An Introduction to Statistics and Data Analysis Using Stata®

From Research Design to Final Report
Second Edition
Lisa Daniels - Washington College, USA
Nicholas W. Minot - International Food Policy Research Institute, Washington, DC
An Introduction to Statistics and Data Analysis Using Stata®
January 2025 | 384 pages | Sage US
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Description

An Introduction to Statistics and Data Analysis Using Stata®: From Research Design to Final Report, Second Edition provides an integrated approach to research methods, statistics and data analysis, and interpretation of results in Stata. Drawing on their combined 25 years of experience teaching statistics and research methods, authors Lisa Daniels and Nicholas Minot frame data analysis within the research process—identifying gaps in the literature, examining the theory, developing research questions, designing a questionnaire or using secondary data, analyzing the data, and writing a research paper—so readers better understand the context of data analysis. Throughout, the text focuses on documenting and communicating results so students can produce a finished report or article by the end of their courses.

The Second Edition has been thoroughly updated with all new articles and data—including coverage of ChatGPT, COVID-19 policies, and SAT scores—to demonstrate the relevance of data analysis for students. A new chapter on advanced methods in regression analysis allows instructors to better feature these important techniques. Stata code has been updated to the latest version, and new exercises throughout offer more chances for practice.

Contents

Preface

Preface

Acknowledgments

Acknowledgments

Part I • The Research Process And Data Collection

  • Chapter 1 • A Brief Overview of the Research Process
  • 1.1 Introduction
  • 1.2 What Is Research
  • 1.3 Steps In The Research Process
  • 1.4 Conclusion
  • Exercises
  • Chapter 2 • Sampling Techniques
  • 2.1 Introduction
  • 2.2 Sample Design
  • 2.3 Selecting A Sample
  • 2.4 Sampling Weights
  • Exercises
  • Chapter 3 • Questionnaire Design
  • 3.1 Introduction
  • 3.2 Types Of Questionnaires
  • 3.3 Guidelines For Questionnaire Design
  • 3.4 Recording Responses
  • 3.5 Skip Patterns
  • 3.6 Ethical Issues
  • Exercises

Part II • Describing Data

  • Chapter 4 • An Introduction to Stata
  • 4.1 Introduction
  • 4.2 Opening Stata And Stata Windows
  • 4.3 Working With Existing Data
  • 4.4 Setting Preferences In Stata
  • 4.5 Entering Your Own Data Into Stata
  • 4.6 Using Log Files And Saving Your Work
  • 4.7 Getting Help
  • 4.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 5 • Preparing and Transforming Your Data
  • 5.1 Introduction
  • 5.2 Checking For Outliers
  • 5.3 Creating New Variables
  • 5.4 Missing Values In Stata
  • 5.5 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 6 • Descriptive Statistics
  • 6.1 Introduction
  • 6.2 Types Of Variables And Measurement
  • 6.3 Descriptive Statistics For All Types Of Variables: Frequency Tables And Modes
  • 6.4 Descriptive Statistics For Variables Measured As Ordinal, Interval, And Ratio Scales: Median And Percentiles
  • 6.5 Descriptive Statistics For Continuous Variables: Mean, Variance, Standard Deviation, And Coefficient Of Variation
  • 6.6 Descriptive Statistics For Categorical Variables Measured On A Nominal Or Ordinal Scale: Cross Tabulation
  • 6.7 Applying Sampling Weights
  • 6.8 Formatting Output For Use In A Document (Word, Google Docs, Etc.)
  • 6.9 Graphs To Describe Data
  • 6.10 Summary Of Commands Used In This Chapter
  • Exercises

