Math3215 Assignments Spring 2008 Exercises are fromProbability and Statistical Inference, 7th edition, by Hogg and Tanis Due Thursady Jan. 17: section 1.2: 1, 2, 6, 7, 10, 11 section 1.3: 3, 11, 14, 15, 20 Due Thursady Jan. 24: section 1.4: 2, 4, 5, 11, 17 section 1.5: 5, 8, 11, 16, 19 Due Thursday Jan. 31: section 1.6: 2, 4, 6. section 2.1: 2, 3, 13. section 2.2: 2, 4, 5, 8. Due Thursday Feb. 7: section 2.3: 1, 2, 15. section 2.4: 3, 8, 10, 13. Due Thursday Feb. 14: section 2.5: 2, 3, 18. section 2.6: 5, 7, 8, 10. Test 1 on Thursday Feb 14, covering chepaters 1 and 2. Due Thursday Feb. 28: section 3.2: 7, 8, 9 14. section 3.3: 5, 8, 10. Due Thursday Mar. 6: section 3.4: 5, 8 section 3.5: 6, 12 Due Thursday Mar. 13: section 4.1: 1, 3, 8, 10. section 4.2: 8, 10 Due Thursday Mar. 27: section 4.3: 1, 13 section 4.4: 1, 2 Test 2 to cover Chapters 3 and 4. Tentatively scheduled on April 8. A forumula sheet is allowed. You may include theorems, as well as distributions and their pdfs or pmfs, moment-generating functions, expectations, and variances. No examples are allowed. Due Thursday. April 3: section 4.5: 2, 4, 10. section 4.6: 1, 2, 4, 7 Due Thursday. April 10: section 4.7: 2, 4 Due Tuesday. April 22: section 5.2: 7, 8, 9 section 5.3: 4, 14 section 5.4: 2, 6, 7 section 5.5: 8, 14 Note the unusual due date, requested by some of you. Final Assingment: section 5.6: 4, 6. section 6.2: 2, 6. section 6.4: 2, 6, 7 You need not turn in this assignment; but relavant material will be included in the final exam (which will also cover all material of this semester). Final is on Monday, April 28, from 8:00 to 10:50 in Skiles 246. You are allowed to have a fomula sheet (same requirement as for test 2). No calculator is allowed. Also please come to Thursday's class to claim your previous HWs and tests. Answers for problems in section 5.6: For problem 4, (a) 81, (b) 144, (c) 0.5987 For problem 6: (a) 0.6730, (b) 0.65x+7.945, (c) 4.7971, (d) 0.8604, (e) 0.7197) Answers for problems in section 6.2: For problem 2, the maximum likelihood estimator is 1/n times sum of (X_i-u)^2, where summation is over i=1 to i=n. Moreover, this estimator is unbiased. For problem 6, 33.4267; 5.0980 Answers for problems in section 6.4: For Problem 2: (a) [77.272, 92.728], (b) [79.12, 90.88], (c) [80.065,89.935], (d) [81.154, 88.846]. For problem 6: [8.15, 15.75]