Back to 14.2 Problems on Conditional Expectation, Regression

14.2 Exercise 11

Avg difficulty 2.5

(See Exercise 22 from " Problems On Random Vectors and Joint Distributions", Exercise 32 from "Problems on Mathematical Expectation", and Exercise 30 from "Problems on Variance, Covariance, Linear Regression"). fXY(t,u)=I[0,1](t)38(t2+2u)+I(1,2](t)914t2u2f_{X Y} \left(t , u\right) = I_{\left[0 , 1\right]} \left(t\right) \frac{3}{8} \left(t^{2} + 2 u\right) + I_{\left(1 , 2\right]} \left(t\right) \frac{9}{14} t^{2} u^{2},

for 0≤u≤10 \leq u \leq 1.

The regression line of Y on X is u=0.0817t+0.5989u = 0 . 0817 t + 0 . 5989.

f X ( t ) = I [ 0 , 1 ] ( t ) 3 8 ( t 2 + 1 ) + I ( 1 , 2 ] ( t ) 3 14 t 2 f_{X} \left(t\right) = I_{\left[0 , 1\right]} \left(t\right) \frac{3}{8} \left(t^{2} + 1\right) + I_{\left(1 , 2\right]} \left(t\right) \frac{3}{14} t^{2}

Pfeiffer, Applied Probability, 14.2 Problems on Conditional Expectation, Regression, exercise 11

AI Tutor

Adapted from Applied Probability © 2009 Paul E. Pfeiffer. Licensed under CC BY 3.0. Source: Applied Probability. Imported at revision d7a0420.