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Stats Chapter 8


model an equation or formula that simplifies and represents reality
linear model a linear model is an equation of a line, need to know the variables along with their W's and their units
predicted value the value of yhat for a given x-value in the data, a predicted value is found by substituting the x-value in the regression equation
residuals the differences between data values and the corresponding values predicted by the regression model - or more generally values predicted by any model
least squares specifies the unique line that minimizes the variance of the residuals or equivalently the sum of the squared residuals
regression to the mean because the correlation is always less than 1.0 in magnitude each predicted yhat tends to be fewer standard deviations from its mean than its corresponding x was from its means which is called regression to the mean
regression line / line of best fit yhat - bnot +bonex
slope bone gives a value in "y-units per x-unit"
intercept bnot gives a starting value in y-units, found from bnot = ybar - bonexbar
Created by: 697421973