Part III • Testing Hypotheses

  • Chapter 7 • The Normal Distribution, Hypothesis Testing, and Statistical Significance
  • 7.1 Introduction
  • 7.2 The Normal Distribution And Standard Scores
  • 7.3 Sampling Distributions And Standard Errors
  • 7.4 Examining The Theory And Identifying The Research Question And Hypothesis
  • 7.5 Testing For Statistical Significance Between A Sample Mean And A Population Mean
  • 7.6 Rejecting Or Not Rejecting The Null Hypothesis
  • 7.7 Interpreting The Results
  • 7.8 Central Limit Theorem
  • 7.9 Presenting The Results
  • 7.10 Comparing A Sample Proportion To A Population Proportion
  • 7.11 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 8 • Testing a Hypothesis About a Single Mean and a Single Proportion
  • 8.1 Introduction
  • 8.2 When To Use The One-Sample t Test
  • 8.3 Calculating The One-Sample t Test
  • 8.4 Conducting A One-Sample t Test
  • 8.5 Interpreting The Output
  • 8.6 Presenting The Results
  • 8.7 Estimating A Population Proportion From A Sample Proportion
  • 8.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 9 • Testing a Hypothesis About Two Independent Means
  • 9.1 Introduction
  • 9.2 When To Use A Two Independentsamples t Test
  • 9.3 Calculating The t Statistic
  • 9.4 Conducting A t Test
  • 9.5 Interpreting The Output
  • 9.6 Presenting The Results
  • 9.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 10 • One-Way Analysis of Variance
  • 10.1 Introduction
  • 10.2 When To Use One-Way ANOVA
  • 10.3 Calculating The F Ratio
  • 10.4 Conducting A One-Way ANOVA Test
  • 10.5 Interpreting The Output
  • 10.6 Is One Mean Different or are all of Them Different?
  • 10.7 Presenting The Results
  • 10.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 11 • Comparing Categorical Variables – The Chi-Squared Test and Proportions
  • 11.1 Introduction
  • 11.2 When To Use The Chi-Squared Test
  • 11.3 Calculating The Chi-Square Statistic
  • 11.4 Conducting A Chi-Squared Test
  • 11.5 Interpreting The Output
  • 11.6 Presenting The Results
  • 11.7 Comparing Proportions Or Binary Categorical Variables
  • 11.8 Summary Of Commands Used In This Chapter
  • Exercises

Part IV • Exploring Relationships

  • Chapter 12 • Linear Regression Analysis
  • 12.1 Introduction
  • 12.2 When To Use Regression Analysis
  • 12.3 Correlation
  • 12.4 Simple Regression Analysis
  • 12.5 Multiple Regression Analysis
  • 12.6 Presenting The Results
  • 12.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 13 • Regression Diagnostics
  • 13.1 Introduction
  • 13.2 Measurement Error
  • 13.3 Specification Error
  • 13.4 Multicollinearity
  • 13.5 Heteroscedasticity
  • 13.6 Endogeneity
  • 13.7 Nonnormality
  • 13.8 Presenting The Results
  • 13.9 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 14 • Regression Analysis with Binary Dependent Variables
  • 14.1 Introduction
  • 14.2 When To Use Logit Or Probit Analysis
  • 14.3 Understanding The Logit Model
  • 14.4 Running A Logit Model
  • 14.5 Interpreting The Results Of A Logit Model
  • 14.6 Logit Versus Probit Regression Models
  • 14.7 Presenting The Results
  • 14.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 15 • Introduction to Advanced Topics in Regression Analysis
  • 15.1 Introduction
  • 15.2 Regression With A Categorical Dependent Variable
  • 15.3 Instrumental Variables Regression
  • 15.4 Regression With Time-Series Data
  • 15.5 Regression That Combines Cross-Section And Time-Series Data
  • 15.6 Summary Of Commands Used In This Chapter
  • Exercises

Part V • Writing A Research Paper

  • Chapter 16 • Writing a Research Paper
  • 16.1 Introduction
  • 16.2 Introduction Section Of A Research Paper
  • 16.3 Literature Review
  • 16.4 Theory, Data, And Methods
  • 16.5 Results
  • 16.6 Discussion
  • 16.7 Conclusions
  • Exercises

