STAT 410 - Schedule

STAT 410 / STAT 615 Course Schedule, Fall 2012

Schedule

Class topics will come on-line in this schedule in a timely manner, along with recommended reading. I will also indicate here assignments with due dates, and if any special handout might be provided in class. Should you have trouble getting a printout please get help from Mr. Patrick O'Driscoll and also notify me.

Additional, optional reading is listed in the Course materials.

If a .ps or .pdf file comes up with poor resolutin on your screen, the printed version should still be perfectly fine. If that is not the case alert me.
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No.	Date	Lecture Topic / Lab Topic	Homework & Due date	Section(s) in Kutner et al.	Optional Reading
1	Aug 21	Orientation, introduction Review of matrix algebra and properties	Familiarize yourself with this course web site, starting at the STAT 410 / STAT 615 home page. Nothing to turn in, but I will assume you know everything I post, and check for updates before every class.	Ch 1.1 - 1.2, Ch 5.1 - 5.3	Lecture notes L1.1-Review-of-Matrix-Algebra.pdf
Lab 1	Aug 22	Introduction to R and RStudio, setting up software environment. Basic R operations.
2	Aug 23	Review of basics, cont'd		Ch 5.1 - 5.8	Lecture notes L1.1-Review-of-Matrix-Algebra.pdf Lecture slides L2h.pdf
3	Aug 28	Review of basics (wrap up) Simple linear regression	Assignment 1 due Sep 4	Ch 5.1 - 5.8 Ch 1.1 - 1.6	Lecture slides L3h.pdf
Lab 2	Aug 29	Introduction to R and RStudio, Basic R operations, cont'd.
4	Aug 30	Simple linear regression Multiple linear regression		Ch 5.1 - 5.11, Ch 6.2 Ch 1.1 - 1.7	Lecture slides L3h.pdf Lecture slides L4h.pdf
5	Sep 4	Multiple linear regression, cont'd Properties of Least Squares Estimation of variance Alternative form of simple linear regression	Assignment 2 due Sep 11	Ch 5.1 - 5.11, Ch 6.2 Ch1.1 - 1.7, A.5	Lecture slides L4h.pdf Lecture slides L5h.pdf
Lab 3	Sep 5	Estimation of Beta0, Beta1, and Sigma; Demonstration of the Gauss-Markov Theorem
6	Sep 6	Hypothesis testing Confidence Interval		Ch 5.1 - 5.11, Ch 6.2 Ch1.1 - 1.7, A.5; Ch 2.1 - 2.3	Lecture slides L6h.pdf
7	Sep 11	Eigenvalues, eigenvectors, condition number Principle Components Lecture by Ben White	Assignment 3 due Sep 18	TBA	Lecture notes L-BWh.pdf
Lab 4	Sep 12	Hypothesis testing, Confidence Intervals
8	Sep 13	NO CLASS Allowance for preparation for QUIZ 1
9	Sep 18	Quiz 1 Analysis of Variance, ANOVA	Assignment 4 due Sep 25	Ch 2.7, 2.9	Lecture slides L7h.pdf Paper on degrees of freedom
Lab 5	Sep 19	Eigenvalues, Eigenvectors, Condition Number, and PCA
10	Sep 20	Analysis of Variance, ANOVA, cont'd Coefficient of Determination Interval Estimation of the Mean Response		Ch 2.4, 2.5, 2.7, 2.9	Lecture slides L7h.pdf Lecture slides L8h.pdf Paper on degrees of freedom
11	Sep 25	Maximum Likelihood Estimation	Assignment 5 due Oct 2	1.8, A.5	Lecture slides L9h.pdf Casella & Berger, p 516 Wasserman Ch 9.4 - 9.10
Lab 6	Sep 26	Mean response CI, PI, and R^2
12	Sep 27	Multiple Regression		Ch 1.8, A.5; Ch 6	Lecture slides L10h.pdf
