Instructor

Syllabus

Office Hours -- Fall 2005

Class Meeting Time

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, 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

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; PROC SQL	Delwiche and Slaughter	2.5 weeks

 

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

• Examples from Class: Section 5

• Examples from Class: Section 6

• Examples from Class: Section 7

• Examples from Class: Section 8

• Examples from Class: Section 9

• Examples from Class: Section 10

• Examples from Class: Section 11

• Example data file: brainbod.txt

• Example data file: garden.txt

• Example code: conditional.txt

• 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 Example Code from Class

• Very simple example of SAS program

• 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

• Simple custom reports

• 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

• Basic data set options and the IN= option

• Examples with the OUTPUT statement

• 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

• CALL SYMPUT example

• PROC SQL examples: basic stuff; subsetting and calculating; joining tables; and editing and altering tables.

Homework

• Homework 1

• Homework 2 (due September 19)

• Homework 3 (due September 12)

• Homework 4 (due September 27)
(HW 4 HINT ADDED 9/23/05)

• Homework 5 (due October 17)

• Homework 6 (due October 26)

• Homework 7 (due November 3)

• Homework 8 (due November 18)

• Homework 9 (due November 30)

Data Files for Homework

• hair_data.txt

• baseball_data.txt

• football_data.txt

• cake_data.txt

• tshirt.txt

• districtdata.txt

• champ36pres.txt

• footballroster.txt

• beatles_songlengths.txt

• moviereview.txt

• cake_data_duncan.txt

• cake_data_betty.txt

Example Homework Solutions

• Example homework 1 solution

• Example homework 2 solution

• Example homework 3 solution

• Example homework 4 solution

• Example homework 5 solution

• Example homework 6 solution

• Example homework 7 solution

• Example homework 8 solution

• Example homework 9 solution

Data Files for Exams

• R program for take home test 1: 517test1prog.txt

• R program for take home test 2: 517test2prog.txt

Exams

• Exam 1: September 30
• Exam 2: November 9
• Final Exam: Friday, December 9 (9:00 a.m.)