Lecture27

Lecture27 - STAT 350 Lecture 27 Simple Linear Regression...

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Unformatted text preview: STAT 350 Lecture 27 Simple Linear Regression Final Exam Date: May 3, 2011 (Tuesday) Time: 7 PM 9 PM Where: EE 270 Crib sheet: three pages, 1-sided, handwriOen Example 11.2 on page 494 y = mortar dry density (lb/T3) x = mortar air content (%) Example 11.2 11.4 a) Calculate the least square esWmate of the slope and the intercept. b) Use the equaWon of the fiOed line to esWmate the mean dry density for all specimens whose air content is 15% c) Suppose the observed value of mortar dry density is 115.1 when x=15.00(%), calculate the residual. d) EsWmate e) What proporWon of the observed variaWon in y can be aOributed to the simple linear regression relaWonship between x and y? Example e) Conduct a model uWlity test using two different methods (H0: =0; H0: =0) f) Construct 95% confidence Interval for g) Conduct Hypothesis TesWng on H0: =-1 vs Ha:-1 i) Interpret the slope b and R2 Example 11.2 on page 494 Step 1 -- Find the slope b: Example 11.2 on page 494 Step 2 -- Find the intercept a: The equaWon for the es#mated regression line is Example 11.4 (same data as 11.2) Calculate 95% CI for b (t crit)sb Example 11.4 (same data as 11.2) Calculate 95% CI for b (t crit)sb Example 11.4 (same data as 11.2) Calculate 95% CI for b (t crit)sb 95% CI: -0.92 (2.16)*(0.146) -0.920.315 (-1.233, -0.603) ...
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