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Statistics for Social Understanding: With Stata and SPSS [Minkštas viršelis]

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  • Formatas: Paperback / softback, 696 pages, aukštis x plotis x storis: 257x206x26 mm, weight: 1284 g, 144 Color Photos, 117 Graphs, 117 Tables
  • Išleidimo metai: 21-Jan-2019
  • Leidėjas: Rowman & Littlefield
  • ISBN-10: 1538109832
  • ISBN-13: 9781538109830
Kitos knygos pagal šią temą:
Statistics for Social Understanding: With Stata and SPSSDidesnis paveikslėlis
  • Formatas: Paperback / softback, 696 pages, aukštis x plotis x storis: 257x206x26 mm, weight: 1284 g, 144 Color Photos, 117 Graphs, 117 Tables
  • Išleidimo metai: 21-Jan-2019
  • Leidėjas: Rowman & Littlefield
  • ISBN-10: 1538109832
  • ISBN-13: 9781538109830
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781538109830.html
Raktažodžiai:
Statistics for Social Understanding: With Stata and SPSS introduces students to the way statistics is used in the social sciences--as a tool for advancing understanding of the social world. Written in an engaging and clear voice and based on the latest research on the teaching and learning of quantitative material, the text is geared to introductory students in the social sciences, including those with little quantitative background. It covers the conceptual aspects of statistics even when the mathematical details are minimized. Informed by research on teaching and learning in statistics, the book takes a universal design approach to accommodate diverse learning styles. With an early chapter on cross-tabulation, a focus on comparisons between groups throughout, and a unique chapter on causality, the text shows students the power of statistics for answering important real-world questions.

By providing thorough coverage of social science statistical topics, a balanced approach to calculation, and step-by-step directions on how to use statistical software, authors Nancy Whittier, Tina Wildhagen, and Howard J. Gold give students the ability to analyze data and explore and answer exciting questions.

