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Produktbild: Price, M: Statistics Alive!

Price, M: Statistics Alive!

187,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.11.2020

Verlag

Sage Publications

Seitenzahl

624

Maße (L/B/H)

21,7/28,3/2,7 cm

Gewicht

1320 g

Auflage

3. Auflage

Sprache

Englisch

ISBN

978-1-5443-2826-3

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.11.2020

Verlag

Sage Publications

Seitenzahl

624

Maße (L/B/H)

21,7/28,3/2,7 cm

Gewicht

1320 g

Auflage

3. Auflage

Sprache

Englisch

ISBN

978-1-5443-2826-3

EU-Ansprechpartner

Zeitfracht Medien GmbH
Ferdinand-Jühlke-Straße 7
99095 Erfurt
DE

Herstelleradresse

SAGE Publications
1 Oliver's Yard 55 City Road
EC1Y 1SP London
GB

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  • Produktbild: Price, M: Statistics Alive!
  • List of Figures
    List of Tables
    Preface
    Supplemental Material for Use With Statistics Alive!
    Acknowledgments
    About the Authors
    PART I. PRELIMINARY INFORMATION: "FIRST THINGS FIRST"
    Module 1. Math Review, Vocabulary, and Symbols
    Getting Started
    Common Terms and Symbols in Statistics
    Fundamental Rules and Procedures for Statistics
    More Rules and Procedures
    Module 2. Measurement Scales
    What Is Measurement?
    Scales of Measurement
    Continuous Versus Discrete Variables
    Real Limits
    PART II. TABLES AND GRAPHS: "ON DISPLAY"
    Module 3. Frequency and Percentile Tables
    Why Use Tables?
    Frequency Tables
    Relative Frequency or Percentage Tables
    Grouped Frequency Tables
    Percentile and Percentile Rank Tables
    SPSS Connection
    Module 4. Graphs and Plots
    Why Use Graphs?
    Graphing Continuous Data
    Symmetry, Skew, and Kurtosis
    Graphing Discrete Data
    SPSS Connection
    PART III. CENTRAL TENDENCY: "BULL'S-EYE"
    Module 5. Mode, Median, and Mean
    What Is Central Tendency?
    Mode
    Median
    Mean
    Skew and Central Tendency
    SPSS Connection
    PART IV. DISPERSION: "FROM HERE TO ETERNITY"
    Module 6. Range, Variance, and Standard Deviation
    What Is Dispersion?
    Range
    Variance
    Standard Deviation
    Mean Absolute Deviation
    Controversy: N Versus n - 1
    SPSS Connection
    PART V. THE NORMAL CURVE AND STANDARD SCORES: "WHAT'S THE SCORE?"
    Module 7. Percent Area and the Normal Curve
    What Is a Normal Curve?
    History of the Normal Curve
    Uses of the Normal Curve
    Looking Ahead
    Module 8. z Scores
    What Is a Standard Score?
    Benefits of Standard Scores
    Calculating z Scores
    Comparing Scores Across Different Tests
    SPSS Connection
    Module 9. Score Transformations and Their Effects
    Why Transform Scores?
    Effects on Central Tendency
    Effects on Dispersion
    A Graphic Look at Transformations
    Summary of Transformation Effects
    Some Common Transformed Scores
    Looking Ahead
    PART VI. PROBABILITY: "ODDS ARE"
    Module 10. Probability Definitions and Theorems
    Why Study Probability?
    Probability as a Proportion
    Equally Likely Model
    Mutually Exclusive Outcomes
    Addition Theorem
    Independent Outcomes
    Multiplication Theorem
    A Brief Review
    Probability and Inference
    Module 11. The Binomial Distribution
    What Are Dichotomous Events?
    Finding Probabilities by Listing and Counting
    Finding Probabilities by the Binomial Formula
    Finding Probabilities by the Binomial Table
    Probability and Experimentation
    Looking Ahead
    Nonnormal Data
