Statistics Alive! by Wendy J. SteinbergStatistics Alive! by Wendy J. Steinberg

Statistics Alive!

byWendy J. Steinberg

Paperback | July 21, 2010

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Based on years of first-hand teaching experience, Wendy J. Steinberg has created Statistics Alive!, the most user-friendly statistics text for students in the social and behavioral sciences, now in its Second Edition. This textbook includes topics such as frequency distributions, hypothesis formation, and inferential statistics and bivariate regression. Effect size and power, often shortchanged in other textbooks, each get substantive treatment. Students are well prepared for a next course in statistics.

Key Features

  • Modular treatment allows students to master prescribed chunks of information.
  • Strong pedagogy throughout includes learning objectives, key terms, and "Check Yourself!" questions.

New to the Second Edition

  • Twice as many chapter exercises.
  • Final module on multiple regression and the General Linear Model.
  • SPSS point-and-click instructions and screen shots of the output for all in-text examples.
  • Descriptive dispersion solutions shown using both N and n-1 denominators, to accommodate any instructor's preference.
  • A more comprehensive Student Study Guide and Instructor Resource Guide.

A version bound with SPSS Student Version 18.0 is available for only $25 extra! (ISBN: 978-1-4129-7951-1)

Title:Statistics Alive!Format:PaperbackDimensions:544 pages, 11 × 8.5 × 1.2 inPublished:July 21, 2010Publisher:Sage PublicationsLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1412979501

ISBN - 13:9781412979504

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Table of Contents

Part 1: Preliminary Information: "First Things First" Module 1: Math Review, Vocabulary, and Symbols Module 2: Measurement Scales Part 2: Tables and Graphs: "On Display" Module 3: Frequency and Percentile Table Module 4: Graphs and Plots Part 3: Central Tendency: "Bull's-Eye" Module 5: Mode, Median, and Mean Part 4: Dispersion: "From here To Eternity" Module 6: Range, Variance, and Standard Deviation Part 5: The Normal Curve and Standard Scores: "What's the Score?" Module 7: Percent Area and the Normal Curve Module 8: zScores Module 9: Score Transformations and Their Effects Part 6: Probability: "Odds Are" Module 10: Probability Definitions and Theorems Module 11: The Binomial Distribution Part 7: Inferential Theory: "Of Truth and Relativity" Module 12: Sampling, Variables, and Hypotheses Module 13: Errors and Significance Module 14: The zScore as a Hypothesis Test Part 8: The One-Sample Test: "Are They From Our Part of Town?" Module 15: Standard Error of the Mean Module 16: Normal Deviate Z Test Module 17: One-Sample t Test Module 18: Interpreting and Reporting One-Sample t: Error, Confidence, and Parameter Estimates Part 9: The Two-Sample Test: "Ours Is Better Than Yours" Module 19: Standard Error of the Difference Between Means Module 20: t Test With Independent Samples and Equal Sample Sizes Module 21: t test with Unequal Sample Sizes Module 22: t Test With Related Samples Module 23: Interpreting and Reporting Two-Sample t: Error, Confidence, and Parameter Estimates Part 10: The Multisample Test: "Ours Is Better Than Yours or Theirs" Module 24: ANOVA Logic: Sums of Squares, Partitioning, and mean Squares Module 25: One-Way ANOVA: Independent Samples and Equal Sample Sizes Part 11: Post Hoc Tests: "So Who's Responsible?" Module 26: Turkey HSD Test Module 27: Scheffe Test Part 12: More Than One Idependent Variable: "Double Dutch Jump Rope" Module 28: Main Effects and Interaction Effects Module 29: Factorial ANOVA Part 13: Nonparametric Statistics: "Without Form or Void" Module 30: One-Variable Chi-Square: Goodness of Fit Module 31: Two-Variable Chi-Square: Test of Independence Part 14: Effect Size and Power: "How Much Is Enough?" Module 32: Measures of Effect Size Module 33: Power and the Factors Effecting It Part 15: Correlation: "Whither Thou Goest, I Will Go" Module 34: Relationship Strength and Direction Module 35: Pearson r Module 36: Correlation Pitfalls Part 16: Linear Prediction: "You're So Predictable" Module 37: Linear Prediction Module 38: Standard Error of Prediction Module 39: Introduction to Multiple Regression Part 17: Review: "Say It Again, Sam" Module 40: Selecting the Appropriate Analysis