Instructor: Vahan Huroyan
Email: vahanhuroyan (at) math (dot) arizona (dot) edu
Section Time: T TH 8:00AM - 9:15PM
Section Room: ILC Room 141 (M Pacheco Integrated Learning Center: Room 141)
Course Syllabus: [here]
Textbook: Mathematical Statistics with Applications, by Wackerly, Mendenhall and Scheaffer, 7th Edition (2008).
Announcements:
Lecture 1, Aug. 25: Review of Probabilities (Section 7.1)
Lecture 2, Aug. 27: Random Samples. Sampling from a Normal Population (Sections 7.1, 7.2)
Lecture 3, Sep. 1: Sampling Distributions Related to the Normal Distribution (Section 7.2)
Lecture 4, Sep. 3: The Central Limit Theorem. The Normal Approximation to the Binomial Distribution (Sections 7.3, 7.4, 7.5)
Lecture 5, Sep. 8: Introduction to Estimation. The Bias and Mean Square Error of Point Estimators. (Sections 8.1, 8.2)
Lecture 6, Sep. 10: Some Common Unbiased Point Estimators (Section 8.3)
Lecture 7, Sep. 15: The Goodness of a Point Estimator (Section 8.4)
Lecture 8, Sep. 17: Confidence Intervals (Section 8.5)
Lecture 9, Sep. 22: Large Sample Confidence Intervals (Section 8.6)
Lecture 10, Sep. 24: Selecting the Sample Size. Small Sample Confidence Intervals (Sections 8.7, 8.8)
Lecture 11, Sep. 29: Small Sample Confidence Intervals, Confidence Intervals for the Variance (Sections 8.8, 8.9)
Lecture 12, Oct. 1: Confidence Intervals for the Variance, Review (Section 8.9)
Lecture 13, Oct. 6: Review
Lecture 14, Oct. 8: Midterm 1
Lecture 15, Oct. 13: Relative Efficiency (Sections 9.1, 9.2)
Lecture 16, Oct. 15: Consistency (Section 9.3)
Lecture 17, Oct. 20: Sufficiency (Section 9.4)
Lecture 18, Oct. 22: Sufficiency, Mininum variance unbiased estimators (MVUE) (Sections 9.4, 9.5)
Lecture 19, Oct. 27: Method of Moments, Maximum Likelihood Estimation (MLE) (Sections 9.6, 9.7)
Lecture 20, Oct. 29: Maximum Likelihood Estimation (MLE) (Section 9.7)
Lecture 21, Nov. 3: Mininum variance unbiased estimators (MVUE), Rao-Blackwell theorem, Hypothesis testing (Sections 9.5, 10.1)
Lecture 22, Nov. 5: Elements of a Statistical Test, Common Large Sample Tests (Sections 10.2, 10.3)
Lecture 23, Nov. 10: Common Large Sample Tests (Section 10.3)
Lecture 24, Nov. 12: Calculating probability of type II error and finding the sample size for Z tests (Section 10.4)
Lecture 25, Nov. 17: Review
Lecture 26, Nov. 19: Midterm 2
Lecture 27, Nov. 24: Relationships between Hypothesis-Testing Procedures and Confidence Intervals. Another Way to Report the Results of a Statistical Test: Attained Significance Levels, or p-Values (Sections 10.5, 10.6)
Lecture 28, Dec. 1: Small-Sample Hypothesis Testing (Section 10.8)
Lecture 29, Dec. 3: Testing Hypotheses Concerning Variances (Section 10.9)
Lecture 30, Dec. 8: Power of Tests and the Neyman–Pearson Lemma (Section 10.10)
Homework:
HW 1: posted 09/10, due 09/17 ---- Homework 1
HW 2: posted 09/27, due 10/6 ---- Homework 2
HW 3: posted 11/02, due 11/12 ---- Homework 3
HW 4: posted 11/14, due 11/24 ---- Homework 4
HW 5: ---- Homework 5