209A LeConte College

Phone: 777-5346

E-mail: hitchcock@stat.sc.edu

__ Purpose:__ To complete a basic two course sequence (in conjunction with STAT 515 or 509) in statistical techniques available to the general practitioner for analyzing experimental data. To introduce students in many different disciplines to multiple regression and analysis of variance for basic experimental designs. To provide students with the knowledge to implement and interpret these standard linear models.

**Current Textbook:***Statistical Methods, Third Edition*, by R.J. Freund, W. J. Wilson and D. L. Mohr, 2010.

- Homework 1, Spring 2016 (due Wednesday, Jan. 27)

- Homework 2, Spring 2016 (due Monday, February 8)

- Homework 3, Spring 2016 (due Friday, February 26)

- Homework 4, Spring 2016 (due Wednesday, March 16)

- Homework 5, Spring 2016 (due Friday, April 8)

- Homework 6, Spring 2016 (due Tuesday, April 19 by 4 p.m.)

After going to the entry page, create a student account. You will receive an enrollment link in an email from the course instructor. Once your account is created, you can access SAS Studio by going to the Control Center:

- Introduction to SAS which should be a good instruction for the software

**Computer Code for Class Examples**

__ Required Computing Resources:__
Some problems in this course involve significant computations, and for spring 2016, we will
primarily learn to use the SAS software to do the needed computations.

You will need access to a computer with SAS Studio (available for free to students in this class). This can easily be accessed your home computer through the internet.

Alternatively, you could use the software package R (available as a free download from the CRAN home page). This can easily be downloaded onto your home computer.

Example code in both R and SAS will be provided on the course web page, but we will use SAS for the in-class examples.

Both R and SAS are available on the computers in the labs in LeConte College. Help in using R can be found on the CRAN home page.

Supplementary material available for download:

Click here for

Available at CRAN home page (click "Manuals" at left side of page; then choose the first manual, "Introduction to R").

- Simple Basket Goals data set (plain text) for Chapter 7, problem 5 -- with SAS commands for creating a data set

- U.S. Cities data set (plain text) for Chapter 7, problem 6 -- with SAS commands for creating a data set

- Heating Cost data set (plain text) for Chapter 7, problem 7

- English Grades data set (plain text) for Chapter 7, problem 3

- Birth Rate data set (plain text) for Chapter 7, problem 9 -- with SAS commands for creating a data set

- Basket Goals data set (plain text) for Chapter 8, problem 8 -- with SAS commands for creating a data set

- Liver data set (plain text) for Chapter 8, problem 10 -- with SAS commands for creating a data set

- Apartment Rent data set (plain text) for Chapter 8, problem 13 -- with SAS commands for creating a data set

- Tree Weight data set (plain text) for Chapter 8, problem 5 -- with SAS commands for creating a data set

- Health data set (plain text) for Chapter 8, problem 6 -- with SAS commands for creating a data set

- Concrete data set (plain text) for Chapter 6, problem 4

- Insecticide data set (plain text) for Chapter 6, problem 9 -- with SAS commands for creating a data set

- Fungus data set (plain text) for Chapter 6, problem 12

- Bank data set (plain text) for Chapter 6, problem 15 -- with SAS commands for creating a data set

- Table 9.21 data set (plain text) for Chapter 9, problem 2

- Roast data set (plain text) for Chapter 9, problem 4

- buildingsdata.txt data set (plain text) for Chapter 10 -- with SAS commands for creating a data set

- wheatdataLS.txt data set (plain text) for Chapter 10 -- with SAS commands for creating a data set

- Pig data set (plain text) for Chapter 11, problem 1

- Recognition data set (plain text) for Chapter 11, problem 9 -- with SAS commands for creating a data set

- Tree data set (plain text) for Chapter 11, problem 4 -- with SAS commands for creating a data set

- Brain data set (plain text) for Chapter 13, problem 3 -- with SAS commands for creating a data set

- Simple Basket Goals data set (plain text) for Chapter 7, problem 5 -- with R commands for creating a data frame

- Birth Rate data set (plain text) for Chapter 7, problem 9 -- with R commands for creating a data frame

- Basket Goals data set (plain text) for Chapter 8, problem 8 -- with R commands for creating a data frame

- Liver data set (plain text) for Chapter 8, problem 10 -- with R commands for creating a data frame

- Apartment Rent data set (plain text) for Chapter 8, problem 13 -- with R commands for creating a data frame

- Tree Weight data set (plain text) for Chapter 8, problem 5 -- with R commands for creating a data frame

- Health data set (plain text) for Chapter 8, problem 6 -- with R commands for creating a data frame

- Irrigation data set (plain text) for Chapter 8, problem 7 -- with R commands for creating a data frame

- Bank data set (plain text) for Chapter 6, problem 15 -- with R commands for creating a data frame

- Table 9.22 set (plain text) for Chapter 9, problem 3 -- with R commands for creating a data frame

- Cake data set (plain text) for Chapter 9, problem 9 -- with R commands for creating a data frame

- Oyster data set (plain text) for Chapter 10, problem 1 -- with R commands for creating a data frame

- Bird Count data set (plain text) for Chapter 10, problem 10 -- with R commands for creating a data frame

- Recognition data set (plain text) for Chapter 11, problem 9 -- with R commands for creating a data frame

- Tree data set (plain text) for Chapter 11, problem 4 -- with R commands for creating a data frame

- Brain data set (plain text) for Chapter 13, problem 3 -- with R commands for creating a data frame

You may bring to the second exam one standard-sized sheet of paper with anything you want written on it (for example, you should write any formulas you may need).

You may bring to the final exam three standard-sized sheets of paper with anything you want written on it (for example, you should write any formulas you may need).

- Midterm 1: Friday, Feb. 19
- Midterm 2: Friday, March 25
- Final Exam: Friday, April 29 - 9:00 a.m.