13	Oct 2	MLE, ANOVA and hypothesis testing for Multiple Regression Model selection with hypothesis testing	Assignment 6 due Oct 9	Ch 1.8, A.5; Ch 6 Ch 5.12, 5.13, 6.1 - 6.5	Lecture slides L11h.pdf Lecture slides L12h.pdf
Lab 7	Oct 3	Multiple Regression, and Hypothesis Testing
14	Oct 4	Checking the Assumptions of Regression Models		Ch 12.1 - 12.3; B.6, B.7	Lecture slides L13h.pdf Ch 12.4-12.5 of Kutner et al.
15	Oct 9	Checking the Assumptions of Regression Models	Assignment 7 due Oct 23 (Yes, in two weeks :-))	Ch 10.1 - 10.4, Ch 12.1 - 12.3; B.6, B.7	Lecture slides L13h.pdf Ch 12.4-12.5 of Kutner et al.
Lab 8	Oct 10	Residual and QQ Plots, Outliers' effect on the model
	Oct 11	NO CLASS Fall recess
16	Oct 16	Multiple Regression, cont'd Joint Confidence Intervals Multi-collinearity		Ch A.2; Ch 4.1-4.3 pp 154-160; Ch 7.6, Ch 10.5	Lecture slides L14h.pdf Wasserman pp 161-164
Lab 9	Oct 17	Identifying correlations, and outliers in data: Leverage Points, PRESS residuals, Cook’s Distance, ACF, Correlation Coefficient, and Durbin-Watson Statistic
17	Oct 18	No lecture (Allowance for midterm exam) Exam 1 will be handed out at the beginning of the class period.	Exam 1 (take home), due Oct 19, 5:00pm
18	Oct 23	Multiple Regression, cont'd Permutation tests	Assignment 8 due Oct 30	Ch 5.12, 5.13, 6.1 - 6.4, 6.5, Ch 16.9	Lecture slides L15h.pdf Wasserman 10.5
Lab 10	Oct 24	Partial regression plots Permutation tests
19	Oct 25	Lack of fit test; transformations;		Ch 3.7, 3.8, 3.9; p 146 (references)	Lecture slides L16h.pdf
20	Oct 30	Transformations (Box-Cox); Generalized LS	Assignment 9 due Nov 6	Ch 3.7, 3.8, 3.9; p 146 (references); pp 424-431 Ch 11.1	Lecture slides L16h.pdf Lecture slides L17h.pdf
Lab 11	Oct 31	Multi-correlation Box-Cox transformations
21	Nov 1	Generalized LS; Weighted LS		Ch 11.1, 11.2, 11.3	Lecture slides L17h.pdf On-line notes from JHU and SIU, see under Course materials
22	Nov 6	Robust regression Ridge Regression	Assignment 10 due 11:55pm, Nov 16 (Fri after Quiz 2)	Ch 11.1, 11.2, 11.3	Lecture slides L17h.pdf On-line notes from JHU and SIU, see under Course materials
Lab 12	Nov 7	LOF test, Generalized LS
23	Nov 8	Variable selection		Ch 9.3 - 9.6	Lecture slides L18h.pdf
24	Nov 13	Quiz 2 No lecture	Assignment 11 (last home work :-) ) due Nov 20
Lab 13	Nov 14	Robust regression, Variable selection
25	Nov 15	Qualitative predictors and ANCOVA, indicator variables		Ch 8.3 - 8.7	Ch 22.1 - 22.5 of Kutner et al. Lecture slides L19h.pdf
26	Nov 20	Qualitative predictors ANCOVA, ANOVA		Ch 8.3 - 8.7	Ch 22.1 - 22.5 of Kutner et al. Lecture slides L19h.pdf updated today
Lab	Nov 21	NO LAB	Mandatory exercises with R scripts ANCOVA-1 and ANCOVA-2
	Nov 22	NO CLASS, THANKSGIVING
27	Nov 27	Logistic Regression Life after linear regression	(Graded Assignment 11 returned.)
Lab	Nov 28	LAB Clinic	Bring your questions to clarify, before Exam 2.
28	Nov 29	No lecture, allowance for midterm 2)	Exam 2 handed out in class, due Nov 30

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