我花了两天的时间将论坛上提供的mobi格式的原版Statistics with STATA, Version 10, 7th Edition 转化为PDF格式；mobi格式的原版见：https://bbs.pinggu.org/forum.php?mod=viewthread&tid=1087829&page=1&from^^uid=300541

Statistics with Stata (Updated for Version 10)
Author: Lawrence C. Hamilton
Publisher: Cengage
Copyright: 2009
ISBN-13: 978-0-495-55786-9
Pages:  504; paperback
Price:  $74.00
Supplements: datasets and programs  
See a large photo of the front cover
Table of contents  
   
        

Comment from the Stata technical group
Statistics with Stata (Updated for Version 10) is the latest edition in Professor Lawrence C. Hamilton’s popular Statistics with Stata series. Intended to bridge the gap between statistical texts and Stata’s own documentation, Statistics with Stata demonstrates how to use Stata to perform a variety of tasks. This text is ideal as a self-study course for those new to statistics or those 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.
Hamilton covers topics including getting started in Stata, data manipulation, graphics, summary statistics and tables, ANOVA, linear regression (and diagnostics), curve fitting, robust methods, regression models for limited dependent variables, panel (longitudinal) data and mixed models, survey data, survival analysis, factor analysis, cluster analysis, time series, and an introduction to programming.
Notable changes to Statistics with Stata (Updated for Version 10) include a new chapter on survey data analysis using Stata’s svy: prefix command and a chapter on the multilevel and mixed model commands introduced in Stata 10. Chapter 3, covering graphics, has been updated to include a section demonstrating Stata’s Graph Editor. The entire book has also been updated to reflect changes in output, syntax, and features.

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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
StataCorp
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
Missing Value Codes
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
Using Weights
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
Adding Text to Graphs
Overlaying Multiple Twoway Plots
Graphing with Do-Files
Retrieving and Combining Graphs
Graph Editor
Creative Graphing
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 (ANCOVA)
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
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
ARMAX Models
14 Survey Data Analysis
Example Commands
Probability Weights
Poststratification Weights
Declare Survey Data
Survey-Weighted Tables and Graphs
Regression-Type Modeling
Conditional Effect Plots for Interactions
Other Tools for Survey Analysis
15 Multilevel and Mixed-Effects Modeling
Example Commands
Regression with Random Intercepts
Random Intercepts and Slopes
Multiple Random Slopes
Nested Levels
Cross-Sectional Time Series
Mixed-Effects Logit Regression
16 Introduction to Programming
Basic Concepts and Tools
Example Program: Moving Autocorrelation
Ado-File
Help File
Example Program: Plot Survey Variables
Monte Carlo Simulation
Matrix Programming with Mata
References
Index