    PART VII. INFERENTIAL THEORY: "OF TRUTH AND RELATIVITY"
    Module 12. Sampling, Variables, and Hypotheses
    From Description to Inference
    Sampling
    Variables
    Hypotheses
    Module 13. Errors and Significance
    Random Sampling Revisited
    Sampling Error
    Significant Difference
    The Decision Table
    Type I Error
    Type II Error
    Module 14. The z Score as a Hypothesis Test
    Inferential Logic and the z Score
    Constructing a Hypothesis Test for a z Score
    Looking Ahead
    PART VIII. THE ONE-SAMPLE TEST: "ARE THEY FROM OUR PART OF TOWN?"
    Module 15. Standard Error of the Mean
    Central Limit Theorem
    Sampling Distribution of the Mean
    Calculating the Standard Error of the Mean
    Sample Size and the Standard Error of the Mean
    Looking Ahead
    Module 16. Normal Deviate Z Test
    Prototype Logic and the Z Test
    Calculating a Normal Deviate Z Test
    Examples of Normal Deviate Z Tests
    Decision Making With a Normal Deviate Z Test
    Looking Ahead
    Module 17. One-Sample t Test
    Z Test Versus t Test
    Comparison of Z-Test and t-Test Formulas
    Degrees of Freedom
    Biased and Unbiased Estimates
    When Do We Reject the Null Hypothesis?
    One-Tailed Versus Two-Tailed Tests
    The t Distribution Versus the Normal Distribution
    The t Table Versus the Normal Curve Table
    Calculating a One-Sample t Test
    Interpreting a One-Sample t Test
    Looking Ahead
    SPSS Connection
    Module 18. Interpreting and Reporting One-Sample t: Error, Confidence, and Parameter Estimates
    What It Means to Reject the Null
    Refining Error
    Decision Making With a One-Sample t Test
    Dichotomous Decisions Versus Reports of Actual p
    Parameter Estimation: Point and Interval
    SPSS Connection
    PART IX. THE TWO-SAMPLE TEST: "OURS IS BETTER THAN YOURS"
    Module 19. Standard Error of the Difference Between the Means
    One-Sample Versus Two-Sample Studies
    Sampling Distribution of the Difference Between the Means
    Calculating the Standard Error of the Difference Between the Means
    Importance of the Size of the Standard Error of the Difference Between the Means
    Looking Ahead
    Module 20. t Test With Independent Samples and Equal Sample Sizes
    A Two-Sample Study
    Inferential Logic and the Two-Sample t Test
    Calculating a Two-Sample t Test
    Interpreting a Two-Sample t Test
    Looking Ahead
    SPSS Connection
    Module 21. t Test With Unequal Sample Sizes
    What Makes Sample Sizes Unequal?
    Comparison of Special-Case and Generalized Formulas
    Calculating a t Test With Unequal Sample Sizes
    Interpreting a t Test With Unequal Sample Sizes
    SPSS Connection
    Module 22. t Test With Related Samples
    What Makes Samples Related?
    Comparison of Special-Case and Related-Samples Formulas
    Advantage and Disadvantage of Related Samples
    Direct-Difference Formula
    Calculating a t Test With Related Samples
    Interpreting a t Test With Related Samples
    SPSS Connection
    Module 23. Interpreting and Reporting Two-Sample t: Error, Confidence, and Parameter Estimates
    What Is Confidence?
    Refining Error and Confidence
    Decision Making With a Two-Sample t Test
    Dichotomous Decisions Versus Reports of Actual p
    Parameter Estimation: Point and Interval
    SPSS Connection
    PART X. THE MULTISAMPLE TEST: "OURS IS BETTER THAN YOURS OR THEIRS"
    Module 24. ANOVA Logic: Sums of Squares, Partitioning, and Mean Squares
    When Do We Use ANOVA?
    ANOVA Assumptions
