A Gentle Introduction to Stata

Published:
December 15, 2005 by Stata Press - 290 Pages
Author(s):
Alan C. Acock, Oregon State University, Corvallis, USA; Alan C. Acock, Oregon State University, Corvallis, USA

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ISBN 9781597180092
Cat# SZ0092
 

Features

  • Provides the basic tools to learn Stata, both for experienced statisticians and less knowledgeable readers
  • Covers descriptive statistics, graphs, charts, correlation, variance analysis, and multiple and logistic regression
  • Interprets statistical procedures from a t test, nonparametric tests, and ANOVA
  • Illustrates the Stata dialog system, particularly when using the system with graphs
  • Explores over 1,000 observations of data including many real-world examples, such as the General Social Survey and National Survey of Youth
  • Offers guidelines for advanced topics and future Stata work

    • Summary

    Providing the basic collection of statistical procedures used by social scientists, A Gentle Introduction to Stata presents the fundamental tools to learn Stata. The book begins with showing how to enter and manage data as well as perform basic descriptive statistics and graphical analysis. It then examines standard statistical procedures from a t test, nonparametric tests, measures of association, multiple regression, and logical regression. The book ends with guidelines for future work and advanced topics. This learning source is an excellent introduction for those with little statistical software experience while also a useful reference for more knowledgeable statisticians by offering a detailed index of commands.

    Table of Contents

    Preface
    Support Materials for the Book
    GETTING STARTED
    Introduction
    The Stata screen
    Using an existing dataset
    An example of a short Stata session
    Conventions
    Chapter summary
    Exercises
    ENTERING DATA
    Creating a dataset
    An example questionnaire
    Develop a coding system
    Entering data
    Saving your dataset
    Checking the data
    Chapter summary
    Exercises
    PREPARING DATA FOR ANALYSIS
    Introduction
    Plan your work
    Create value labels
    Reverse-code variables
    Create and modify variables
    Create scales
    Save some of your data
    Summary
    Exercises
    WORKING WITH COMMANDS, DO-FILES, AND RESULTS
    Introduction
    How Stata commands are constructed
    Getting the command from the menu system
    Saving your results
    Logging your command file
    Summary
    Exercises
    DESCRIPTIVE STATISTICS AND GRAPHS FOR A SINGLE VARIABLE
    Descriptive statistics and graphs
    Where is the center of a distribution?
    How dispersed is the distribution?
    Statistics and graphs-unordered categories
    Statistics and graphs-ordered categories and variables
    Statistics and graphs-quantitative variables
    Summary
    Exercises
    STATISTICS AND GRAPHS FOR TWO CATEGORICAL VARIABLES
    Relationship between categorical variables
    Cross-tabulation
    Chi-squared
    Percentages and measures of association
    Ordered categorical variables
    Interactive tables
    Tables-linking categorical and quantitative variables
    Summary
    Exercises
    TESTS FOR ONE OR TWO MEANS
    Tests for one or two means
    Randomization
    Hypotheses
    One-sample test of a proportion
    Two-sample test of a proportion
    One-sample test of means
    Two-sample test of group means
    Repeated-measures t test
    Power analysis
    Nonparametric alternatives
    Summary
    Exercises
    BIVARIATE CORRELATION AND REGRESSION
    Introduction to bivariate correlation and regression
    Scattergrams
    Plotting the regression line
    Correlation
    Regression
    Spearman's rho: rank-order correlation for ordinal data
    Alpha reliability
    Kappa as a measure of agreement for categorical data
    Summary
    Exercises
    ANALYSIS OF VARIANCE (ANOVA)
    The logic of one-way analysis of variance
    ANOVA example
    ANOVA example using survey data
    A nonparametric alternative to ANOVA
    Analysis of covariance
    Two-way ANOVA
    Repeated-measures design
    Intraclass correlation-measuring agreement
    Summary
    Exercises
    MULTIPLE REGRESSION
    Introduction
    What is multiple regression?
    The basic multiple regression command
    Increment in R-squared: semipartial correlations
    Is the dependent variable normally distributed?
    Are the residuals normally distributed?
    Regression diagnostic statistics
    Weighted data
    Categorical predictors and hierarchical regression
    Fundamentals of interaction
    Summary
    Exercises
    LOGISTIC REGRESSION
    Introduction
    An example
    What are an odds ratio and a logit?
    Data used in rest of chapter
    Logistic regression
    Hypothesis testing
    Nested logistic regressions
    Summary
    Exercises
    WHAT'S NEXT?
    Introduction
    Resources
    Summary
    References
    Author Index
    Subject Index

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