Providing the basic collection of statistical procedures used by social scientists, A Gentle Introduction to Stata, Second Edition 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.
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Preface
Support Materials
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
Book by Acock Alan C
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