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E-raamat: Introduction to Statistics and Data Analysis Using Stata(R): From Research Design to Final Report

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  • Ilmumisaeg: 11-Jan-2019
  • Kirjastus: SAGE Publications Inc
  • Keel: eng
  • ISBN-13: 9781506371849
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Introduction to Statistics and Data Analysis Using Stata(R): From Research Design to Final ReportSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 11-Jan-2019
  • Kirjastus: SAGE Publications Inc
  • Keel: eng
  • ISBN-13: 9781506371849
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Providing information from data preparation and mean, median and mode, to regression, Lisa Daniels and Nicholas Minot use concise descriptions to help students understand the concepts behind statistics rather than the derivations of the formulas. Examples within the text come from criminal justice, economics, political science, psychology, public health and sociology, in addition to news articles on social science research. The book also includes three introductory chapters on research and a final chapter for writing up results and presenting data analyses.

Offering a step-by-step introduction to data analysis in Stata, this text uses examples from a variety of disciplines and extensive detail on the commands in stata.

Arvustused

"This book introduces statistical methods to students while, at the same time, walking them through the process by which to apply those methods to real-world problems using Stata. This is something that is severely lacking in methods texts at this time." -- Steven P. Nawara "This is so far one of the best introductions to statistics and Stata that I have seen, particularly for my students who really need a bit of hand holding. This will likely make it less intimidating for students with no exposure to statistics." -- Holona LeAnne Ochs "I found the style of the book very sound for todays student. The style wasnt overly formal nor was the material presented in an overly complicated fashion. The author kept to a somewhat casual, approachable writing style that should be perfect for the modern college student." -- Wendy L. Hicks "This is a much needed book that encompasses research methods through to the analysis stage and reporting writing." -- Eileen M. Ahlin

