**Course Announcement**

**Time:**Monday, Wednesday, Friday at 10:00 a.m. - 10:50 a.m.

**Location:**Taft Hall 216**Instructor:**Jie Yang

**Office:**SEO 539

**Phone:**(312) 413-3748

**E-Mail:**jyang06 AT math DOT uic DOT edu

**Office Hours:**Monday, Wednesday, Friday at 12:00 p.m. - 1:00 p.m. (or by appointment)**Textbook:**Johannes Ledolter and Robert V. Hogg,*Applied Statistics for Engineers and Physical Scientists*, Prentice Hall, 3rd edition, 2009.

**Reference book:**Ronald P. Cody and Jeffrey K. Smith,*Applied Statistics and the SAS Programming Language*, Prentice Hall, 5th edition, 2006.

**Content:**Tests of hypotheses, simple linear regression, multiple linear regression, experiments with one factor, experiments of two or more factors

**Prerequisite:**Grade of C or better in STAT 381**Homework:**Turn in on Wednesdays before class; half of the grade counts for completeness; half of the grade counts for correctness of one selected problem.

**Midterms:**February 19th (Friday), and**March 19th (Friday)**, 10:00 a.m. - 11:00 a.m.

**Final Exam:**10:30 a.m. - 12:30 p.m. Friday, May 7th

**Grading:**Homework 20%, midterms 20% each, final exam 40%

**Grading Scale:**95% A , 85% B , 75% C , 65% D**Format of All Exams:**Each exam is based on the homework and the examples discussed in class. The last class session before each exam is a review session. Please prepare any questions that you may have.*No makeup exam will be given without a valid excuse*.

**Course Syllabus****WEEK****SECTIONS****BRIEF DESCRIPTION**01/11 - 01/15 4.5; 4.5; 4.6 Tests of characteristics of a single distribution; Tests of characteristics of two distributions 01/18 - 01/22 Holiday; 4.6; 4.7 Tests of characteristics of two distributions; Certain chi-square tests 01/25 - 01/29 4.7; 8.1; 8.1 Certain chi-square tests; Simple linear regression model 02/01 - 02/05 8.1; 8.2; 8.2 Simple linear regression model; Inferences in the regression model 02/08 - 02/12 8.3; 8.3; 8.4 Adequacy of the fitted model; Multiple linear regression 02/15 - 02/19 8.4; Review; Midterm 1 Multiple linear regression 02/22 - 02/26 8.4; 8.5; 8.5 Multiple linear regression; More on multiple regression 03/01 - 03/05 6.1; 6.1; 6.2 Completely randomized one-factor experiments; Other inferences in one-factor experiments 03/08 - 03/12 6.2; 6.2; 6.3 Other inferences in one-factor experiments; Randomized complete block designs 03/15 - 03/19 Review; Midterm 2; 6.3 Randomized complete block designs 03/29 - 04/02 6.3; 6.4; 6.4 Randomized complete block designs; Designs with two blocking variables: Latin squares 04/05 - 04/09 7.1; 7.1; 7.1 Two-factor factorial designs 04/12 - 04/16 7.2; 7.2; 7.3 Nested factors and hierarchical designs; General factorial and 2^k factorial experiments 04/19 - 04/23 7.3; 7.4; 7.4 General factorial and 2^k factorial experiments; 2^{k-p} fractional factorial experiments 04/26 - 04/30 7.4; Review; Review 2^{k-p} fractional factorial experiments 05/03 - 05/07 Final exam Final exam

**Homework**- Homework #1, due 01/22/2010

- Homework #2, due 01/27/2010

- Homework #3, data set of Exercise 8.1-1 , due 02/03/2010

- Homework #4, data set of Exercise 8.1-3 , due 02/10/2010

- Homework #5, due 02/17/2010

- Homework #6, data set of Exercise 8.3-9 , due 03/03/2010

- Homework #7, data set of Exercise 8.4-7 , due 03/10/2010

- Homework #8, data set of Exercise 8.5-8 , due 03/17/2010

- Homework #9, due 03/31/2010

- Homework #10, due 04/09/2010

- Homework #11, due 04/16/2010

- Homework #12, due 04/23/2010

- Homework #13, due 04/28/2010

- Homework #1, due 01/22/2010
**R Code for the Course**- R code for §4.5 (binomial distribution, operating characteristic curve)

- R code for §4.6 (read data into R, t test) data set of Example 4.6-3

- R code for §8.1 (print graph, simple linear regression) data set of Table 8.1-1

- R code for §8.3 (simple linear regression) data set of Exercise 8.3-6

- More R code for §8.3 (residual plots, outliers) data set of Example 8.3-2

- R code for §8.4 (multiple linear regression) data set of Table 8.4-2 data set of ACH example

- R code for §8.5 (multiple linear regression) data set of Table 8.5-6

- R code for §6.1 & §6.2 (dot diagram, boxplot, Tukey's Q-method)

- R code for §6.3 (one-factor block design) data set of Table 6.3-1

- R code for §7.1 (two-factor factorial design) data set of Table 7.1-5

- R code for §7.3 (2^k factorial experiment, normal probability plot)

- R code for §4.5 (binomial distribution, operating characteristic curve)
**SAS Code for the Course**- SAS code for §8.3 (Simple linear regression) data set of Exercise 8.3-6

- SAS code for §8.4 (Mulitple linear regression)

- SAS code for §8.3 (Simple linear regression) data set of Exercise 8.3-6
**Relevant Course Materials**- Textbook website (Data, R code, etc)

- E. L. Lehmann,
*Testing Statistical Hypotheses*, 2nd edition, Springer, 1997 -- a good reference book

- M. H. Kutner, C. J. Nachtsheim, J. Neter, and W. Li,
*Applied Linear Statistical Models*, 5th edition, McGraw-Hill/Irwin, 2005 -- a good reference book

- Learn R in 15 Minutes

- Downloadable Books on R:
*An Introduction to R*, by William N. Venables, David M. Smith and the R Development Core Team

*Using R for Data Analysis and Graphics - Introduction, Code and Commentary*, by John H. Maindonald

*Practical Regression and ANOVA using R*, by Julian J. Faraway

**More R Books in Different Languages ...**

- Textbook website (Data, R code, etc)

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