A positive residual indicates that the model is under-predicting. The residual would be 62.1 – 64.8 = -2.7 in.Ī negative residual indicates that the model is over-predicting. is 64.8 in.Ĭhest girth = 13.2 + 0.43(120) = 64.8 in.īut a measured bear chest girth (observed value) for a bear that weighed 120 lb. The predicted chest girth of a bear that weighed 120 lb. The criterion to determine the line that best describes the relation between two variables is based on the residuals.įor example, if you wanted to predict the chest girth of a black bear given its weight, you could use the following model. The difference between the observed data value and the predicted value (the value on the straight line) is the error or residual. The regression line does not go through every point instead it balances the difference between all data points and the straight-line model. This simple model is the line of best fit for our sample data. Where is the slope and b 0 = ŷ – b 1 x̄ is the y-intercept of the regression line.Īn alternate computational equation for slope is: The equation is given by ŷ = b 0 + b 1 x The Least-Squares Regression Line (shortcut equations) What would be the average stream flow if it rained 0.45 inches that day?
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |