distributed random variation around the line. As with simple regression, o^2e quantifies the magnitude of the variability. In multiple regression, we have more than one predictor variable, so r2 is interpreted as the proportion of variation in the response variable that is explained by (or attributed to) the predictor variables.
