Text: An Introduction to Mathematical Statistics and Its Applications Richard. J.
Larson ... butions, theory and applications of estimation and hypothesis testing.
MATH 427 Probability and Mathematical Statistics II Spring 2014 Instructor: Lihua Chen Office: Roop Hall 338 Office phone: 540-568-6533 Office hours MWF 11:10-12:10, W: 3:00-5:30 and by appointment Email:
[email protected] Text: An Introduction to Mathematical Statistics and Its Applications Richard J. Larson and Morris L. Marx, 5th edition. Course Website: http://educ.jmu.edu/∼chen3lx/math426 Goals of the Course: Limiting distributions, sampling theory and distributions, theory and applications of estimation and hypothesis testing Prerequisite: MATH 426 Evaluations: Quizzes: 15 percent Tests: 45 percent(Test 1: 2/14. Test 2: 3/21. Test 3: 4/18) Final Exam : 40 percent (5/ Monday 8-10:00) Grading scale: If you reach these point percentages, you are guaranteed at least the corresponding grade: A :≥ 92, B :≥ 82, C :≥ 72, D :≥ 62. The actual cutoff points may depend upon the performance of the class and the difficulty of the material. Grading policy: Unannounced quizzes will be given and quizzes and tests may NOT be made up. Up to two quizzes with lowest scores may be dropped. Note one purpose of this policy is to take care of missed work due to excused absences. If you miss more than you are allowed to drop due to excused absences, we will deal with that on an individual basis. Exams: The exams are closed notes and closed book. The formula sheets will be supplied by the instructor. You can bring a calculator to each exam, but you may not share a calculator with other students. The final exam is cumulative. Attendance: Attending classes is very important for learning the required material of this course. Students who missing 4 classes without excuses will result in a reduction of grade by one letter. Others: For locations of computers, see http://www.jmu.edu/computing/labs/locations/index.html The honor code of the university will be strictly enforced. The JMU Honor Code is available from www.jmu.edu/honor/code.shtml.
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Disruptive behavior will result in the reduction of the student’s final grade. No WP or WF grade will be issued for this course. Tentative Outline Chapter 5: Estimation: MLE and the method of moments, interval estimation, minimum variance estimators, sufficient statistics, consistency, Bayesian estimation Chapter 6: Hypothesis testing: decision rule, testing binomial proportion, Type I and Type II error, optimal test Chapter 7: Inference based on the normal distribution: inference about the population mean and the variance Chapter 8: Types of data: Classifying data Chapter 9: Two sample inferences: Testing equality of means, variances and proportions, confidence intervals Chapter 10: Goodness-of-fit tests: Multinomial distribution, goodness-of-fit tests, contigency tables This is a tentative schedule. The actual contents may be altered based on the time limitation and the needs of the students.
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