Stat 427: R Programming
Home
Course Logistics
Syllabus
Contact
Dates
Links
Lectures
Schedule
Module 1: Getting Started
Module 2: R Scripts
Module 3: Functions
Module 4: Basic Graphs
Module 5: Data Input and Output
Module 6: Iterative Data Processing
Module 7: Logic and Control
Module 8: R Markdown and Packages
Module 9: Mathematical Functions
Module 10: Data Validation, Cleaning, Combining Datasets
Module 11: Matrix Arithmetic
Module 12: Systems of Linear Equations
Module 13: Advanced Graphs
Module 14: Probability and Simulation
Module 15: Introductory Inferential Methods
Supplemental Topics
>
Module 16: Real World Examples
Module 17: Fitting Models to Data
Review
>
Intro Class lectures
Coursework
Instructions
Labs
Project
R
Code
Information
Instructions for accessing drives:
Mapping shared drive
OneDrive in Vlab, see
ITS website
Read in data (create SAS dataset)
SAS version releases
CARDS/DATALINES1
CARDS/DATALINES2
INFILE
Excel
exceloutput
FILENAME with DATA step
Formats
comparison of format vs. no format
formats2
length1
length2
title/foot
drop/keep
where1
dates1
dates2
label1
label2
user defined formats
informat
dsd
missover
options1
options2
ODS/Reports
ods statement1
ods style
style list
multiple outs
Cleaning and Validation
valid1
valid2
valid3
clean
Conditional selection
new variable
if-then-do
if-then-delete
drop=/keep=
where
trasnformations
Combining datasets
concatenation
sort
merge
append
PROC SQL merge
nodup
nonmatch
Graphs
graphs:
1
2
Loops and Macros
doloops:
1
2
3
macro list
macros:
1
2
3
4
power macro
Statistical Analyses
1 sample t:
1
2
2 sample t
paired t
slr (regression)
multiple regression
1 (keeping all variables)
2 (model selection)
anova
(CRD):
1
2
RCBD
CRF:
1
2
chi-square test
1 and 2 proportions
Home
Course Logistics
Syllabus
Contact
Dates
Links
Lectures
Schedule
Module 1: Getting Started
Module 2: R Scripts
Module 3: Functions
Module 4: Basic Graphs
Module 5: Data Input and Output
Module 6: Iterative Data Processing
Module 7: Logic and Control
Module 8: R Markdown and Packages
Module 9: Mathematical Functions
Module 10: Data Validation, Cleaning, Combining Datasets
Module 11: Matrix Arithmetic
Module 12: Systems of Linear Equations
Module 13: Advanced Graphs
Module 14: Probability and Simulation
Module 15: Introductory Inferential Methods
Supplemental Topics
>
Module 16: Real World Examples
Module 17: Fitting Models to Data
Review
>
Intro Class lectures
Coursework
Instructions
Labs
Project
R
Code
Information