STAT 705 (Data Analysis II)

Spring 2017

Syllabus

Syllabus (Word document) or Syllabus (pdf format)

Instructor

David Hitchcock, assistant professor of statistics

Spring 2017 Office Hours:

Mon 2:15-3:15 pm, Tues 2:00-3:00 pm, Wed 2:15-3:15 pm, Thurs 1:45-2:45 pm
Please feel free to make appointments to see me at other times.

Class Meeting Time

MWF, 10:50 am - 11:40 am, Leconte College 201A

Textbook:
Required Textbook: "Applied Linear Statistical Models" (5th edition) by Kutner, Nachtsheim, Neter, and Li.
(This is the same book used for STAT 704 in the fall.)

Supplementary Books (NOT required):
"Linear Models with R" by Faraway, J.J.
"Extending the Linear Model with R" by Faraway, J.J.
"An R and S-plus Companion to Applied Regression" by Fox, J.
"Statistical Analysis and Data Display" by Heiberger and Holland.
"Statistical Research Methods in the Life Sciences" by Rao, P.V.

Course Notes

Computer Code for Class Examples

Statistical TopicExample in SAS Code Example in R Code
Regression with Qualitative Predictors SAS example: (Insurance Innovation data & Shirt data) R example: (Insurance Innovation data & Shirt data)
Single-Factor ANOVA SAS example: (Kenton Foods data) R example: (Kenton Foods data)
Regression Approach to ANOVA model SAS example: (Kenton Foods data) R example: (Kenton Foods data)
Investigation of Treatment Means SAS example: (Kenton Foods data) R example: (Kenton Foods data)
Checking ANOVA Model Assumptions SAS example: (Kenton Foods data) R example: (Kenton Foods data)
Two-Factor ANOVA SAS example: (Castle Bakery data) R example: (Castle Bakery data)
Investigation of Factor Effects
(No Interaction)		 SAS example: (Castle Bakery data) R example: (Castle Bakery data)
Investigation of Factor Effects
(With Interaction)		 SAS example: (Melon data) R example: (Melon data)
Two-Factor ANOVA With
One Observation per Cell		 SAS example: (Insurance data) R example: (Insurance data)
Two-Factor ANOVA With
Unequal Cell Sample Sizes		 SAS example: (Growth data)
(SAS example includes empty-cell analysis) 		R example: (Growth data)
Three-Factor ANOVA SAS example: (stress data) R example: (stress data)
Random-Effects Model SAS example: (Apex Enterprises data) R example: (Apex Enterprises data)
Mixed-Effects Model SAS example: (training data) R example: (training data)
Mixed-Effects Model with Unbalanced Data SAS example: (Sheffield data) ---
Randomized Complete Block Design SAS example: (executive data) R example: (executive data)
Generalized Random Block Design SAS example: (task completion data) R example: (task completion data)
Balanced Incomplete Block Design SAS example: (taste test data) R example: (taste test data)
Latin Square Design SAS example: (bank teller data) R example: (bank teller data)
Single-Factor Repeated Measures SAS example: (wine judging data) R example: (wine judging data)
Two-Factor Repeated Measures SAS example: (shoe data) ---
Repeated Measures: Different Approaches SAS example: (dental data) ---
Distribution-free Tests in ANOVA
(Kruskal-Wallis Test & multiple comparisons)		 SAS example: (soil data) R example: (soil data)
Distribution-free Tests for RCBD
(Friedman Test)		 SAS example: (soybean data)
SAS example: (windspeed data) 		R example: (soybean data)
R example: (windspeed data)
Analysis of Covariance SAS example: (cracker data) R example: (cracker data)
Nested Design SAS example: (training school data) R example: (training school data)
Weighted Least Squares SAS example (blood pressure data) R example (blood pressure data)
Ridge and LASSO Regression SAS example (body fat data) R example (body fat data)
Robust Regression SAS example (math proficiency data) R example (math proficiency data)
Bootstrap in Regression --- R example: (Toluca and blood pressure data)
Piecewise Regression SAS example: (raw materials data) R example: (raw materials data)
Nonlinear Regression SAS example (injured patients data) R example (injured patients data)
Simple Logistic Regression SAS example (programming task data) R example (programming task data)
Multiple Logistic Regression SAS example (disease outbreak data) R example (disease outbreak data)
Poisson (Count) Regression SAS example (Miller lumber data) R example (Miller lumber data)
Nonparametric Regression:
Kernel Regression		 -- R example (simulated & Old Faithful data)
Nonparametric Regression:
Regression with Splines		 SAS example (simulated data) R example (simulated & Old Faithful data)
Regression Trees and Random Forests -- R example (Boston housing & admissions data)
Regression with Time Series SAS example (Blaisdell data) R example (Blaisdell data)
Missing Data Methods SAS example (Dental and NLS with missing data) R example (NLS with missing data)
1 × 2 Contingency Tables
(Inference about binomial probability)
(z-test/CI and Binomial test)		 SAS example: (driver's test data) R example: (driver's test data)
1 × c Contingency Tables
(Inference about multinomial probabilities)
(Chi-square goodness-of-fit test)		 SAS example: (blood types data) R example: (blood types data)
2 × 2 Contingency Tables
(Comparing 2 proportions, independent samples)
(z-test/CI and Fisher's Exact test)		 SAS example: (trees data) R example: (trees data)
2 × 2 Contingency Tables
(Comparing 2 proportions, paired samples)
(McNemar's test)		 SAS example: (ice cream data) R example: (ice cream data)
r × c Contingency Tables
(Chi-square test for independence &
Chi-square test for homogeneity)		 SAS example: (snoring data & voter data) R example: (snoring data & voter data)
Loglinear Models --- R example (various data sets)
Multicategory Logistic Regression SAS example (pregnancy duration data set) ---

Available Computing Resources:

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 or SAS Enterprise Guide by going to the Control Center:
R is available as a free download from the CRAN home page) and students who want SAS can buy a copy from USC Computer Services.
These packages are also available on the computers in the labs in LeConte College (and a few other buildings). Help in using R can be found on the CRAN home page.

Downloading Instructions for R

Computing Tips: Some Review

Homework

Example Homework Solutions

Data Sets

Review Sheets

Formula Sheets

Example Solutions

Information about the Project

Exams