Appendices

Appendices

Appendix 1 • Quick Reference Guide to Stata Commands

Appendix 1 • Quick Reference Guide to Stata Commands

Appendix 2 • Summary of Statistical Tests by Chapter

Appendix 2 • Summary of Statistical Tests by Chapter

Appendix 3 • Decision Tree for Choosing the Right Statistic

Appendix 3 • Decision Tree for Choosing the Right Statistic

Appendix 4 • Decision Rules for Statistical Significance

Appendix 4 • Decision Rules for Statistical Significance

Appendix 5 • Areas Under the Normal Curve (Z Scores)

Appendix 5 • Areas Under the Normal Curve (Z Scores)

Appendix 6 • Critical Values of the t Distribution

Appendix 6 • Critical Values of the t Distribution

Appendix 7 • Stata Code for Random Sampling

Appendix 7 • Stata Code for Random Sampling

Appendix 8 • Examples of Nonlinear Functions

Appendix 8 • Examples of Nonlinear Functions

Appendix 9 • Estimating the Minimum Sample Size

Appendix 9 • Estimating the Minimum Sample Size

Appendix 10 Description of the Data Sets Used in the Textbook

Appendix 10 Description of the Data Sets Used in the Textbook

Glossary

Glossary

About the Authors

About the Authors

Index

Index

Additional materials

Description

An Introduction to Statistics and Data Analysis Using Stata®: From Research Design to Final Report, Second Edition provides an integrated approach to research methods, statistics and data analysis, and interpretation of results in Stata. Drawing on their combined 25 years of experience teaching statistics and research methods, authors Lisa Daniels and Nicholas Minot frame data analysis within the research process—identifying gaps in the literature, examining the theory, developing research questions, designing a questionnaire or using secondary data, analyzing the data, and writing a research paper—so readers better understand the context of data analysis. Throughout, the text focuses on documenting and communicating results so students can produce a finished report or article by the end of their courses.

The Second Edition has been thoroughly updated with all new articles and data—including coverage of ChatGPT, COVID-19 policies, and SAT scores—to demonstrate the relevance of data analysis for students. A new chapter on advanced methods in regression analysis allows instructors to better feature these important techniques. Stata code has been updated to the latest version, and new exercises throughout offer more chances for practice.

Contents

Preface

Preface

Acknowledgments

Acknowledgments

Part I • The Research Process And Data Collection

  • Chapter 1 • A Brief Overview of the Research Process
  • 1.1 Introduction
  • 1.2 What Is Research
  • 1.3 Steps In The Research Process
  • 1.4 Conclusion
  • Exercises
  • Chapter 2 • Sampling Techniques
  • 2.1 Introduction
  • 2.2 Sample Design
  • 2.3 Selecting A Sample
  • 2.4 Sampling Weights
  • Exercises
  • Chapter 3 • Questionnaire Design
  • 3.1 Introduction
  • 3.2 Types Of Questionnaires
  • 3.3 Guidelines For Questionnaire Design
  • 3.4 Recording Responses
  • 3.5 Skip Patterns
  • 3.6 Ethical Issues
  • Exercises

Part II • Describing Data

  • Chapter 4 • An Introduction to Stata
  • 4.1 Introduction
  • 4.2 Opening Stata And Stata Windows
  • 4.3 Working With Existing Data
  • 4.4 Setting Preferences In Stata
  • 4.5 Entering Your Own Data Into Stata
  • 4.6 Using Log Files And Saving Your Work
  • 4.7 Getting Help
  • 4.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 5 • Preparing and Transforming Your Data
  • 5.1 Introduction
  • 5.2 Checking For Outliers
  • 5.3 Creating New Variables
  • 5.4 Missing Values In Stata
  • 5.5 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 6 • Descriptive Statistics
  • 6.1 Introduction
  • 6.2 Types Of Variables And Measurement
  • 6.3 Descriptive Statistics For All Types Of Variables: Frequency Tables And Modes
  • 6.4 Descriptive Statistics For Variables Measured As Ordinal, Interval, And Ratio Scales: Median And Percentiles
  • 6.5 Descriptive Statistics For Continuous Variables: Mean, Variance, Standard Deviation, And Coefficient Of Variation
  • 6.6 Descriptive Statistics For Categorical Variables Measured On A Nominal Or Ordinal Scale: Cross Tabulation
  • 6.7 Applying Sampling Weights
  • 6.8 Formatting Output For Use In A Document (Word, Google Docs, Etc.)
  • 6.9 Graphs To Describe Data
  • 6.10 Summary Of Commands Used In This Chapter
  • Exercises

