An Introduction to Statistics and Data Analysis Using Stata®

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.

• PrefaceAcknowledgmentsPart I • The Research Process And Data CollectionChapter 1 • A Brief Overview of the Research Process1.1 Introduction1.2 What Is Research1.3 Steps In The Research Process1.4 ConclusionExercisesChapter 2 • Sampling Techniques2.1 Introduction2.2 Sample Design2.3 Selecting A Sample2.4 Sampling WeightsExercisesChapter 3 • Questionnaire Design3.1 Introduction3.2 Types Of Questionnaires3.3 Guidelines For Questionnaire Design3.4 Recording Responses3.5 Skip Patterns3.6 Ethical IssuesExercisesPart II • Describing DataChapter 4 • An Introduction to Stata4.1 Introduction4.2 Opening Stata And Stata Windows4.3 Working With Existing Data4.4 Setting Preferences In Stata4.5 Entering Your Own Data Into Stata4.6 Using Log Files And Saving Your Work4.7 Getting Help4.8 Summary Of Commands Used In This ChapterExercisesChapter 5 • Preparing and Transforming Your Data5.1 Introduction5.2 Checking For Outliers5.3 Creating New Variables5.4 Missing Values In Stata5.5 Summary Of Commands Used In This ChapterExercisesChapter 6 • Descriptive Statistics6.1 Introduction6.2 Types Of Variables And Measurement6.3 Descriptive Statistics For All Types Of Variables: Frequency Tables And Modes6.4 Descriptive Statistics For Variables Measured As Ordinal, Interval, And Ratio Scales: Median And Percentiles6.5 Descriptive Statistics For Continuous Variables: Mean, Variance, Standard Deviation, And Coefficient Of Variation6.6 Descriptive Statistics For Categorical Variables Measured On A Nominal Or Ordinal Scale: Cross Tabulation6.7 Applying Sampling Weights6.8 Formatting Output For Use In A Document (Word, Google Docs, Etc.)6.9 Graphs To Describe Data6.10 Summary Of Commands Used In This ChapterExercisesPart III • Testing HypothesesChapter 7 • The Normal Distribution, Hypothesis Testing, and Statistical Significance7.1 Introduction7.2 The Normal Distribution And Standard Scores7.3 Sampling Distributions And Standard Errors7.4 Examining The Theory And Identifying The Research Question And Hypothesis7.5 Testing For Statistical Significance Between A Sample Mean And A Population Mean7.6 Rejecting Or Not Rejecting The Null Hypothesis7.7 Interpreting The Results7.8 Central Limit Theorem7.9 Presenting The Results7.10 Comparing A Sample Proportion To A Population Proportion7.11 Summary Of Commands Used In This ChapterExercisesChapter 8 • Testing a Hypothesis About a Single Mean and a Single Proportion8.1 Introduction8.2 When To Use The One-Sample t Test8.3 Calculating The One-Sample t Test8.4 Conducting A One-Sample t Test8.5 Interpreting The Output8.6 Presenting The Results8.7 Estimating A Population Proportion From A Sample Proportion8.8 Summary Of Commands Used In This ChapterExercisesChapter 9 • Testing a Hypothesis About Two Independent Means9.1 Introduction9.2 When To Use A Two Independentsamples t Test9.3 Calculating The t Statistic9.4 Conducting A t Test9.5 Interpreting The Output9.6 Presenting The Results9.7 Summary Of Commands Used In This ChapterExercisesChapter 10 • One-Way Analysis of Variance10.1 Introduction10.2 When To Use One-Way ANOVA10.3 Calculating The F Ratio10.4 Conducting A One-Way ANOVA Test10.5 Interpreting The Output10.6 Is One Mean Different or are all of Them Different?10.7 Presenting The Results10.8 Summary Of Commands Used In This ChapterExercisesChapter 11 • Comparing Categorical Variables – The Chi-Squared Test and Proportions11.1 Introduction11.2 When To Use The Chi-Squared Test11.3 Calculating The Chi-Square Statistic11.4 Conducting A Chi-Squared Test11.5 Interpreting The Output11.6 Presenting The Results11.7 Comparing Proportions Or Binary Categorical Variables11.8 Summary Of Commands Used In This ChapterExercisesPart IV • Exploring RelationshipsChapter 12 • Linear Regression Analysis12.1 Introduction12.2 When To Use Regression Analysis12.3 Correlation12.4 Simple Regression Analysis12.5 Multiple Regression Analysis12.6 Presenting The Results12.7 Summary Of Commands Used In This ChapterExercisesChapter 13 • Regression Diagnostics13.1 Introduction13.2 Measurement Error13.3 Specification Error13.4 Multicollinearity13.5 Heteroscedasticity13.6 Endogeneity13.7 Nonnormality13.8 Presenting The Results13.9 Summary Of Commands Used In This ChapterExercisesChapter 14 • Regression Analysis with Binary Dependent Variables14.1 Introduction14.2 When To Use Logit Or Probit Analysis14.3 Understanding The Logit Model14.4 Running A Logit Model14.5 Interpreting The Results Of A Logit Model14.6 Logit Versus Probit Regression Models14.7 Presenting The Results14.8 Summary Of Commands Used In This ChapterExercisesChapter 15 • Introduction to Advanced Topics in Regression Analysis15.1 Introduction15.2 Regression With A Categorical Dependent Variable15.3 Instrumental Variables Regression15.4 Regression With Time-Series Data15.5 Regression That Combines Cross-Section And Time-Series Data15.6 Summary Of Commands Used In This ChapterExercisesPart V • Writing A Research PaperChapter 16 • Writing a Research Paper16.1 Introduction16.2 Introduction Section Of A Research Paper16.3 Literature Review16.4 Theory, Data, And Methods16.5 Results16.6 Discussion16.7 ConclusionsExercisesAppendicesAppendix 1 • Quick Reference Guide to Stata CommandsAppendix 2 • Summary of Statistical Tests by ChapterAppendix 3 • Decision Tree for Choosing the Right StatisticAppendix 4 • Decision Rules for Statistical SignificanceAppendix 5 • Areas Under the Normal Curve (Z Scores)Appendix 6 • Critical Values of the t DistributionAppendix 7 • Stata Code for Random SamplingAppendix 8 • Examples of Nonlinear FunctionsAppendix 9 • Estimating the Minimum Sample SizeAppendix 10 Description of the Data Sets Used in the TextbookGlossaryAbout the AuthorsIndex

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.