To accommodate changing undergraduate courses, the text incorporates examples from both Stata and SPSS in every chapter and provides practice problems of every type as well as readily available datasets for classroom use, including the General Social Survey, American National Election Study, and more. Each chapter concludes with a chapter summary, a section on using Stata, a section on using SPSS, and practice problems.
Preface viii
About the Authors xvi
Chapter 1 Introduction 1(53)
Why Study Statistics?
1(2)
Research Questions and the Research Process
3(1)
Pinning Things Down: Variables and Measurement
4(2)
Units of Analysis
6(1)
Measurement Error: Validity and Reliability
6(3)
Levels of Measurement
9(2)
Causation: Independent and Dependent Variables
11(1)
Getting the Data: Sampling and Generalizing
12(1)
Sampling Methods
13(2)
Sources of Secondary Data: Existing Data Sets, Reports, and "Big Data"
15(2)
Big Data
17(1)
Growth Mindset and Math Anxiety
18(2)
Using This Book
20(1)
Statistical Software
21(2)
Chapter Summary
23(2)
Using Stata
25(8)
Using SPSS
33(12)
Practice Problems
45(7)
Notes
52(2)
Chapter 2 Getting to Know Your Data 54(67)
Frequency Distributions
55(2)
Percentages and Proportions
57(3)
Cumulative Percentage and Percentile
60(2)
Percent Change
62(1)
Rates and Ratios
63(2)
Rates
63(2)
Ratios
65(1)
Working with Frequency Distribution Tables
65(4)
Missing Values
65(2)
Simplifying Tables by Collapsing Categories
67(2)
Graphical Displays of a Single Variable: Bar Graphs, Pie Charts, Histograms, Stem-and-Leaf Plots, and Frequency Polygons
69(7)
Bar Graphs and Pie Charts
69(3)
Histograms
72(1)
Stem-and-Leaf-Plots
73(2)
Frequency Polygons
75(1)
Time Series Charts
76(1)
Comparing Two Groups on the Same Variable Using Tables, Graphs, and Charts
77(7)
Chapter Summary
84(1)
Using Stata
85(10)
Using SPSS
95(14)
Practice Problems
109(11)
Notes
120(1)
Chapter 3 Examining Relationships between Two Variables 121(40)
Cross-Tabulations and Relationships between Variables
122(12)
Independent and Dependent Variables
123(4)
Column, Row, and Total Percentages
127(7)
Interpreting the Strength of Relationships
134(2)
Interpreting the Direction of Relationships
136(4)
Graphical Representations of Bivariate Relationships
140(2)
Chapter Summary
142(1)
Using Stata
143(4)
Using SPSS
147(5)
Practice Problems
152(8)
Notes
160(1)
Chapter 4 Typical Values in a Group 161(42)
What Does It Mean to Describe What Is Typical?
162(1)
Mean
163(4)
Median
167(4)
Mode
171(2)
Finding the Mode, Median, and Mean in Frequency Distributions
173(2)
Choosing the Appropriate Measure of Central Tendency
175(4)
Median Versus Mean Income
179(2)
Chapter Summary
181(1)
Using Stata
182(5)
Using SPSS
187(6)
Practice Problems
193(9)
Notes
202(1)
Chapter 5 The Diversity of Values in a Group 203(38)
Range
205(1)
Interquartile Range
205(5)
Standard Deviation
210(2)
Using the Standard Deviation to Compare Distributions
212(2)
Comparing Apples and Oranges
214(4)
Skewed Versus Symmetric Distributions
218(2)
Chapter Summary
220(1)
Using Stata
221(4)
Using SPSS
225(6)
Practice Problems
231(9)
Notes
240(1)
Chapter 6 Probability and the Normal Distribution 241(39)
The Rules of Probability
242(11)
The Addition Rule
245(1)
The Complement Rule
246(2)
The Multiplication Rule with Independence
248(1)
The Multiplication Rule without Independence
249(2)
Applying the Multiplication Rule with Independence to the "Linda" and "Birth-Order" Probability Problems
251(2)
Probability Distributions
253(5)
The Normal Distribution
254(4)
Standardizing Variables and Calculating z-Scores
258(8)
Chapter Summary
266(1)
Using Stata
267(3)
Using SPSS
270(2)
Practice Problems
272(7)
Notes
279(1)
Chapter 7 From Sample to Population 280(34)
Repeated Sampling, Sample Statistics, and the Population Parameter
281(3)
Sampling Distributions
284(3)
Finding the Probability of Obtaining a Specific Sample Statistic
287(6)
Estimating the Standard Error from a Known Population Standard Deviation
288(1)
Finding and Interpreting the z-Score for Sample Means
289(3)
Finding and Interpreting the z-Score for Sample Proportions
292(1)
The Impact of Sample Size on the Standard Error
293(2)
Chapter Summary
295(1)
Using Stata
295(5)
Using SPSS
300(6)
Practice Problems
306(7)
Notes
313(1)
Chapter 8 Estimating Population Parameters 314(42)
Inferential Statistics and the Estimation of Population Parameters
315(2)
Confidence Intervals Manage Uncertainty through Margins of Error
317(1)
Certainty and Precision of Confidence Intervals
317(1)
Confidence Intervals for Proportions
318(8)
Constructing a Confidence Interval for Proportions: Examples
322(4)
Confidence Intervals for Means
326(7)
The t-Distribution
326(3)
Calculating Confidence Intervals for Means: Examples
329(4)
The Relationship between Sample Size and Confidence Interval Range
333(2)
The Relationship between Confidence Level and Confidence Interval Range