Preface xiv
Acknowledgments xix
Part I The Research Process And Data Collection 1(40)
Chapter 1 The Research Process
2(8)
1.1 Introduction
3(1)
1.2 Read the Literature and Identify Gaps or Ways to Extend the Literature
4(2)
1.3 Examine the Theory
6(1)
1.4 Develop Your Research Questions and Hypotheses
6(1)
1.5 Develop Your Research Method
7(1)
1.6 Analyze the Data
8(1)
1.7 Write the Research Paper
8(1)
Exercises
8(1)
References
9(1)
Chapter 2 Sampling Techniques
10(15)
2.1 Introduction
11(1)
2.2 Sample Design
12(2)
2.3 Selecting a Sample
14(7)
2.3.1 Probability and Nonprobability Sampling
14(2)
2.3.2 Identifying a Sampling Frame
16(1)
2.3.3 Determining the Sample Size
17(1)
2.3.4 Sample Selection Methods
18(3)
2.4 Sampling Weights
21(2)
2.4.1 Calculating Sampling Weights
21(2)
2.4.2 Using Sampling Weights
23(1)
Exercises
23(1)
References
24(1)
Chapter 3 Questionnaire Design
25(16)
3.1 Introduction
26(1)
3.2 Structured and Semi-Structured Questionnaires
26(2)
3.3 Open- and Closed-Ended Questions
28(1)
3.4 General Guidelines for Questionnaire Design
28(2)
3.5 Designing the Questions
30(4)
3.5.1 Question Order
30(1)
3.5.2 Phrasing the Questions
31(3)
3.6 Recording Responses
34(2)
3.6.1 Responses in the Form of Continuous Variables
34(1)
3.6.2 Responses in the Form of Categorical Variables
35(1)
3.7 Skip Patterns
36(2)
3.8 Ethical Issues
38(1)
Exercises
39(1)
References
40(1)
Part II Describing Data 41(68)
Chapter 4 An Introduction to Stata
42(17)
4.1 Introduction
43(1)
4.2 Opening Stata and Stata Windows
43(2)
4.2.1 Results Window
44(1)
4.2.2 Review Window
44(1)
4.2.3 Command Window
44(1)
4.2.4 Variables Window
45(1)
4.2.5 Properties Window
45(1)
4.3 Working With Existing Data
45(3)
4.4 Entering Your Own Data Into Stata
48(3)
4.5 Using Log Files and Saving Your Work
51(3)
4.6 Getting Help
54(1)
4.6.1 Help Command
54(1)
4.6.2 Search Command
54(1)
4.6.3 Stata Website
54(1)
4.6.4 UCLA's Institute for Digital Research and Education Website
55(1)
4.7 Summary of Commands Used in This
Chapter
55(1)
Exercises
56(3)
Chapter 5 Preparing and Transforming Your Data
59(15)
5.1 Introduction
59(1)
5.2 Checking for Outliers
60(3)
5.3 Creating New Variables
63(6)
5.3.1 Generate
63(1)
5.3.2 Using Operators
64(1)
5.3.3 Recode
64(3)
5.3.4 Egen
67(2)
5.4 Missing Values in Stata
69(1)
5.5 Summary of Commands Used in This
Chapter
69(2)
Exercises
71(2)
References
73(1)
Chapter 6 Descriptive Statistics
74(35)
6.1 Introduction
75(1)
6.2 Types of Variables and Measurement
75(2)
6.3 Descriptive Statistics for All Types of Variables: Frequency Tables and Modes
77(4)
6.3.1 Frequency Tables
77(3)
6.3.2 Mode
80(1)
6.4 Descriptive Statistics for Variables Measured as Ordinal, Interval, and Ratio Scales: Median and Percentiles
81(2)
6.4.1 Median
81(1)
6.4.2 Percentiles
82(1)
6.5 Descriptive Statistics for Continuous Variables: Mean, Variance, Standard Deviation, and Coefficient of Variation
83(8)
6.5.1 Mean
84(3)
6.5.2 Variance and Standard Deviation
87(1)
6.5.3 Coefficient of Variation
88(3)
6.6 Descriptive Statistics for Categorical Variables Measured on a Nominal or Ordinal Scale: Cross Tabulation
91(3)
6.7 Applying Sampling Weights
94(2)
6.8 Formatting Output for Use in a Document (Word, Google Docs, etc.)
96(1)
6.9 Graphs to describe data
96(8)
6.9.1 Bar Graphs
96(1)
6.9.2 Box Plots
96(4)
6.9.3 Histograms
100(1)
6.9.4 Pie Charts
101(3)
6.10 Summary of Commands Used in This
Chapter
104(1)
Exercises
105(2)
References
107(2)
Part III Testing Hypotheses 109(76)
Chapter 7 The Normal Distribution
110(21)
7.1 Introduction
111(1)
7.2 The Normal Distribution and Standard Scores
112(7)
7.3 Sampling Distributions and Standard Errors
119(2)
7.4 Examining the Theory and Identifying the Research Question and Hypothesis
121(1)
7.5 Testing for Statistical Significance
122(2)
7.6 Rejecting or Not Rejecting the Null Hypothesis
124(1)
7.7 Interpreting the Results
125(1)
7.8 Central Limit Theorem
125(2)
7.9 Presenting the Results
127(1)
7.10 Summary of Commands Used in This
Chapter
128(1)
Exercises
128(2)
References
130(1)
Chapter 8 Testing a Hypothesis About a Single Mean
131(11)
8.1 Introduction
132(1)
8.2 When to Use the One-Sample t Test
133(2)
