A Gentle Introduction to Stata

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