Midterm3/Stat4102, Fall 2022
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Midterm3/Stat4102, Fall 2022
Problem 1 (25 points). The following are the final grades of two sections of one statistics course. n1 =22 students in section 1 have a sample of an average of x¯1 = 84 with a standard deviation of s1 = 4. n2 =18 students in section 2 made a sample average of x¯2 = 80 with a standard deviation of s1 = 6. We now want to assess the difference of population means µ 1 − µ2 of grades between two sections.
(1) (15 points) Test for H0 : µ 1 − µ2 = 0 v.s. Ha : µ 1 − µ2
0 using a large sample Z-test and report the p value. Use a significance level of α = 0.025.
(2) (10 points) Compute a 95% confidence interval estimate for µ 1 − µ2 .
Problem 2 (25 points). Let X1 , X2 , ... , Xn be i.i.d. samples from the uniform(θ,θ + 1) distribution. To test H0 : θ = 0 versus H1 : θ > 0, we use the following test
reject H0 if X(1) ≥ k,
where k is a constant, X(1)=min{X1 , ...,Xn}.
(1) (10 points) Determine k so that the level of the test is α (the probability of Type I error).
(2) (15 points) Find the expression for the probability of Type II error of this test using k and θ . (Hint: Discuss different values of k .)
Problem 3 (25 points). Consider a simple linear model with normal error: Y = β0 + β1x + ε, ε ∼ N(0,σ2 )
Suppose that 10 pairs of observed values from this model given in the following table are obtained:
|
i xi yi |
||
|
1 2 3 4 5 6 7 8 9 10 |
1.9 1.1 5.5 3.4 -0.1 4.6 1.6 0.8 4.4 0.1 |
0.7 -0.2 3.7 2.0 0.0 -0.1 0.8 -1.0 3.4 -1.2 |
(1) (8 points) Calculate the values of the M.L.E.’s βˆ0 , βˆ1 , and
2 .
(2) (7 points) Determine an unbiased estimator of Var(βˆ0 ) and calculate its value.
(3) (10 points) Let θ = 2β0 +cβ1 , where c is a constant. Determine an unbiased estimator θˆ of θ . For what value of c will the M.S.E. of θˆ be smallest?
Problem 4 (25 points). Suppose n data points {(xi,yi), i = 1, . . . ,n} are obtained from the linear model:
Y = β0 + β1x + β2 e北 + ε,
where E[ε] = 0 and Var(ε) = σ 2 .
However, we do not know the above true model and fit the data points on the simple linear model:
E(Y) = β0 + β1x,
and obtain the least-squares estimator for β0 and β 1 :
对
(xi −
)2
βˆ0 =
− βˆ1
.
1. (15 points) Are these estimators unbiased? If yes, prove it. If no, find the bias.
2. (10 points) Derive the variance of βˆ0 and the covariance between βˆ1 and βˆ0 .
2022-12-16