Part III • Testing Hypotheses

  • Chapter 7 • The Normal Distribution, Hypothesis Testing, and Statistical Significance
  • 7.1 Introduction
  • 7.2 The Normal Distribution And Standard Scores
  • 7.3 Sampling Distributions And Standard Errors
  • 7.4 Examining The Theory And Identifying The Research Question And Hypothesis
  • 7.5 Testing For Statistical Significance Between A Sample Mean And A Population Mean
  • 7.6 Rejecting Or Not Rejecting The Null Hypothesis
  • 7.7 Interpreting The Results
  • 7.8 Central Limit Theorem
  • 7.9 Presenting The Results
  • 7.10 Comparing A Sample Proportion To A Population Proportion
  • 7.11 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 8 • Testing a Hypothesis About a Single Mean and a Single Proportion
  • 8.1 Introduction
  • 8.2 When To Use The One-Sample t Test
  • 8.3 Calculating The One-Sample t Test
  • 8.4 Conducting A One-Sample t Test
  • 8.5 Interpreting The Output
  • 8.6 Presenting The Results
  • 8.7 Estimating A Population Proportion From A Sample Proportion
  • 8.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 9 • Testing a Hypothesis About Two Independent Means
  • 9.1 Introduction
  • 9.2 When To Use A Two Independentsamples t Test
  • 9.3 Calculating The t Statistic
  • 9.4 Conducting A t Test
  • 9.5 Interpreting The Output
  • 9.6 Presenting The Results
  • 9.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 10 • One-Way Analysis of Variance
  • 10.1 Introduction
  • 10.2 When To Use One-Way ANOVA
  • 10.3 Calculating The F Ratio
  • 10.4 Conducting A One-Way ANOVA Test
  • 10.5 Interpreting The Output
  • 10.6 Is One Mean Different or are all of Them Different?
  • 10.7 Presenting The Results
  • 10.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 11 • Comparing Categorical Variables – The Chi-Squared Test and Proportions
  • 11.1 Introduction
  • 11.2 When To Use The Chi-Squared Test
  • 11.3 Calculating The Chi-Square Statistic
  • 11.4 Conducting A Chi-Squared Test
  • 11.5 Interpreting The Output
  • 11.6 Presenting The Results
  • 11.7 Comparing Proportions Or Binary Categorical Variables
  • 11.8 Summary Of Commands Used In This Chapter
  • Exercises

Part IV • Exploring Relationships

  • Chapter 12 • Linear Regression Analysis
  • 12.1 Introduction
  • 12.2 When To Use Regression Analysis
  • 12.3 Correlation
  • 12.4 Simple Regression Analysis
  • 12.5 Multiple Regression Analysis
  • 12.6 Presenting The Results
  • 12.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 13 • Regression Diagnostics
  • 13.1 Introduction
  • 13.2 Measurement Error
  • 13.3 Specification Error
  • 13.4 Multicollinearity
  • 13.5 Heteroscedasticity
  • 13.6 Endogeneity
  • 13.7 Nonnormality
  • 13.8 Presenting The Results
  • 13.9 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 14 • Regression Analysis with Binary Dependent Variables
  • 14.1 Introduction
  • 14.2 When To Use Logit Or Probit Analysis
  • 14.3 Understanding The Logit Model
  • 14.4 Running A Logit Model
  • 14.5 Interpreting The Results Of A Logit Model
  • 14.6 Logit Versus Probit Regression Models
  • 14.7 Presenting The Results
  • 14.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 15 • Introduction to Advanced Topics in Regression Analysis
  • 15.1 Introduction
  • 15.2 Regression With A Categorical Dependent Variable
  • 15.3 Instrumental Variables Regression
  • 15.4 Regression With Time-Series Data
  • 15.5 Regression That Combines Cross-Section And Time-Series Data
  • 15.6 Summary Of Commands Used In This Chapter
  • Exercises

