NetCourseNowTM 101: Introduction to Stata
- Content:
- The course is
designed to take smart, knowledgeable people and turn them into proficient
interactive users of Stata. The course covers not just the obvious such as
getting data into Stata, but also covers lots of detailed techniques and
tricks to make you a powerful Stata user.
- Prerequisites:
- Stata 9 or Stata 10, installed and working
- Knowledge of your computer
- Internet web browser, such as Netscape, Microsoft Internet Explorer, or
Mozilla, installed and working
- (Course is platform independent)
Price:
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$195
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Enroll in NCNow101
(group rates)
How is a NetCourseNow different from a regular NetCourse?
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What is a NetCourseNow?
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Course content
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
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
Enroll in NCNow101
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