STAT 516 (Statistical Methods II)

Spring 2016

Syllabus

Syllabus (Word document) or Syllabus (pdf format)

Instructor

David Hitchcock, associate professor of statistics

Office Hours -- Spring 2016

Mon-Tue-Wed-Fri 1:05-2:05 p.m., or by appointment

209A LeConte College
Phone: 777-5346
E-mail: hitchcock@stat.sc.edu

Course Meeting Times

Mon-Wed-Fri 10:50 a.m. - 11:40 a.m., Davis College, Room 209

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.

Course Notes

Homework Assignments

Homework Solutions

STAT 516 Supplementary Material

Access Instructions for SAS


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:

Downloading Instructions for R

Computing Tips: Some Review

Computer Code for Class Examples

Statistical TopicExample in SAS Code Example in R Code
Simple Linear Regression
and Correlation
(Chapter 7)
SAS example: (House data)
Output for SAS example
R example: (House data)
Output for R example
Multiple Linear Regression
(Chapter 8)
SAS example (California rain data)
Output for SAS example
R example (California rain data)
Output for R example
Transformations
(Chapter 7-8)
SAS example (surgical data)
Output for SAS example
R example (surgical data)
Output for R example
One-Way Analysis of Variance
(Chapter 6)
SAS example: (Rice data)
Output for SAS example
R example: (Rice data)
Output for R example
Two-Way ANOVA & Factorial Experiments
(Chapter 9)
SAS example (Gas mileage data)
Output for SAS example
R example: (Gas mileage data)
Output for R example
Randomized Block Design
(Chapter 10)
SAS example (Wheat data)
Output for SAS example
R example (Wheat data)
Output for R example
Randomized Block Design with Sampling
(Chapter 10)
SAS example: (Rubber data)
Output for SAS example
R example: (Rubber data)
Output for R example
Latin Square Design
(Chapter 10)
SAS example (Productivity data)
Output for SAS example
R example: (Productivity data)
Output for R example
Analysis of Unbalanced Data
(Chapter 11)
SAS example (Table 11.3 data)
Output for SAS example
R example (Table 11.3 data)
Output for R example
Analysis of Covariance (ANCOVA)
(Chapter 11)
SAS example (Trigonometry scores data)
Output for SAS example
R example (Trigonometry scores data)
Output for R example
Logistic Regression
(Chapter 13)
SAS example (TIF data)
Output for SAS example
R example (TIF data)
Output for R example

Some additional code

Some additional data 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.

HELPFUL R RESOURCE:


Supplementary material available for download:
Click here for Basics of R: A Primer, by Don Edwards.
Introduction to R, Comprehensive R Archive Network (CRAN).
Available at CRAN home page (click "Manuals" at left side of page; then choose the first manual, "Introduction to R").

Data Sets

For those using SAS:

For those using R:

Review Sheets

Formula Sheets

You may bring to the first 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 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).

Exam Solutions

Information about Project

Exams