Part V • Writing A Research Paper

  • Chapter 16 • Writing a Research Paper
  • 16.1 Introduction
  • 16.2 Introduction Section Of A Research Paper
  • 16.3 Literature Review
  • 16.4 Theory, Data, And Methods
  • 16.5 Results
  • 16.6 Discussion
  • 16.7 Conclusions
  • Exercises

Appendices

Appendices

Appendix 1 • Quick Reference Guide to Stata Commands

Appendix 1 • Quick Reference Guide to Stata Commands

Appendix 2 • Summary of Statistical Tests by Chapter

Appendix 2 • Summary of Statistical Tests by Chapter

Appendix 3 • Decision Tree for Choosing the Right Statistic

Appendix 3 • Decision Tree for Choosing the Right Statistic

Appendix 4 • Decision Rules for Statistical Significance

Appendix 4 • Decision Rules for Statistical Significance

Appendix 5 • Areas Under the Normal Curve (Z Scores)

Appendix 5 • Areas Under the Normal Curve (Z Scores)

Appendix 6 • Critical Values of the t Distribution

Appendix 6 • Critical Values of the t Distribution

Appendix 7 • Stata Code for Random Sampling

Appendix 7 • Stata Code for Random Sampling

Appendix 8 • Examples of Nonlinear Functions

Appendix 8 • Examples of Nonlinear Functions

Appendix 9 • Estimating the Minimum Sample Size

Appendix 9 • Estimating the Minimum Sample Size

Appendix 10 Description of the Data Sets Used in the Textbook

Appendix 10 Description of the Data Sets Used in the Textbook

Glossary

Glossary

About the Authors

About the Authors

Index

Index

Additional materials

SAGE Publishing Logo

An Introduction to Statistics and Data Analysis Using Stata®

From Research Design to Final Report

Lisa Daniels , Nicholas W. Minot
Cancel Print

January 2025 | 384 pages | Sage US

Format Published Date ISBN Price

An Introduction to Statistics and Data Analysis Using Stata®: From Research Design to Final Report, Second Edition provides an integrated approach to research methods, statistics and data analysis, and interpretation of results in Stata. Drawing on their combined 25 years of experience teaching statistics and research methods, authors Lisa Daniels and Nicholas Minot frame data analysis within the research process—identifying gaps in the literature, examining the theory, developing research questions, designing a questionnaire or using secondary data, analyzing the data, and writing a research paper—so readers better understand the context of data analysis. Throughout, the text focuses on documenting and communicating results so students can produce a finished report or article by the end of their courses.

The Second Edition has been thoroughly updated with all new articles and data—including coverage of ChatGPT, COVID-19 policies, and SAT scores—to demonstrate the relevance of data analysis for students. A new chapter on advanced methods in regression analysis allows instructors to better feature these important techniques. Stata code has been updated to the latest version, and new exercises throughout offer more chances for practice.


Table Of Contents:

