|Time and Place:||MWF 10:20am-11:10am, Blocker 163 (Statistics and mathematics majors only).|
|Instructor:||Daren Cline, Department of Statistics.|
|Office:||Blocker 459D, 845-1443. Note new location and phone number.|
|Hours:||MW 8:30am-10:00am or by appointment. Please check my schedule.|
|Grader:||Beverly Gaucher, Blocker 415A, 845-9774.
hours: TBA (questions about grading only).
|Text:||G. Casella and R.L. Berger, Statistical Inference, 2nd ed. Duxbury.|
(On reserve in Evans Library)
|E.J. Dudewicz and S.N. Mishra, Modern Mathematical Statistics, Wiley.
J.E. Freund, John E. Freund's Mathematical Statistics, 6th ed., Prentice-Hall.
R.V. Hogg and A.T. Craig, Introduction to Mathematical Statistics, 4th ed., Macmillan.
A.M. Mood, F.A. Graybill and D.C. Boes, Introduction to the Theory of Statistics, 3rd ed., McGraw-Hill.
V.K. Rohatgi, An Introduction to Probability Theory and Mathematical Statistics, 2nd ed., Wiley.
|Prerequisite:||Three semesters of calculus, including
|Homework:||Homework will be assigned (on the course web page)
and collected regularly. Homework is worth 20% of the total term score.
Please see the homework policy below.
|Exams:||Two midterm exams worth 22.5% each and a final exam worth 35%.
Please see the exam policy below.
|Exam Dates:||Exam I: TBA.
Exam II: TBA.
Final Exam: Tuesday, 14 December, 8:00am - 10:00am.
|Grading Scale:||A: 85% - 100%.
B: 70% - 84%.
C: 60% - 69%.
|Homework Policy:||Your homework solutions must be your own work, not from outside sources, consistent
with the university rules on
I expect you to follow this policy scrupulously. Your performance on the exams
is much more likely to be better.
You may use:
|Exam Policy:||Each exam will be comprehensive, cumulative and closed book. Please bring your
own paper. I ask that separate problems be on separate sheets. No resources
other than pen and paper are acceptable.
I will not expect you to quote theorems and results explicitly but I do expect you to demonstrate that you can make use of them. Specifically, you will need to:
|Missed Work and Incompletes:||This is based on university policy.
|1. The Probability Measure|
|1-2. Sample Spaces and s-algebras||1.1|
|1-3. Axioms and Properties||1.2|
|1-4. Counting Rules||1.2|
|1-5. Conditional Probability and Bayes' Theorem||1.3|
|2. Working with Random Variables|
|2-1. Random Variables||1.4|
|2-2. Distributions, pmf's and pdf's||1.5, 1.6|
|2-5. Moments, Mean and Variance||2.2, 2.3|
|2-6. Generating Functions||2.3|
|3. Special Families of Distributions|
|3-1. Occurences and Waiting Times||3.2, 3.3|
|3-2. Random Sampling||3.2|
|3-3. Gamma Distributions and Friends||3.3|
|3-5. Location and Scale||3.5|
|3-6. Exponential Families||3.4|
|4. Handling Multiple Random Variables|
|4-1. Discrete Multivariate Distributions||4.1, 4.2, 4.3|
|4-2. Continuous Multivariate Distributions||4.1, 4.2, 4.3|
|4-3. Expectations and Conditional Expectations||4.1, 4.2|
|4-4. Covariance and Correlation||4.5|
|4-5. Bivariate Normal Distribution||4.5|
|4-6. Mixtures and Hierarchical Models||4.4|
|5. Bridging to Statistics|
|5-1. Random Samples and Statistics||5.1|
|5-2. Sums, Means and Moments||5.2|
|5-3. Statistical Limit Theorems||5.5|
|5-4. Random Normal Samples||5.3|
|5-5. Order Statistics and Quantiles||5.4|