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Table of Contents
실라버스: 미디어애널리틱스 스케쥴
Week01
ideas and concepts
Introduction to R and others
- Downloading and Installing R
- Starting R
- Entering Commands
- Exiting from R
- Interrupting R
- Viewing the Supplied Documentation
- Getting Help on a Function
- Searching the Supplied Documentation
- Getting Help on a Package
- Searching the Web for Help
- Finding Relevant Functions and Packages
- Searching the Mailing Lists
- Submitting Questions to the Mailing Lists
Assignment
Week02
Some basics
- Introduction
- Printing Something
- Setting Variables
- Listing Variables
- Deleting Variables
- Creating a Vector
- Computing Basic Statistics
- Creating Sequences
- Comparing Vectors
- Selecting Vector Elements
- Performing Vector Arithmetic
- Getting Operator Precedence Right
- Defining a Function
- Typing Less and Accomplishing More
- Avoiding Some Common Mistakes
using theories and making hypotheses
Week03
Navigating software
- Introduction
- Getting and Setting the Working Directory
- Saving Your Workspace
- Viewing Your Command History
- Saving the Result of the Previous Command
- Displaying the Search Path
- Accessing the Functions in a Package
- Accessing Built-in Datasets
- Viewing the List of Installed Packages
- Installing Packages from CRAN
- Setting a Default CRAN Mirror
- Suppressing the Startup Message
- Running a Script
- Running a Batch Script
- Getting and Setting Environment Variables
- Locating the R Home Directory
- Customizing R
Week04
Input and output
- Introduction
- Entering Data from the Keyboard
- Printing Fewer Digits (or More Digits)
- Redirecting Output to a File
- Listing Files
- Dealing with “Cannot Open File” in Windows
- Reading Fixed-Width Records
- Reading Tabular Data Files
- Reading from CSV Files
- Writing to CSV Files
- Reading Tabular or CSV Data from the Web
- Reading Data from HTML Tables
- Reading Files with a Complex Structure
- Reading from MySQL Databases
- Saving and Transporting Objects
Week05
Data Structures
- Introduction
- Appending Data to a Vector
- Inserting Data into a Vector
- Understanding the Recycling Rule
- Creating a Factor (Categorical Variable)
- Combining Multiple Vectors into One Vector and a Factor
- Creating a List
- Selecting List Elements by Position
- Selecting List Elements by Name
- Building a Name/Value Association List
- Removing an Element from a List
- Flatten a List into a Vector
- Removing NULL Elements from a List
- Removing List Elements Using a Condition
- Initializing a Matrix
- Performing Matrix Operations
- Giving Descriptive Names to the Rows and Columns of a Matrix
- Selecting One Row or Column from a Matrix
- Initializing a Data Frame from Column Data
- Initializing a Data Frame from Row Data
- Appending Rows to a Data Frame
- Preallocating a Data Frame
- Selecting Data Frame Columns by Position
- Selecting Data Frame Columns by Name
- Selecting Rows and Columns More Easily
- Changing the Names of Data Frame Columns
- Editing a Data Frame
- Removing NAs from a Data Frame
- Excluding Columns by Name
- Combining Two Data Frames
- Merging Data Frames by Common Column
- Accessing Data Frame Contents More Easily
- Converting One Atomic Value into Another
- Converting One Structured Data Type into Another
Week06
Data Transformations
- Introduction
- Splitting a Vector into Groups
- Applying a Function to Each List Element
- Applying a Function to Every Row
- Applying a Function to Every Column
- Applying a Function to Groups of Data
- Applying a Function to Groups of Rows
- Applying a Function to Parallel Vectors or Lists
Strings and Dates
Week07
Probability
- Introduction
- Counting the Number of Combinations
- Generating Combinations
- Generating Random Numbers
- Generating Reproducible Random Numbers
- Generating a Random Sample
- Generating Random Sequences
- Randomly Permuting a Vector
- Calculating Probabilities for Discrete Distributions
- Calculating Probabilities for Continuous Distributions
- Converting Probabilities to Quantiles
- Plotting a Density Function
Week08
Mid-term period
Week09
General Statistics
- Introduction
- Summarizing Your Data
- Calculating Relative Frequencies
- Tabulating Factors and Creating Contingency Tables
- Testing Categorical Variables for Independence
- Calculating Quantiles (and Quartiles) of a Dataset
- Inverting a Quantile
- Converting Data to Z-Scores
- Testing the Mean of a Sample (t Test)
- Forming a Confidence Interval for a Mean
- Forming a Confidence Interval for a Median
- Testing a Sample Proportion
- Forming a Confidence Interval for a Proportion
- Testing for Normality
- Testing for Runs
- Comparing the Means of Two Samples
- Comparing the Locations of Two Samples Nonparametrically
- Testing a Correlation for Significance
- Testing Groups for Equal Proportions
- Performing Pairwise Comparisons Between Group Means
- Testing Two Samples for the Same Distribution
Week10
General Statistics
Week11
Graphics
- Introduction
- Creating a Scatter Plot
- Adding a Title and Labels
- Adding a Grid
- Creating a Scatter Plot of Multiple Groups
- Adding a Legend
- Plotting the Regression Line of a Scatter Plot
- Plotting All Variables Against All Other Variables
- Creating One Scatter Plot for Each Factor Level
- Creating a Bar Chart
- Adding Confidence Intervals to a Bar Chart
- Coloring a Bar Chart
- Plotting a Line from x and y Points
- Changing the Type, Width, or Color of a Line
- Plotting Multiple Datasets
- Adding Vertical or Horizontal Lines
- Creating a Box Plot
- Creating One Box Plot for Each Factor Level
- Creating a Histogram
- Adding a Density Estimate to a Histogram
- Creating a Discrete Histogram
- Creating a Normal Quantile-Quantile (Q-Q) Plot
- Creating Other Quantile-Quantile Plots
- Plotting a Variable in Multiple Colors
- Graphing a Function
- Pausing Between Plots
- Displaying Several Figures on One Page
- Opening Additional Graphics Windows
- Writing Your Plot to a File
- Changing Graphical Parameters
Week12
Graphics
Week13
Linear Regression and ANOVA
- Introduction
- Performing Simple Linear Regression
- Performing Multiple Linear Regression
- Getting Regression Statistics
- Understanding the Regression Summary
- Performing Linear Regression Without an Intercept
- Performing Linear Regression with Interaction Terms
- Selecting the Best Regression Variables
- Regressing on a Subset of Your Data
- Using an Expression Inside a Regression Formula
- Regressing on a Polynomial
- Regressing on Transformed Data
- Finding the Best Power Transformation (Box?Cox Procedure)
- Forming Confidence Intervals for Regression Coefficients
- Plotting Regression Residuals
- Diagnosing a Linear Regression
- Identifying Influential Observations
- Testing Residuals for Autocorrelation (Durbin?Watson Test)
- Predicting New Values
- Forming Prediction Intervals
- Performing One-Way ANOVA
- Creating an Interaction Plot
- Finding Differences Between Means of Groups
- Performing Robust ANOVA (Kruskal?Wallis Test)
- Comparing Models by Using ANOVA
Week14
Linear Regression and ANOVA
Week15
Group Presentation
Week16
Group Presentation
Final-term
class_schedule_template.1472776140.txt.gz · Last modified: 2016/09/02 08:59 by hkimscil