Statistics with Stata (Updated for Version 9) is the latest edition in Professor Hamilton's popular Statistics with Stata series. Statistics with Stata is intended to bridge the gap between statistical texts and Stata's own documentation. This text is ideal both as a self-study course for those new to statistics or migrating from other statistical software to Stata and as a valuable reference for experienced Stata users wishing to explore Stata's capabilities in fields new to them.
Covered topics include getting started in Stata, data manipulation, graphics (chapter 3 on graphics is the largest in the text and consists of a wonderful example-oriented overview of Stata's graphics), summary statistics and tables, ANOVA, linear regression (and diagnostics), curve fitting, robust methods, regression models for limited dependent variables, panel (longitudinal) data, survival analysis, factor analysis, cluster analysis, time series, and an introduction to programming.

Although this edition is an excellent resource for learning and using Stata 9, owners of Statistics with Stata (Updated for Version 8) should note that this edition contains little new material.



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Table of contents
Preface
1 Stata and Stata Resources

A Typographical Note
An Example Stata Session
Stata's Documentation and Help Files
Searching for Information
Stata Corporation
Statalist
The Stata Journal
Books Using Stata
2 Data Management

Example Commands
Creating a New Dataset
Specifying Subsets of the Data: in and if Qualifiers
Generating and Replacing Variables
Using Functions
Converting between Numeric and String Formats
Creating New Categorical and Ordinal Variables
Using Explicit Subscripts with Variables
Importing Data from Other Programs
Combining Two or More Stata Files
Transposing, Reshaping, or Collapsing Data
Weighting Observations
Creating Random Data and Random Samples
Writing Programs for Data Management
Managing Memory
3 Graphs

Example Commands
Histograms
Scatterplots
Line Plots
Connected-Line Plots
Other Twoway Plot Types
Box Plots
Pie Charts
Bar Charts
Dot Plots
Symmetry and Quantile Plots
Quality Control Graphs
Adding Text to Graphs
Overlaying Multiple Twoway Plots
Graphing with Do-Files
Retrieving and Combining Graphs
4 Summary Statistics and Tables

Example Commands
Summary Statistics for Measurement Variables
Exploratory Data Analysis
Normality Tests and Transformations
Frequency Tables and Two-Way Cross-Tabulations
Multiple Tables and Multi-Way Cross-Tabulations
Tables of Means, Medians, and Other Summary Statistics
Using Frequency Weights
5 ANOVA and Other Comparison Methods

Example Commands
One-Sample Tests
Two-Sample Tests
One-Way Analysis of Variance (ANOVA)
Two- and N-Way Analysis of Variance
Analysis of Covariance (ANOCOVA)
Predicted Values and Error-Bar Charts
6 Linear Regression Analysis

Example Commands
The Regression Table
Multiple Regression
Predicted Values and Residuals
Basic Graphs for Regression
Correlations
Hypothesis Tests
Dummy Variables
Automatic Categorical-Variable Indicators and Interactions
Stepwise Regression
Polynomial Regression
Panel Data
7 Regression Diagnostics

Example Commands
SAT Score Regression, Revisited
Diagnostic Plots
Diagnostic Case Statistics
Multicollinearity
8 Fitting Curves

Example Commands
Band Regression
Lowess Smoothing
Regression with Transformed Variables 1
Regression with Transformed Variables 2
Conditional Effect Plots
Nonlinear Regression 1
Nonlinear Regression 2
9 Robust Regression

Example Commands
Regression with Ideal Data
Y Outliers
X Outliers (Leverage)
Asymmetrical Error Distributions
Robust Analysis of Variance
Further rreg and qreg Applications
Robust Estimates of Variance 1
Robust Estimates of Variance 2
10 Logistic Regression

Example Commands
Space Shuttle Data
Using Logistic Regression
Conditional Effect Plots
Diagnostic Statistics and Plots
Logistic Regression with Ordered-Category y
Multinomial Logistic Regression
11 Survival and Event-Count Models

Example Commands
Survival-Time Data
Count-Time Data
Kaplan Meier Survivor Functions
Cox Proportional Hazard Models
Exponential and Weibull Regression
Poisson Regression
Generalized Linear Models
12 Principal Components, Factor, and Cluster Analysis

Example Commands
Principal Components
Rotation
Factor Scores
Principal Factoring
Maximum-Likelihood Factoring
Cluster Analysis 1
Cluster Analysis 2
13 Time Series Analysis

Example Commands
Smoothing
Further Time Plot Examples
Lags, Leads, and Differences
Correlograms
ARIMA Models
14 Introduction to Programming

Basic Concepts and Tools
Example Program: Moving Autocorrelation
Ado-File
Help File
Matrix Algebra
Bootstrapping
Monte Carlo Simulation
References

Index