  • Preface
  • Acknowledgments
  • Part I • The Research Process And Data Collection
  • Chapter 1 • A Brief Overview of the Research Process
  • 1.1 Introduction
  • 1.2 What Is Research
  • 1.3 Steps In The Research Process
  • 1.4 Conclusion
  • Exercises
  • Chapter 2 • Sampling Techniques
  • 2.1 Introduction
  • 2.2 Sample Design
  • 2.3 Selecting A Sample
  • 2.4 Sampling Weights
  • Exercises
  • Chapter 3 • Questionnaire Design
  • 3.1 Introduction
  • 3.2 Types Of Questionnaires
  • 3.3 Guidelines For Questionnaire Design
  • 3.4 Recording Responses
  • 3.5 Skip Patterns
  • 3.6 Ethical Issues
  • Exercises
  • Part II • Describing Data
  • Chapter 4 • An Introduction to Stata
  • 4.1 Introduction
  • 4.2 Opening Stata And Stata Windows
  • 4.3 Working With Existing Data
  • 4.4 Setting Preferences In Stata
  • 4.5 Entering Your Own Data Into Stata
  • 4.6 Using Log Files And Saving Your Work
  • 4.7 Getting Help
  • 4.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 5 • Preparing and Transforming Your Data
  • 5.1 Introduction
  • 5.2 Checking For Outliers
  • 5.3 Creating New Variables
  • 5.4 Missing Values In Stata
  • 5.5 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 6 • Descriptive Statistics
  • 6.1 Introduction
  • 6.2 Types Of Variables And Measurement
  • 6.3 Descriptive Statistics For All Types Of Variables: Frequency Tables And Modes
  • 6.4 Descriptive Statistics For Variables Measured As Ordinal, Interval, And Ratio Scales: Median And Percentiles
  • 6.5 Descriptive Statistics For Continuous Variables: Mean, Variance, Standard Deviation, And Coefficient Of Variation
  • 6.6 Descriptive Statistics For Categorical Variables Measured On A Nominal Or Ordinal Scale: Cross Tabulation
  • 6.7 Applying Sampling Weights
  • 6.8 Formatting Output For Use In A Document (Word, Google Docs, Etc.)
  • 6.9 Graphs To Describe Data
  • 6.10 Summary Of Commands Used In This Chapter
  • Exercises
  • Part III • Testing Hypotheses
  • Chapter 7 • The Normal Distribution, Hypothesis Testing, and Statistical Significance
  • 7.1 Introduction
  • 7.2 The Normal Distribution And Standard Scores
  • 7.3 Sampling Distributions And Standard Errors
  • 7.4 Examining The Theory And Identifying The Research Question And Hypothesis
  • 7.5 Testing For Statistical Significance Between A Sample Mean And A Population Mean
  • 7.6 Rejecting Or Not Rejecting The Null Hypothesis
  • 7.7 Interpreting The Results
  • 7.8 Central Limit Theorem
  • 7.9 Presenting The Results
  • 7.10 Comparing A Sample Proportion To A Population Proportion
  • 7.11 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 8 • Testing a Hypothesis About a Single Mean and a Single Proportion
  • 8.1 Introduction
  • 8.2 When To Use The One-Sample t Test
  • 8.3 Calculating The One-Sample t Test
  • 8.4 Conducting A One-Sample t Test
  • 8.5 Interpreting The Output
  • 8.6 Presenting The Results
  • 8.7 Estimating A Population Proportion From A Sample Proportion
  • 8.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 9 • Testing a Hypothesis About Two Independent Means
  • 9.1 Introduction
  • 9.2 When To Use A Two Independentsamples t Test
  • 9.3 Calculating The t Statistic
  • 9.4 Conducting A t Test
  • 9.5 Interpreting The Output
  • 9.6 Presenting The Results
  • 9.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 10 • One-Way Analysis of Variance
  • 10.1 Introduction
  • 10.2 When To Use One-Way ANOVA
  • 10.3 Calculating The F Ratio
  • 10.4 Conducting A One-Way ANOVA Test
  • 10.5 Interpreting The Output
  • 10.6 Is One Mean Different or are all of Them Different?
  • 10.7 Presenting The Results
  • 10.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 11 • Comparing Categorical Variables – The Chi-Squared Test and Proportions
  • 11.1 Introduction
  • 11.2 When To Use The Chi-Squared Test
  • 11.3 Calculating The Chi-Square Statistic
  • 11.4 Conducting A Chi-Squared Test
  • 11.5 Interpreting The Output
  • 11.6 Presenting The Results
  • 11.7 Comparing Proportions Or Binary Categorical Variables
  • 11.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Part IV • Exploring Relationships
  • Chapter 12 • Linear Regression Analysis
  • 12.1 Introduction
  • 12.2 When To Use Regression Analysis
  • 12.3 Correlation
  • 12.4 Simple Regression Analysis
  • 12.5 Multiple Regression Analysis
  • 12.6 Presenting The Results
  • 12.7 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 13 • Regression Diagnostics
  • 13.1 Introduction
  • 13.2 Measurement Error
  • 13.3 Specification Error
  • 13.4 Multicollinearity
  • 13.5 Heteroscedasticity
  • 13.6 Endogeneity
  • 13.7 Nonnormality
  • 13.8 Presenting The Results
  • 13.9 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 14 • Regression Analysis with Binary Dependent Variables
  • 14.1 Introduction
  • 14.2 When To Use Logit Or Probit Analysis
  • 14.3 Understanding The Logit Model
  • 14.4 Running A Logit Model
  • 14.5 Interpreting The Results Of A Logit Model
  • 14.6 Logit Versus Probit Regression Models
  • 14.7 Presenting The Results
  • 14.8 Summary Of Commands Used In This Chapter
  • Exercises
  • Chapter 15 • Introduction to Advanced Topics in Regression Analysis
  • 15.1 Introduction
  • 15.2 Regression With A Categorical Dependent Variable
  • 15.3 Instrumental Variables Regression
  • 15.4 Regression With Time-Series Data
  • 15.5 Regression That Combines Cross-Section And Time-Series Data
  • 15.6 Summary Of Commands Used In This Chapter
  • Exercises
  • Part V • Writing A Research Paper
  • Chapter 16 • Writing a Research Paper
  • 16.1 Introduction
  • 16.2 Introduction Section Of A Research Paper
  • 16.3 Literature Review
  • 16.4 Theory, Data, And Methods
  • 16.5 Results
  • 16.6 Discussion
  • 16.7 Conclusions
  • Exercises
  • Appendices
  • Appendix 1 • Quick Reference Guide to Stata Commands
  • Appendix 2 • Summary of Statistical Tests by Chapter
  • Appendix 3 • Decision Tree for Choosing the Right Statistic
  • Appendix 4 • Decision Rules for Statistical Significance
  • Appendix 5 • Areas Under the Normal Curve (Z Scores)
  • Appendix 6 • Critical Values of the t Distribution
  • Appendix 7 • Stata Code for Random Sampling
  • Appendix 8 • Examples of Nonlinear Functions
  • Appendix 9 • Estimating the Minimum Sample Size
  • Appendix 10 Description of the Data Sets Used in the Textbook
  • Glossary
  • About the Authors
  • Index

