Chapter 5: Correlation and Regression

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strength of a linear relationship; estimating a linear relationship coefficients
Erin Vales
Flashcards by Erin Vales, updated more than 1 year ago
Erin Vales
Created by Erin Vales over 5 years ago
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Question Answer
Correlation coefficient (r) a numerical measure of strength and direction of the linear relationship between two variables
Standard deviation formulas
Properties of Linear Correlation Coefficient
Rule of Thumb For Interpreting r
Regression prediction of the average response for all subjects with a given value of the explanatory value
Simple Linear Regression Model
Least Squares Regression Line (Best fitting line) the line that minimizes the sum of the squared errors (or residuals) the line that minimizes the square of the vertical distance between the observed values of y and the predicted values
Residuals the vertical distances between the observed and predicted values
Interpreting Intercept the value of the response when the value of the explanatory is 0
Interpreting Slope the value of the response when the value of the explanatory increases by 1
Extrapolation predicting Y values for X values outside the range of the original values
Outlier an observation that falls within the range of the other X values but which lies far above or below the regression line and produces large residual
Influential Observation observations that are separated in the X (horizontal) direction from the other observation have unusually large influence on the position of the regression line
Coefficient of Determination r^2 indicates the proportion of observed y variation that can be explained by the linear regression model r^2 = (1 - SSResid)/SSTotal
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