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Unformatted text preview: STA 3024: Regression Douglas Whitaker Department of Statistics 12 March 2012 Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 1 / 45 Upcoming Statistics Courses Summer STA 4321  Introduction to Probability (Mathematical Statistics I) MTWRF 2nd Period (Summer A) STA 4322  Introduction to Statistics Theory (Mathematical Statistics II) MTWRF 2nd Period (Summer B) Fall STA 4321  Introduction to Probability (Mathematical Statistics I) MWF 1st or 2nd Period STA 4210  Regression Analysis MWF 2nd Period Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 2 / 45 Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 3 / 45 Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 4 / 45 Before Spring Break... The last thing we did was this: X Y 4 5 5 9 9 10 12 13 14 17 y i = α + βx i + e i ˆ y i = 2 . 123 + 0 . 986 x i Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 5 / 45 Scatterplot Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 6 / 45 Scatterplot with Regression Line Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 7 / 45 Computer Output (Note: This output was shown in class but a bit later on. We used it to get the 0.1887 for the SE for ˆ β when making a confidence interval for β .) Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 2.1176 1.8135 1.168 0.3273 x 0.9866 0.1887 5.230 0.0136 * Signif. codes: 0 ’***’ 0.001 ’**’ 0.01 ’*’ 0.05 ’.’ 0.1 Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 8 / 45 Regression: Interpretations But now that we have these numbers, what do we do? We tested to see if the model was significant (F and t tests). We could make confidence intervals for β in the usual way. But how do we actually interpret these numbers? Douglas Whitaker (Department of Statistics) STA 3024: Regression 12 March 2012 9 / 45 Interpreting the slope The way we interpret the slope ( ˆ β ) is: for a one unit increase in x we expect that the average value of y will increase by ˆ β ....
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This note was uploaded on 03/20/2012 for the course STA 3024 taught by Professor Ta during the Spring '08 term at University of Florida.
 Spring '08
 TA
 Statistics, Probability

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