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  • Produktbild: Straightforward Statistics
  • Produktbild: Straightforward Statistics

Straightforward Statistics Understanding the Tools of Research

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2015

Verlag

Oxford University Press

Seitenzahl

416

Maße (L/B/H)

25,4/17,8/2,2 cm

Gewicht

748 g

Sprache

Englisch

ISBN

978-0-19-027695-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2015

Verlag

Oxford University Press

Seitenzahl

416

Maße (L/B/H)

25,4/17,8/2,2 cm

Gewicht

748 g

Sprache

Englisch

ISBN

978-0-19-027695-9

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Straightforward Statistics
  • Produktbild: Straightforward Statistics

    • Preface

    • Acknowledgements

    • 1. Prelude: Why Do I Need to Learn Statistics?

    • -The Nature of Findings and Facts in the Behavioral Sciences

    • - Statistical Significance and Effect Size

    • - Descriptive and Inferential Statistics

    • - A Conceptual Approach to Teaching and Learning Statistics

    • - The Nature of this Book

    • - How to Approach this Class and What You Should Get Out of It

    • - Key Terms

    • 2. Describing a Single Variable

    • - Variables, Values, and Scores

    • - Types of Variables

    • - Describing Scores for a Single Variable

    • - Indices of Central Tendency

    • - Indices of Variability (and the Sheer Beauty of Standard Deviation!)

    • - Rounding

    • - Describing Frequencies of Values for a Single Variable

    • - Representing Frequency Data Graphically

    • - Describing Data for a Categorical Variable

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 3. Standardized Scores

    • - When a Z-Score Equals 0, the Raw Score It Corresponds to Must Equal the Mean

    • - Verbal Scores for the Madupistan Aptitude Measure

    • - Quantitative Scores for the Madupistan Aptitude Measure

    • - Every Raw Score for Any Variable Corresponds to a Particular Z-Score

    • - Computing Z-Scores for All Students for the Madupistan Verbal Test

    • - Computing Raw Scores from Z-Scores

    • - Comparing Your GPA of 3.10 from Solid State University with Pat's GPA of 1.95 from Advanced Technical University

    • - Each Z-Score for Any Variable Corresponds to a Particular Raw Score

    • - Converting Z-Scores to Raw Scores (The Dorm Resident Example)

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 4. Correlation

    • - Correlations Are Summaries

    • - Representing a Correlation Graphically

    • - Representing a Correlation Mathematically

    • - Return to Madupistan

    • - Correlation Does Not Imply Causation

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 5. Statistical Prediction and Regression

    • - Standardized Regression

    • - Predicting Scores on Y with Different Amounts of Information

    • - Beta Weight

    • - Unstandardized Regression Equation

    • - The Regression Line

    • - Quantitatively Estimating the Predictive Power of Your Regression Model

    • - Interpreting r2

    • - A Real Research Example

    • - Conclusion

    • - Key Terms

    • 6. The Basic Elements of Hypothesis Testing

    • - The Basic Elements of Inferential Statistics

    • - The Normal Distribution

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 7. Introduction to Hypothesis Testing

    • - The Basic Rationale of Hypothesis Testing

    • - Understanding the Broader Population of Interest

    • - Population versus Sample Parameters

    • - The Five Basic Steps of Hypothesis Testing

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • > 1

    • - The Distribution of Means

    • > 1

    • - Confidence Intervals

    • - Real Research Example

    • - Summary

    • - Key Terms

    • 9. Statistical Power

    • - What Is Statistical Power?

    • - An Example of Statistical Power

    • - Factors that Affect Statistical Power

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 10. t-tests (One-Sample and Within-Groups)

    • - One-Sample t-test

    • - Steps for Hypothesis Testing with a One-Sample t-test

    • - Here Are Some Simple Rules to Determine the Sign of tcrit with a One-Sample t-Test

    • - Computing Effect Size with a One-Sample t-Test

    • - How the t-Test Is Biased Against Small Samples

    • - The Within-Group t-Test

    • - Steps in Computing the Within-Group t-Test

    • - Computing Effect Size with a Within-Group t-test

    • - A Real Research Example

    • - Summary

    • - Key Terms

    • 11. The Between-Groups t-test

    • - The Elements of the Between-Groups t-test

    • - Effect Size with the Between-Groups t-test

    • - Another Example

    • - Real Research Example

    • - Summary

    • - Key Terms

    • 12. Analysis of Variance

    • - ANOVA as a Signal-Detection Statistic

    • - An Example of the One-Way ANOVA

    • - What Can and Cannot Be Inferred from ANOVA (The Importance of Follow-Up Tests)

    • - Estimating Effect Size with the One-Way ANOVA

    • - Real Research Example

    • - Summary

    • - Key Terms

    • 13. Chi Square and Hypothesis-Testing with Categorical Variables

    • - Chi Square Test of Goodness of Fit

    • - Steps in Hypothesis Testing with Chi Square Goodness of Fit

    • - What Can and Cannot Be Inferred from a Significant Chi Square

    • - Chi Square Goodness of Fit Testing for Equality across Categories

    • - Chi Square Test of Independence

    • - Real Research Example

    • - Summary

    • - Key Terms

    • Appendix A: Cumulative Standardized Normal Distribution

    • Appendix B: t Distribution: Critical Values of t

    • Appendix C: F Distribution: Critical Values of F

    • Appendix D: Chi Square Distribution: Critical Values of ?2 (Chi Squared) Distribution: Critical Values of ?2

    • Appendix E: Advanced Statistics to Be Aware of

    • - Advanced Forms of ANOVA

    • - Summary

    • - Key Terms

    • Appendix F: Using SPSS

    • - Activity 1: SPSS Data Entry Lab

    • - Activity 2: Working with SPSS Syntax Files

    • - Syntax Files, Recoding Variables, Compute Statements, Out Files, and the Computation of Variables in SPSS

    • - Recoding Variables

    • - Computing New Variables

    • - Output Files

    • - Example: How to Recode Items for the Jealousy Data and Compute Composite Variables

    • - Activity 3: Descriptive Statistics

    • - Frequencies, Descriptives, and Histograms

    • - Frequencies, Descriptives, and Histograms for Data Measured in Class

    • - The Continuous Variable

    • - The Categorical Variable

    • - Activity 4: Correlations

    • - Activity 5: Regression

    • - Activity 6: t-tests

    • - Independent Samples Test

    • - Activity 7: ANOVA with SPSS

    • - Post Hoc Tests

    • - Homogeneous Subsets

    • - Activity 8: Factorial ANOVA

    • - Recomputing Variables so as to Be Able to Conduct a One-Way ANOVA to Examine Specific Differences Between Means

    • - Activity 9: Chi Square

    • - Crosstabs

    • Glossary

    • References

    • Index