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319182.pdf
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R
Course Contents
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Session 1: R
Introduction and References
Notation Conventions used throughout the course Starting R for Windows
Getting Help
The R Console
The Menu bar
The Toolbar
Practical Session 1
1. Objective of this exercise Starting R
Accessing built-in datasets A simple analysis
Viewing output
Printing and saving output Leaving R
2. Creating your own R Data File Using the Data Editor
The Data
Defining the Variables Entering the Data Saving the Data
Some Descriptive Statistics Exiting R
Session 2: Importing Data Files from Text Formats Reading a raw data file
Importing Text Files
A note about variable names in R
Notes on the Data Editor: Adjusting Column widths Missing Values
Importing an Excel file to R Practical Session 2
1. Reviewing the demonstration
2. Importing an ASCII file, defining labels & missing values
British Social Attitudes Survey, 1987:Coding Sheet
Session 3: Data and Language Structures R as a calculator
Vectors and assignment
Generating Sequences
Character Vectors
Arithmetic Operators
Comparison Operators
Extracting Data by using an index 3-7
Simple and Complex Objects 3-9
Loops and Conditional Execution 3-10
1. Conditional Statement: If Statement 3-10
2. Iteration: for, while 3-12
Practical Session 3 3-13
1 . Reviewing the demonstration 3-13
2. Operators and Subscripts 3-13
3. Loops and Conditional Execution 3-14
Session 4: Crosstabulation and Recode
Crosstabulation in R 4-2
Recoding 4-4
How to recode 4-5
Recoding into a different variable 4-5
Recoding AGE into age groups (Recode Ranges) 4-6
Missing values and recoding 4-7
Variable labels 4-8
Practical Session 4 4-9
1. Reviewing the demonstration 4-10
2. Age and gender and government spending 4-10
3. Political identification and age 4-11
Session 5: Computing New Variables
Numerical Expressions 5-2
Missing values and compute 5-5
Other types of variables 5-6
More on data frames 5-8
The function tapplyt) 5-9
Arrays and matrices 5-11
Index arrays 5-13
Manipulation of Arrays and Matrices 5-15
Practical Session 5 5-18
1. Reviewing the demonstration 5-18
2. Computing new variables/ producing bar charts 5-18
3. Computing new matrices 5-19
Session 6: Selecting, Sampling Cases and Functions
Selecting Cases 6-2
Selecting the whole set of cases again 6-4
Sampling Cases 6-4
Split Data Frame Command 6-5
Functions 6-7
Practical Session 6 6-9
1. Reviewing the demonstration 6-9
2. Mobility Tables 6-9
3. Subdividing by sex 6-10
4. Writing functions 6-10
Session 7: Numerical and Graphical Summaries of Data
Summary Statistics 7-2
Histograms Box-Plots
Bar Charts
Scatter Plots Practical Session 7
1. Reviewing the demonstration
2. Further Graphs
3. Exploring the age of the respondents
4. Investigating the education of respondent and family
Session 8: R-Commander, Two-Sample T-Tests and ANOVA
R Commander Example
Running R Commander automatically
Running Scripts in R
Two-Sample t-test- Comparing Two Independent Means Paired t-test for Means - Comparing Two Dependent Means One-Way ANOVA
Pairwise Comparisons
Very simple linear regression Practical Session 8
1. Reviewing the demonstration
2. Analysis of the STATLABA data
3. Consolidation
Session 9: The General linear model and graphics An example: block designs
Model simplification
More on linear regression More on graphics Practical Session 9
Session 10: Additional topics 1. The Chi-Squared (Z2) test Cross-tabulation
Observed and Expected Frequencies
Comparing Observed and Expected Frequencies the x2 Test
Degrees of Freedom
2. Logistic regression The glmO function Modelling proportions
Binary logistic regression - model selection
3. Survival Analysis
Functions used in Survival analysis
Kaplan Meier estimate of the Survival Function Cox Proportional hazards model
Parametric models
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