8.3 Calculating the One-Sample t Test
135(2)
8.4 Conducting a One-Sample t Test
137(1)
8.5 Interpreting the Output
138(2)
8.6 Presenting the Results
140(1)
8.7 Summary of Commands Used in This
Chapter
140(1)
Exercises
141(1)
References
141(1)
Chapter 9 Testing a Hypothesis About Two Independent Means
142(15)
9.1 Introduction
143(1)
9.2 When to Use a Two Independent-Samples t Test
144(2)
9.3 Calculating the t Statistic
146(1)
9.4 Conducting a t Test
146(5)
9.5 Interpreting the Output
151(2)
9.6 Presenting the Results
153(1)
9.7 Summary of Commands Used in This
Chapter
154(1)
Exercises
154(2)
References
156(1)
Chapter 10 One-Way Analysis of Variance
157(15)
10.1 Introduction
158(1)
10.2 When to Use One-Way ANOVA
159(1)
10.3 Calculating the F Ratio
160(2)
10.4 Conducting a One-Way ANOVA Test
162(3)
10.5 Interpreting the Output
165(1)
10.6 Is One Mean Different or Are All of Them Different?
166(1)
10.7 Presenting the Results
167(1)
10.8 Summary of Commands Used in This
Chapter
168(1)
Exercises
169(2)
References
171(1)
Chapter 11 Cross Tabulation and the Chi-Squared Test
172(13)
11.1 Introduction
173(1)
11.2 When to Use the Chi-Squared Test
174(1)
11.3 Calculating the Chi-Square Statistic
175(2)
11.4 Conducting a Chi-Squared Test
177(2)
11.5 Interpreting the Output
179(2)
11.6 Presenting the Results
181(1)
11.7 Summary of Commands Used in This
Chapter
182(1)
Exercises
182(1)
References
183(2)
Part IV Exploring Relationships 185(98)
Chapter 12 Linear Regression Analysis
186(31)
12.1 Introduction
187(1)
12.2 When to Use Regression Analysis
188(2)
12.3 Correlation
190(5)
12.4 Simple Regression Analysis
195(7)
12.5 Multiple Regression Analysis
202(9)
12.6 Presenting the Results
211(2)
12.7 Summary of Commands Used in This
Chapter
213(1)
Exercises
214(2)
References
216(1)
Chapter 13 Regression Diagnostics
217(36)
13.1 Introduction
218(1)
13.2 Measurement Error
219(5)
13.3 Specification Error
224(11)
13.3.1 Types of Specification Errors
225(2)
13.3.2 Diagnosing Specification Error
227(2)
13.3.3 Correcting Specification Error
229(6)
13.4 Multicollinearity
235(3)
13.5 Heteroscedasticity
238(4)
13.6 Endogeneity
242(2)
13.7 Nonnormality
244(5)
13.8 Presenting the Results
249(1)
13.9 Summary of Commands Used in This
Chapter
250(2)
References
252(1)
Chapter 14 Regression Analysis With Categorical Dependent Variables
253(30)
14.1 Introduction
254(2)
14.2 When to Use Logit or Probit Analysis
256(2)
14.3 Understanding the Logit Model
258(3)
14.4 Running Logit and Interpreting the Results
261(9)
14.4.1 Running Logit Regression in Stata
261(4)
14.4.2 Interpreting the Results of a Logit Model
265(5)
14.5 Logit Versus Probit Regression Models
270(2)
14.6 Regression Analysis With Other Types of Categorical Dependent Variables
272(2)
14.7 Presenting the Results
274(4)
14.8 Summary of Commands Used in This
Chapter
278(2)
Exercises
280(1)
References
281(2)
Part V Writing A Research Paper 283(20)
Chapter 15 Writing a Research Paper
284(19)
15.1 Introduction
285(1)
15.2 Introduction Section of a Research Paper
285(4)
15.3 Literature Review
289(3)
15.4 Theory, Data, and Methods
292(1)
15.5 Results
293(6)
15.5.1 Logical Sequence
294(1)
15.5.2 Tables, Figures, and Numbers
295(2)
15.5.3 Reporting Results From Statistical Tests
297(1)
15.5.4 Active Versus Passive Voice and the Use of First-Person Pronouns
298(1)
15.6 Discussion
299(1)
15.7 Conclusions
300(1)
Exercises
301(1)
References
301(2)
Appendices 303(51)
Appendix 1 Quick Reference Guide to Stata Commands
303(16)
Appendix 2 Summary of Statistical Tests by
Chapter
319(6)
Appendix 3 Decision Tree for Choosing the Right Statistic
325(1)
Appendix 4 Decision Rules for Statistical Significance
326(2)
Appendix 5 Areas Under the Normal Curve (ZScores)
328(2)
Appendix 6 Critical Values of the t Distribution
330(2)
Appendix 7 State Code for Random Sampling
332(6)
Appendix 8 Examples of Nonlinear Functions
338(12)
Appendix 9 Estimating the Minimum Sample Size
350(4)
Glossary 354(6)
About the Authors 360(1)
Name Index 361(2)
Subject Index 363
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 UrbanaChampaign, 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.
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