Recent Product Reviews:

The book by Daniels and Minot helps students understand how to conduct empirical research. The authors' concise and straightforward approach makes complicated topics easy to grasp, while their emphasis on a hands-on experience approach utilizing Stata further enhances the practicality of the material.
Hector H. Sandoval, University of Florida
An Introduction to Statistics and Data Analysis is a perfect example of a text that helps students learn how to use Stata and interpret statistical output! I often tell students that 'real' statisticians do not use paper and pencil or a graphing calculator to crunch numbers. We use Stata and this book integrates Stata into the learning process.
Michael Danza, Copper Mountain College
This textbook is a valuable resource for teaching students the basics of quantitative analysis with Stata. Its clear writing style ensures content accessibility. The simple explanations and practical examples maintain student engagement. Additionally, the book seamlessly integrates theoretical concepts with real-world applications, enhancing understanding and fostering critical thinking skills.
Nurgul R. Aitalieva, Purdue University, Fort Wayne.
This is a great book for an undergraduate student population just getting into quantitative methods and Stata.
Jill Weinberg, Tufts University
The writing is very clear and accessible, yet the statistical coverage is thorough enough for graduate students. The examples of how to use commands and how to interpret output are great references for students after they finish the course.
Janet P. Stamatel, University of Kentucky

Recommendations