An Introduction to Statistics and Data Analysis Using Stata (R) 2/e

Lisa Daniels is the Hodson Trust Professor Emeritus of Economics at Washington College in Chestertown, Maryland. She specializes in development in Africa, where she worked for 10 years, beginning as a Peace Corps volunteer. During her time in Africa, she studied agricultural markets, market information systems, poverty trends, and micro- and small-scale enterprises. As part of her research on micro- and small-scale enterprises, she directed national surveys of 7,000 to 56,000 households and businesses in Bangladesh, Botswana, Kenya, Malawi, and Zimbabwe funded by the U.S. Agency for International Development. In each survey, she was responsible for the questionnaire design, sample selection, data collection and analysis, and report preparation. Her work from these surveys and other research in Africa and Asia appears in consulting reports and in peer-reviewed journals. In addition to research and fieldwork, she has taught a range of courses over the past 28 years, including a research methods course and a data analysis course that she has taught over 20 times. She has also presented her work related to teaching at more than a dozen workshops. Nicholas Minot is a Senior Research Fellow at the International Food Policy Research Institute (IFPRI) in Washington, D.C. Since joining IFPRI in 1997, he has carried out research on agricultural market reform, income diversification, spatial patterns in policy, and food price volatility in developing countries. This research often involves carrying out surveys of farmers, cooperatives, traders, and consumers to better understand changes in food marketing systems. In addition to research, he is involved in outreach and capacity-building activities, including offering short courses on the use of Stata for survey data analysis. Before joining IFPRI, he taught at the University of Illinois in Urbana-Champaign, served as a policy adviser in Zimbabwe, and analyzed survey data in Rwanda. Overall, he has worked in more than two dozen countries in Latin America, sub-Saharan Africa, North Africa, and Asia.

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

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 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 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 This is a great book for an undergraduate student population just getting into quantitative methods and STATA. -- Jill Weinberg 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 This is by far among my favorite features of this book! I LOVE how you use applied examples as I endeavor to do this every week for them and have found some great examples within this work! It brings the fun world of data analysis right to them so they can see why it is important. I think the authors also did a great job on varying topics across social science disciplines, not neglecting hardly a one anywhere-no room for improvement and only wish more analysis books did featuring so well. -- Kara Sutton Takes the approach we do that you have to start with good research methods, assumes no prior stat knowledge, focuses on the foundational basics that students 'already know' but don't really understand (this is a big strength of the book!), and teaches those basics in conjunction with Stata coding. -- Chelsea Rae Kelly The second chapter offers a comprehensive guide on presenting students' research papers. It includes concrete examples illustrating each section of a research paper, making it particularly beneficial for students unfamiliar with this type of writing. Furthermore, the paper by Talan and Kalinkara (2023) on ChatGPT serves as a bridge between academic research and our daily lives. It highlights that academic knowledge, including what students learn from this book, is not separate from our everyday experiences. -- Jaeyun Sung