MATH 4343: Mathematical Statistics II   Spring 2014

Instructor:    Dr. Leif Ellingson
E-Mail:    leif.ellingson_at_ttu.edu    Office:    Math 215
Office Hours:    2:00 — 3:30 PM TuTh
Class Meetings:    2:00 — 2:50 MWF in Math 012
Final Exam:    Tuesday, May 13   4:30 — 7:00 PM

An electronic copy of the syllabus can be found here.

Textbook:    Mathematical Statistics with Applications, 7th Edition, by Wackerly, Mendenhall, and Scheaffer

Additional Resources:

Z-Table (Normal Distribution cdf)

Sampling Distribution slides

Confidence Interval Interpretation image

Consistency Slides

T-Table (Critical Values for the t-Distribution)


Virtual Lectures:   The following are videos containing slides with narration that consist of additional information beyond what is presented in class.
  1. Multivariate generalizations of independence (4:35): html5, swf
  2. Chapter 7: Transition to Statistics (6:45): html5
  3. Chapter 7: Sampling Distributions (10:08): html5
  4. Chapter 7: Sampling Distributions of the Sample Mean and Sample Variance from a Normal Population (9:11): html5
  5. Chapter 7: The Central Limit Theorem (8:43): html5
  6. Chapter 7: Normal Approximation of Binomial Random Variables (11:15): html5
  7. Chapter 8: Some Common Unbiased Point Estimators (10.54): html5


Practice Problems:   The following is a list of suggested practice problems from the textbook to help you master the material.  While only some of the problems will be included in the assigned homework, completing all of these problems is to your benefit. The list will be updated throughout the semester.


Exam 1 Material

Chapter 5:   Independent Random Variables
                   45, 46, 48, 49, 50, 51, 52, 55, 62

                   Expected Value of a Function of Random Variables
                   72, 76, 77, 80

                   Covariance
                   89, 91, 92, 94, 97, 98

                   Expected Value of a Linear Function of Random Variables
                   102, 103, 105, 106, 108, 110

                   Multinomial Distribution
                   120, 121, 123, 124

                   Conditional Expectation
                   133, 140, 141, {149c, 150}

Chapter 6:   Method of Distribution Functions
                   1, 2, 3, 4, 5, 20

                   Minimum and Maximum
                   72, 73, 80, 81

                   Transformation Method
                   23, 24, 28, 32, 33

                   Method of MGFs
                   37, 39



Exam 2 Material

Chapter 7:   Sampling Distribution of the Sample Mean
                   9, 10, 11, 12, 15

                   The Central Limit Theorem
                   43, 44, 45, 52, 58

                   Binomial Approximation
                   71, 72, 74, 76, 84

Chapter 8:   Point Estimators
                   1, 2, 3, 5, 7, 8, 10, 12, 17

Chapter 9:  Consistency
                   15, 16, 17, 18, 19, 20

                   Method of Moments
                   70, 71, 74, 75, 77, 78

                   Maximum Likelihood Estimation
                   80, 81, 82(b), 83, 88, 96, 97



Exam 3 Material

Chapter 8:  General Confidence Intervals
                   40, 43, 44, 45

                   Large-Sample Confidence Intervals
                   56 (Use 99%), 58, 59, 60, 62, 65

                   Minimum Sample Size Calculation
                   70, 71, 72

                   Small Sample Confidence Intervals
                   80, 81, 82, 83, 88, 89, 90, 91

Chapter 10: Large-Sample Tests
                   17, 18, 19, 21, 23, 24, 27