Week01

ideas and concepts

Introduction to R and others

1. Downloading and Installing R
2. Starting R
3. Entering Commands
4. Exiting from R
5. Interrupting R
6. Viewing the Supplied Documentation
7. Getting Help on a Function
8. Searching the Supplied Documentation
9. Getting Help on a Package
10. Searching the Web for Help
11. Finding Relevant Functions and Packages
12. Searching the Mailing Lists
13. Submitting Questions to the Mailing Lists

Assignment

Week02

Some basics

1. Introduction
2. Printing Something
3. Setting Variables
4. Listing Variables
5. Deleting Variables
6. Creating a Vector
7. Computing Basic Statistics
8. Creating Sequences
9. Comparing Vectors
10. Selecting Vector Elements
11. Performing Vector Arithmetic
12. Getting Operator Precedence Right
13. Defining a Function
14. Typing Less and Accomplishing More
15. Avoiding Some Common Mistakes

using theories and making hypotheses

Week03

Navigating software

1. Introduction
2. Getting and Setting the Working Directory
3. Saving Your Workspace
4. Viewing Your Command History
5. Saving the Result of the Previous Command
6. Displaying the Search Path
7. Accessing the Functions in a Package
8. Accessing Built-in Datasets
9. Viewing the List of Installed Packages
10. Installing Packages from CRAN
11. Setting a Default CRAN Mirror
12. Suppressing the Startup Message
13. Running a Script
14. Running a Batch Script
15. Getting and Setting Environment Variables
16. Locating the R Home Directory
17. Customizing R

Week04

Input and output

1. Introduction
2. Entering Data from the Keyboard
3. Printing Fewer Digits (or More Digits)
4. Redirecting Output to a File
5. Listing Files
6. Dealing with “Cannot Open File” in Windows
7. Reading Fixed-Width Records
8. Reading Tabular Data Files
9. Reading from CSV Files
10. Writing to CSV Files
11. Reading Tabular or CSV Data from the Web
12. Reading Data from HTML Tables
13. Reading Files with a Complex Structure
14. Reading from MySQL Databases
15. Saving and Transporting Objects

Week05

Data Structures

1. Introduction
2. Appending Data to a Vector
3. Inserting Data into a Vector
4. Understanding the Recycling Rule
5. Creating a Factor (Categorical Variable)
6. Combining Multiple Vectors into One Vector and a Factor
7. Creating a List
8. Selecting List Elements by Position
9. Selecting List Elements by Name
10. Building a Name/Value Association List
11. Removing an Element from a List
12. Flatten a List into a Vector
13. Removing NULL Elements from a List
14. Removing List Elements Using a Condition
15. Initializing a Matrix
16. Performing Matrix Operations
17. Giving Descriptive Names to the Rows and Columns of a Matrix
18. Selecting One Row or Column from a Matrix
19. Initializing a Data Frame from Column Data
20. Initializing a Data Frame from Row Data
21. Appending Rows to a Data Frame
22. Preallocating a Data Frame
23. Selecting Data Frame Columns by Position
24. Selecting Data Frame Columns by Name
25. Selecting Rows and Columns More Easily
26. Changing the Names of Data Frame Columns
27. Editing a Data Frame
28. Removing NAs from a Data Frame
29. Excluding Columns by Name
30. Combining Two Data Frames
31. Merging Data Frames by Common Column
32. Accessing Data Frame Contents More Easily
33. Converting One Atomic Value into Another
34. Converting One Structured Data Type into Another

Week06

Data Transformations

1. Introduction
2. Splitting a Vector into Groups
3. Applying a Function to Each List Element
4. Applying a Function to Every Row
5. Applying a Function to Every Column
6. Applying a Function to Groups of Data
7. Applying a Function to Groups of Rows
8. Applying a Function to Parallel Vectors or Lists

Strings and Dates

Week07

Probability

1. Introduction
2. Counting the Number of Combinations
3. Generating Combinations
4. Generating Random Numbers
5. Generating Reproducible Random Numbers
6. Generating a Random Sample
7. Generating Random Sequences
8. Randomly Permuting a Vector
9. Calculating Probabilities for Discrete Distributions
10. Calculating Probabilities for Continuous Distributions
11. Converting Probabilities to Quantiles
12. Plotting a Density Function

Week08

Mid-term period

Week09

General Statistics

1. Introduction
2. Summarizing Your Data
3. Calculating Relative Frequencies
4. Tabulating Factors and Creating Contingency Tables
5. Testing Categorical Variables for Independence
6. Calculating Quantiles (and Quartiles) of a Dataset
7. Inverting a Quantile
8. Converting Data to Z-Scores
9. Testing the Mean of a Sample (t Test)
10. Forming a Confidence Interval for a Mean
11. Forming a Confidence Interval for a Median
12. Testing a Sample Proportion
13. Forming a Confidence Interval for a Proportion
14. Testing for Normality
15. Testing for Runs
16. Comparing the Means of Two Samples
17. Comparing the Locations of Two Samples Nonparametrically
18. Testing a Correlation for Significance
19. Testing Groups for Equal Proportions
20. Performing Pairwise Comparisons Between Group Means
21. Testing Two Samples for the Same Distribution

Week10

General Statistics

Week11

Graphics

1. Introduction
2. Creating a Scatter Plot
3. Adding a Title and Labels
4. Adding a Grid
5. Creating a Scatter Plot of Multiple Groups
6. Adding a Legend
7. Plotting the Regression Line of a Scatter Plot
8. Plotting All Variables Against All Other Variables
9. Creating One Scatter Plot for Each Factor Level
10. Creating a Bar Chart
11. Adding Confidence Intervals to a Bar Chart
12. Coloring a Bar Chart
13. Plotting a Line from x and y Points
14. Changing the Type, Width, or Color of a Line
15. Plotting Multiple Datasets
16. Adding Vertical or Horizontal Lines
17. Creating a Box Plot
18. Creating One Box Plot for Each Factor Level
19. Creating a Histogram
20. Adding a Density Estimate to a Histogram
21. Creating a Discrete Histogram
22. Creating a Normal Quantile-Quantile (Q-Q) Plot
23. Creating Other Quantile-Quantile Plots
24. Plotting a Variable in Multiple Colors
25. Graphing a Function
26. Pausing Between Plots
27. Displaying Several Figures on One Page
28. Opening Additional Graphics Windows
29. Writing Your Plot to a File
30. Changing Graphical Parameters

Week12

Graphics

Week13

Linear Regression and ANOVA

1. Introduction
2. Performing Simple Linear Regression
3. Performing Multiple Linear Regression
4. Getting Regression Statistics
5. Understanding the Regression Summary
6. Performing Linear Regression Without an Intercept
7. Performing Linear Regression with Interaction Terms
8. Selecting the Best Regression Variables
9. Regressing on a Subset of Your Data
10. Using an Expression Inside a Regression Formula
11. Regressing on a Polynomial
12. Regressing on Transformed Data
13. Finding the Best Power Transformation (Box?Cox Procedure)
14. Forming Confidence Intervals for Regression Coefficients
15. Plotting Regression Residuals
16. Diagnosing a Linear Regression
17. Identifying Influential Observations
18. Testing Residuals for Autocorrelation (Durbin?Watson Test)
19. Predicting New Values
20. Forming Prediction Intervals
21. Performing One-Way ANOVA
22. Creating an Interaction Plot
23. Finding Differences Between Means of Groups
24. Performing Robust ANOVA (Kruskal?Wallis Test)
25. Comparing Models by Using ANOVA

Week14

Linear Regression and ANOVA

Week15

Group Presentation

Week16

Group Presentation
Final-term