335(2)
Interpreting Confidence Intervals
337(1)
How Big a Sample?
338(3)
Assumptions for Confidence Intervals
341(1)
Chapter Summary
342(2)
Using Stata
344(2)
Using SPSS
346(3)
Practice Problems
349(5)
Notes
354(2)
Chapter 9 Differences between Samples and Populations 356(43)
The Logic of Hypothesis Testing
357(2)
Null Hypotheses (H0) and Alternative Hypotheses (Ha)
358(1)
One-Tailed and Two-Tailed Tests
359(1)
Hypothesis Tests for Proportions
359(6)
The Steps of the Hypothesis Test
364(1)
One-Tailed and Two-Tailed Tests
365(2)
Hypothesis Tests for Means
367(8)
Example: Testing a Claim about a Population Mean
373(2)
Error and Limitations: How Do We Know We Are Correct?
375(4)
Type I and Type II Errors
376(3)
What Does Statistical Significance Really Tell Us? Statistical and Practical Significance
379(2)
Chapter Summary
381(1)
Using Stata
382(4)
Using SPSS
386(6)
Practice Problems
392(6)
Notes
398(1)
Chapter 10 Comparing Groups 399(36)
Two-Sample Hypothesis Tests
401(3)
The Logic of the Null and Alternative Hypotheses in Two-Sample Tests
401(1)
Notation for Two-Sample Tests
402(1)
The Sampling Distribution for Two-Sample Tests
403(1)
Hypothesis Tests for Differences between Means
404(7)
Confidence Intervals for Differences between Means
411(1)
Hypothesis Tests for Differences between Proportions
412(4)
Confidence Intervals for Differences between Proportions
416(2)
Statistical and Practical Significance in Two-Sample Tests
418(1)
Chapter Summary
419(1)
Using Stata
420(4)
Using SPSS
424(5)
Practice Problems
429(5)
Notes
434(1)
Chapter 11 Testing Mean Differences among Multiple Groups 435(28)
Comparing Variation within and between Groups
436(2)
Hypothesis Testing Using ANOVA
438(1)
Analysis of Variance Assumptions
439(1)
The Steps of an ANOVA Test
440(6)
Determining Which Means Are Different: Post-Hoc Tests
446(1)
ANOVA Compared to Repeated t-Tests
447(1)
Chapter Summary
448(1)
Using Stata
448(2)
Using SPSS
450(3)
Practice Problems
453(8)
Notes
461(2)
Chapter 12 Testing the Statistical Significance of Relationships in Cross-Tabulations 463(38)
The Logic of Hypothesis Testing with Chi-Square
466(3)
The Steps of a Chi-Square Test
469(6)
Size and Direction of Effects: Analysis of Residuals
475(2)
Example: Gender and Perceptions of Health
477(4)
Assumptions of Chi-Square
481(1)
Statistical Significance and Sample Size
481(5)
Chapter Summary
486(1)
Using Stata
487(2)
Using SPSS
489(3)
Practice Problems
492(8)
Notes
500(1)
Chapter 13 Ruling Out Competing Explanations for Relationships between Variables 501(41)
Criteria for Causal Relationships
506(2)
Modeling Spurious Relationships
508(5)
Modeling Non-Spurious Relationships
513(7)
Chapter Summary
520(1)
Using Stata
521(5)
Using SPSS
526(6)
Practice Problems
532(9)
Notes
541(1)
Chapter 14 Describing Linear Relationships between Variables 542(57)
Correlation Coefficients
544(2)
Calculating Correlation Coefficients
545(1)
Scatterplots: Visualizing Correlations
546(4)
Regression: Fitting a Line to a Scatterplot
550(2)
The "Best-Fitting" Line
552(1)
Slope and Intercept
553(4)
Calculating the Slope and Intercept
556(1)
Goodness-of-Fit Measures
557(2)
R-Squared (r2)
557(1)
Standard Error of the Estimate
558(1)
Dichotomous ("Dummy") Independent Variables
559(4)
Multiple Regression
563(2)
Statistical Inference for Regression
565(6)
The F-Statistic
566(2)
Standard Error of the Slope
568(3)
Assumptions of Regression
571(2)
Chapter Summary
573(2)
Using Stata
575(6)
Using SPSS
581(7)
Practice Problems
588(10)
Notes
598(1)
Solutions To Odd-Numbered Practice Problems 599(50)
Glossary 649(7)
Appendix A Normal Table 656(2)
Appendix B Table Of T-Values 658(2)
Appendix C F-Table, For Alpha = .05 660(2)
Appendix D Chi-Square Table 662(2)
Appendix E Selected List Of Formulas 664(2)
Appendix F Choosing Tests For Bivariate Relationships 666(1)
Index 667
Nancy Whittier is Sophia Smith Professor of Sociology at Smith College. She has taught statistics and research methods for 25 years, and also teaches classes on gender, sexuality, and social movements. She is the author of Frenemies: Feminists, Conservatives, and Sexual Violence (Oxford University Press, 2018), The Politics of Child Sexual Abuse: Emotions, Social Movements, and the State (Oxford University Press, 2009) and numerous articles on social movements, gender, and sexual violence.

Tina Wildhagen is Associate Professor of Sociology and Dean of the Sophomore Class at Smith College. She has taught statistics and quantitative research methods for more than a decade, and also teaches courses on privilege and power in American education, inequality in higher education.

Howard J. Gold is Professor of Government at Smith College. He has taught statistics for 30 years, and also teaches courses on American elections, public opinion and the media, and political behavior. His research focuses on public opinion, partisanship, and voting behavior.