Content:

An introduction to using Stata interactively.

Course Leaders:

James Hassell, Technical Services Representative at StataCorp.
Allen McDowell, Director of Technical Services at StataCorp.
Derek Wagner, Technical Services Representative at StataCorp.

Course Length:
6 weeks (4 lectures)

Dates:

21 January - 04 March 2005

Cost:

£ 57 + VAT

Prerequisites:

• Stata 8, installed and working.
  
• Knowledge of your computer.
  
• Internet web browser, such as Netscape, Microsoft Internet Explorer, or Mosaic, installed and working.
  
• Course is platform independent.

Lecture 1: Introduction

The basics

• Using directories to organize your work
  
• The current directory: a summary
  
• Overview of the course
  
• Dealing with files
  
• Filenames in Stata
  
• Loading the automobile data
  

The basics of Stata

• How Stata conceptualizes data
  
• Stata's command syntax
  
• The minimum set of commands everyone should know
  
• Working interactively: Getting organized
  
• Working interactively: Keeping logs
  
• Working interactively: Making Stata stop
  
• Installing Stata updates over the web
  
• search is your friend
  
• Installing new commands over the web: the STB
  
• Installing new commands over the web: other sources
  
• Installing new commands: Statalist
  

Lecture 2: Miscellaneous data management topics

• Describing your dataset
  
• Variable types
  
• Value labels
  
• Display formats
  
• Other kinds of labels
  
• Data reporting
  
• The by prefix
  
• Data manipulation
  
• Categorical variables
  
• Observation subscripts _n and _N
  
• Memory management
  

There is an one-week break between Lectures 2 and 3 in this course because we have found the extra time is necessary for discussion.

Lecture 3: Getting data into Stata

• The infile command
  
• Post-infile processing
  
• infile command with a data dictionary
  
• The insheet and outsheet commands
  
• A note on memory management
  
• Reading multiple lines per observation
  
• Reading multiple observations per line
  
• Reading omitted data
  
• Reading string data
  
• Reading dates
  
• Reading large integers
  

Lecture 4: Data management

• Appending data
  
• The roles of the master and using datasets
• Merging data
  One-to-one merge
  Match merge
  Assuring that identifiers are unique
  One-to-many and many-to-one merges (also known as spreads)
  Many-to-one merges (also known as mistakes)
  Updates
  
• Using append and merge
  
• Wide versus long data
  
• How to think about variables and their contents