* Denotes problems scheduled to be done in class

Section 4.9
4.82, 4.83*, 4.85

Chapter 7
For an exponential distribution, use the mgf to find the fourth moment and the fourth central moment
For a gamma distribution,  use the mgf to find the mean and variance

7.1 (p=0.8664), 7.2 (n=90), 7.5 (n=18), 7.7 (p=0.10), 7.8, 7.9 (a=0.656, b=2.42), 7.11, 7.12*, 7.13, 7.14*
7.19 (p=0.9544), 7.20 (n=151), 7.27 (p=0.0002), 7.29 (p=0.0062)
7.34 (p=0.0668), 7.35 (p=0.8980 with c.c.), 7.36 (p=0.9504, p=0.0708, Z=1.37), 7.42, 7.43 (p=0.8414)
7.51*, 7.52 (c=183.07), 7.53*, 7.56*, 7.57*

Chapter 8
8.1*, 8.2*, 8.3*, 8.4*, 8.5 (Y_bar - 1), 8.6*, 8.7 (theta_hat_sub3 - 9*theta_hat_sub2 + 54), 8.8 (a: 1/2; b: Y_bar - 1/2; c: 1/(12n) + 1/4), 8.9 (a: (n-1)pq; b: n^2/(n-1)*(Y/n)*(1 - Y/n)), 8.10*, 8.11*, 8.12*, 8.13 (a: (1 - 2p)/(n + 2); b: p(1 - p)/n and (np(1 - p) + (1 - 2p)^2)/(n + 2)^2; c: assume n = 100, 0.1456 < p < 0.8544), 8.14*, 8.15*, 8.16*
8.17 (4.86), 8.19 (a: 4.86, b: 1.7, c: 0.08), 8.20 (0.03), 8.24 (0.121), 8.28 (a: 98550 +- 20316, b: 197.1 +- 40.63), 8.34*
8.35*, 8.36 a: =-1.96, b: +1.645, c: -1.645), 8.39*
8.40 (0.536 +- 0.052), 8.42 5.4 +- 0.27), 8.45 (26.2 +- 10.477), 8.48 (0.06 +- 0.046), 8.54 (see page 238 for the covariance formula, -0.10 +- 0.04), 8.55 (0.22 +- 0.34)
8.56 (a: 139, b: 385), 8.57 (100), 8.58 (a: 0.0316, b: 2537), 8.61 (136)
8.66 (26.6 +- 3.37), 8.71 (-1 +- 4.72), 8.77*
8.79*, 8.84 (294.55)
8.107*, 8.108 (0.0854, 1.3876)

Chapter 9
9.53 ((2*avg-1)/(1-avg), 9.54 (avg), 9.60 (1/Y), 9.61 (2*avg/3), 9.62 (avg/(3-avg)
9.64 (avg), 9.65 (avg^2), 9.66 (sum(y_i^r, i = 1..n)/n), 9.68 (avg/2), 9.69a (avg/alpha), 9.72*, 9.76*, 9.77*, 9.78*

9.5 (in class we showed that the Risk( S^2) = 2*sigma^4/(n-1) and show that the second risk is 2*sigma^4), 9.8*
Read the ones in this section 9.10 (no), 9.11, 9.12*, 9.16*
Read the ones in this section 9.25*, 9.26, 9.32, 9.37*
Read the ones in this section 9.42, 9.46, 9.50*

Chapter 11
11.1 y_hat = 1.5 - 0.6x), 11.6 ( beta_1_hat = sum(xi*yi)/sum(xi*xi) )
11.11*, 11.13a (SSE/6 = 3.0476)
11.19b (-0.6 +- 0.367)
11.31*, 11.34 (1) 1.5 +- 0.38 (2) 2.7 +- 0.67 (3) 0.3 +- 0.67
Redo 11.34 for confidence intervals for Y|X=0, Y|X=-2, and Y|X=2

Chapter 10
Read 10.2, 10.3
Read 10.5, 10.9, 10.13, 10.15
Read 10.30
Read 10.38
Read 10.50, 10.55
Section 10.10 The Neyman-Pearson Lemma
10.75a (Reject when X_BAR > c)
10.78 (sum(y_i - mu)^2/sigma_0^2 > c)
10.79a (sum(y_i) > c)
10.80a (sum(y_i^m) > c)
10.81a (sum(y_i) > c)
10.82 (sum(x_i)*log(4) + sum(y_j)*log(2/3) < c)
10.83a (sum(y_i) < c)
1084a(iii) (sum(y_i) > c)
Read 10.91*