Spring 2009

STAT 7030 – Mathematical Statistics II

 

Date

Section

Assignment

Jan 13

Brief review of order statistics: maximum and minimum order statistics.

Brief review of estimators. MLE, MOM estimators. Minimum variance estimators. Sufficient estimators.

Read 3.10 for order statistics.

See class notes on Efficiency and the Cramer-Rao lower bound, and the class notes on Sufficiency.

Read 5.4, 5.5, 5.6. Read Case study 5.4.1: very interesting.

Hw#1 (due Jan 20): 5.4.10, 5.4.21, 5.5.3, 5.5.4, 5.5.6, 5.6.3, 5.6.7.

Jan 20

Bayesian estimation (5.8)

Read section 5.8 text

Read class notes on Bayesian estimation

Read the articles

A Bayesian Look at Classical Estimation: The Exponential Distribution (by Abdulaziz Elfessi and David M. Reineke) and

Bayes Estimators for the Continuous Uniform Distribution by A. Rossman, T Short and M. Parks

Tentative Hw#2 (due Jan 27): 5.8.1, 5.8.3, 5.8.5, 5.8.7.

Jan 27

Hypothesis Testing: testing for means when the population is normal; tests for proportions.

Read 6.1-6.3 Read on your own section 6.3 and we will discuss some examples in class.

Hw added to Hw#2 (due Feb 3): 6.2.3, 6.2.5, 6.3.3.

Think about 6.3.4, 6.3.5, 6.3.7.

Feb 3

Type I and type II errors. Power of the test.

The Generalized Likelihood Ratio test. (6.4, 6.5)

Read sections 6.3-6.5 text. Read 9.1-9.4 class handout.

Hw#3 (due Feb. 17): 6.4.5, 6.4.7, 6.4.13 (see example 6.4.2), 6.5.1, 32 (from Rice handout)

Suggested problems: 6.4.10, 6.4.18, 6.4.19, 6.5.3, 6.5.4, 6.5.5,

Feb 10

Distributions derived from the normal distribution: Chi-square, F and Student distributions.

Read 7.1-7.4.

Additional problems to Hw#3: 7.3.8, 7.3.9, 7.3.11, 7.3.12.

Notice that I did not assign problems from 7.4 but I believe most of the facts are known by you.

Feb 17

Generating random data from unusual distributions (see class notes). Robustness of the t-test.

Read: 7.4-7.5 and notes (see left).

Read from the article How large does n have to be for Z and t intervals? the first three sections and be prepared to discuss it in class. 

Hw#4 (due Feb. 24): 7.4.24 (see HW4 file for what to do in this problem) 7.5.9, 7.5.14, 7.5.16.

I will add to all the questions in section 7.5 that you should ask yourselves (and also check!) whether the data is coming from a normal distribution so that you can use the theory presented in sections 7.4 and 7.5.

Feb 24

Discuss the article: How large does n have to be in the Z and t test?

Hw#5 (due March 3): see file

I noticed that I had the first exam scheduled a while ago and since the Spring break is approaching I will try to bring it to you next time to have it over the break.

March 3

Unfortunately, no class due to “Little Houdini”

The Exam is now posted in Vista in the Exams folder

March 10

 

No class Spring break

March 17

Tests for two means, two proportions and two variances. (Chapter 9). Deriving the F-test as a Generalized Likelihood Ratio Test.

Exam 1 due

Read Chapter 9.

Hw#6 (due March 24): 9.2.4, 9.2.11, 9.2.13 (Note: assume that the sample variance is an unbiased estimator for the variance), 9.3.4, 9.4.4, 9.5.6.

Note: On problems using data plot your data and check the conditions for using the tests presented in this chapter.

March 24

The Multinomial Distribution and the Goodness of Fit tests.

Read 10.1 – 10.4.

Hw#7 (due March 31): 10.2.2, 10.2.7, 10.2.9, 10.3.2, 10.3.3 (this question is very interesting), see problem in file, 10.4.3, 10.4.5. 

March 31

Chi-square test for contingency tables. Tests for matched pairs (McNemar test). Odds ratio test.

Read 10.5-10.6. Read class handout: chapter 13.

Hw #8 (due April 7): 10.5.4 (see comments on retrospect studies on handout in regard to odds ratio), 10.5.6 (Can this be seen as a case of McNemar test for K x K tables? See McNemar test for marginal homogeneity on Resources page),  10.5.8 (be careful, the “Enrolled” category is out of the  “Admitted”).

From the class handout: Pb 8, 12 (this looks very interesting) 14, 18.

April 7

Covariance and correlation. The Bivariate Normal distribution. The Linear model.

Read 11.4, 11.5

Hw #9 (due April 14): 11.4.1, 11.4.2, 11.4.10 (I hope it does not turn out to be too complicated. The problem is quite intriguing), 11.4.11, 11.5.1 more to be posted

April 14

The Linear Model.

Read 11.2, 11.3.

Hw#10 (due April 21): 11.2.4, 11.2.8, 11.2.16, 11.2.19 (rather than recalling Question 11.2.14 use pb. 11.2.16 with a*=0), 11.2.21, 11.3.20, 11.3.21.

In all problems involving data please perform the regression analysis yourselves and do not use the summary provided by the text.

Do not forget to plot the residuals as well to see whether the model is a good fit.

April 21

 

 

April 28