Instructor

Syllabus

Office Hours -- Fall 2012

Class Meeting Time

Accessing Online Lectures

Purpose: To help students learn computing skills that will be useful to them both in academic endeavors and as working statisticians. To introduce students to programming using the free software package R and the widely used commercial software SAS. Programming skills, rather than straightforward data analyses, are emphasized in this course.

Current Textbook: The Little SAS Book: A Primer (4th edition), by Delwiche and Slaughter.

Required Supplementary Material: Supplementary material available for download:
Basics of R: A Primer, by Don Edwards.
Click here for Basics of R: A Primer.
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").

Required Computing Resources: Access to a computer with R (available as a free download from the CRAN home page) and SAS (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. Help in using R can be found on the CRAN home page.

Downloading Instructions

• Instructions for Downloading R

• Instructions for Accessing SAS Enterprise Guide for Students (not available for Macs)

Topics Covered	Text	Time
Objects in R; Inputting and Outputting Data in R	Edwards	1.5 weeks
R Graphics, Functions, Arithmetic, Logicals, Conditional Execution, Subsetting, Sorting, Iteration	Edwards	2 weeks
Random Variables and Simulation Studies	TBA	1.5 weeks
Introduction to SAS; Reading and Writing Data	Delwiche and Slaughter	2 weeks
Working with Your Data; Sorting, Printing, Summarizing Data	Delwiche and Slaughter	2 weeks
Modifying and Combining Data Sets	Delwiche and Slaughter	1 week
MACRO programming in SAS; ODS output; PROC SGPLOT	Delwiche and Slaughter	2.5 weeks

 

Slides for Class Notes

• Class Notes: Edwards Sections 1-6 (R)

• Class Notes: Edwards Sections 7-12 (R)

• Class Notes: Random Numbers and Simulation

• Class Notes: Delwiche/Slaughter Chapter 1 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 2 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 3 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 4 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 6 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 7 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 5 (SAS)

• Class Notes: Delwiche/Slaughter Chapter 8 (SAS)

Example R Code from Class

• Examples from Class: Section 2

• Example function code: vecnorm.txt

• Examples from Class: Section 3

• Examples from Class: Section 4

• Excel file with Presidents data

• Examples from Class: Section 5

• Example data file: brainbod.txt

• Example data file: garden.txt

• Examples from Class: Section 6

• Examples from Class: Section 7

• Examples from Class: Section 8

• Example R code: conditional.txt

• Examples from Class: Section 9

• Examples from Class: Section 10

• Examples involving Dates

• Examples from Class: Section 11

• Examples from Class: Some 3-D plots

• football_data.txt file from class example

• Examples from Class: Section 12

• Example code: Simple Stochastic Search optimization

• Examples from Class: The optim() function

• Example 1: Hit-or-Miss integration

• Example 1: Classical Monte Carlo integration

• Example 2: Classical Monte Carlo integration

• Example code: Expected Values of Functions of r.v.'s

• Example code: Approximating Sampling Distributions

• Example code: Bootstrap method

SAS Code: Examples from Class

• Example of a Very Simple SAS Program

• hair_data.txt

• reading baseball data

• reading from external file

• Scores data file and reading in the simple scores

• More complicated scores data file and reading in the complicated scores

• Messy dog data and reading in the messy dog data

• Garden data (multiple lines per observation) and reading in garden data (multiple lines per observation)

• Garden data (multiple observations per line) and reading in garden data (multiple observations per line)

• reading in part of hair data

• scores data file (options) and reading in the scores with options

• scores data file (comma-delimited), scores data file (2 commas indicate missing value) and reading in the comma-delimited file (DLM and DSD)

• Example with PROC CONTENTS

• Creating new variables in the DATA step

• Conditional (IF-THEN-ELSE) statements and Dogs data

• Selecting a subset of data

• Working with dates

• RETAIN and sum statements

• ARRAY statements and Shortcut variable references and soil data set

• Subsetting with the WHERE statement (plus options for TITLE and FOOTNOTE)

• Sorting the baseball data

• Specialized printing with PROC PRINT and FORMAT

• PROC FORMAT for working with coded data and sas_roll.txt

• Simple custom reports and sas_roll2.txt

• Summary Statistics with PROC MEANS

• Counting Data with PROC FREQ

• NFL franchise data and using PROC TABULATE

• Expanded garden data and using PROC REPORT

• Modifying data sets with SET statement

• Merging data sets: temperature data and student data

• Examples with the OUTPUT statement

• Basic data set options and the IN= option

• baseball_data_wide.txt

• PROC TRANSPOSE examples: baby data and converting "wide" to "long" data

• NFL players data (very long) and using SAS automatic variables

• Macro Variables and %LET

• Simple Macros and Macros with Parameters and Macros with Conditional Logic

• Extension of Macros with Parameters Example

• Example of DO WHILE and DO UNTIL loops

• ODS examples: Plotting with ODS command and ODS with TRACE and SELECT

• Examples with PROC SGPLOT

Homework

• STAT J540 Homework 1, Fall 2012 (due Wednesday, September 5 by 3:00 p.m.)

• STAT J540 Homework 2, Fall 2012 (due Friday, September 21 by 3:00 p.m.)

• STAT J540 Homework 3, Fall 2012 (due Friday, October 12 by 3:00 p.m.)

• STAT J540 Homework 4, Fall 2012 (due Wednesday, October 31 by 3:00 p.m.)

• STAT J540 Homework 5, Fall 2012 (due Tuesday, November 20 by 3:00 p.m.)

Instructions for Homework Abstracts

• Guide for Abstracts for STAT J540 Homework

• Some Good Example Abstracts from STAT J540 Homework 1

Data Files for Homework

• tennisplayers2012.txt

• tshirt.txt

• districtdata.txt

• champ36pres.txt

• baseballroster.txt

• moviereview.txt

Example Homework Solutions

• Example Solution Code, Homework 1, Fall 2012 (This may not be the only way to solve the problem)

• Example Solution Code, Homework 2, Fall 2012 (This may not be the only way to solve the problem)

• Example Solution Code, Homework 3, Fall 2012 (This may not be the only way to solve the problem)

• Example Solution Code, Homework 4, Fall 2012 (This may not be the only way to solve the problem)

• Example Solution Code, Homework 5, Fall 2012 (This may not be the only way to solve the problem)

Example Quiz Solutions

• Quiz 1, Fall 2012: Solution Key for Version A (blue version)

• Quiz 1, Fall 2012: Solution Key for Version B (yellow version)

• Quiz 1, Fall 2012: Solution Key for Version C (white version)

• Quiz 2, Fall 2012: Solution Key for Version A (white version)

• Quiz 2, Fall 2012: Solution Key for Version B (blue version)

• Quiz 2, Fall 2012: Solution Key for Version C (yellow version)

Example Final Exam Solutions

• Some Example Solutions for the Final Exam Problems

Data Files for Exams

• cake_data_duncan.txt

• cake_data_betty.txt

Exam Sheets

Information about the Graduate Student Project

Exams

• Quiz 1: Thursday, September 27 (Notify me if you have a conflict and cannot take it in class)

• Quiz 2: Thursday, November 1 (Notify me if you have a conflict and cannot take it in class).

• Take-home Final Exam (Word document) or Take-home Final Exam (pdf document) (due Monday, December 10 by 3:00 p.m. through email)

• Some Clarifications about Final Exam Questions