    Partitioning of Deviation Scores
    From Deviation Scores to Variances
    From Variances to Mean Squares
    From Mean Squares to F
    Looking Ahead
    Module 25. One-Way ANOVA: Independent Samples and Equal Sample Sizes
    What Is a One-Way ANOVA?
    Inferential Logic and ANOVA
    Deviation Score Method
    Raw Score Method
    Remaining Steps for Both Methods: Mean Squares and F
    Interpreting a One-Way ANOVA
    The ANOVA Summary Table
    SPSS Connection
    PART XI. POST HOC TESTS: "SO WHO'S RESPONSIBLE?"
    Module 26. Tukey HSD Test
    Why Do We Need a Post Hoc Test?
    Calculating the Tukey HSD
    Interpreting the Tukey HSD
    SPSS Connection
    Module 27. Scheffé Test
    Why Do We Need a Post Hoc Test?
    Calculating the Scheffé
    Interpreting the Scheffé
    SPSS Connection
    PART XII. MORE THAN ONE INDEPENDENT VARIABLE: "DOUBLE DUTCH JUMP ROPE"
    Module 28. Main Effects and Interaction Effects
    What Is a Factorial ANOVA?
    Factorial ANOVA Designs
    Number and Type of Hypotheses
    Main Effects
    Interaction Effects
    Looking Ahead
    Module 29. Factorial ANOVA
    Review of Factorial ANOVA Designs
    Data Setup and Preliminary Expectations
    Sums of Squares Formulas
    Calculating Factorial ANOVA Sums of Squares: Raw Score Method
    Factorial Mean Squares and Fs
    Interpreting a Factorial F Test
    The Factorial ANOVA Summary Table
    SPSS Connection
    PART XIII. NONPARAMETRIC STATISTICS: "WITHOUT FORM OR VOID"
    Module 30. One-Variable Chi-Square: Goodness of Fit
    What Is a Nonparametric Test?
    Chi-Square as a Goodness-of-Fit Test
    Formula for Chi-Square
    Inferential Logic and Chi-Square
    Calculating a Chi-Square Goodness of Fit
    Interpreting a Chi-Square Goodness of Fit
    Looking Ahead
    SPSS Connection
    Module 31. Two-Variable Chi-Square: Test of Independence
    Chi-Square as a Test of Independence
    Prerequisites for a Chi-Square Test of Independence
    Formula for a Chi-Square
    Finding Expected Frequencies
    Calculating a Chi-Square Test of Independence
    Interpreting a Chi-Square Test of Independence
    SPSS Connection
    PART XIV. EFFECT SIZE AND POWER: "HOW MUCH IS ENOUGH?"
    Module 32. Measures of Effect Size
    What Is Effect Size?
    For Two-Sample t Tests
    For ANOVA F Tests
    For Chi-Square Tests
    Module 33. Power and the Factors Affecting It
    What Is Power?
    Factors Affecting Power
    Putting It Together: Alpha, Power, Effect Size, and Sample Size
    Looking Ahead
    PART XV. CORRELATION: "WHITHER THOU GOEST, I WILL GO"
    Module 34. Relationship Strength and Direction
    Experimental Versus Correlational Studies
    Plotting Correlation Data
    Relationship Strength
    Relationship Direction
    Linear and Nonlinear Relationships
    Outliers and Their Effects
    Looking Ahead
    SPSS Connection
    Module 35. Pearson r
    What Is a Correlation Coefficient?
    Calculation of a Pearson r
    Formulas for Pearson r
    z-Score Scatterplots and r
    Calculating Pearson r: Deviation Score Method
    Interpreting a Pearson r Coefficient
    Looking Ahead
    SPSS Connection
    Module 36. Correlation Pitfalls
    Effect of Sample Size on Statistical Significance
    Statistical Significance Versus Practical Importance
    Effect of Restriction in Range
    Effect of Sample Heterogeneity or Homogeneity
    Effect of Unreliability in the Measurement Instrument
    Correlation Versus Causation
    PART XVI. LINEAR PREDICTION: "YOU'RE SO PREDICTABLE"
    Module 37. Linear Prediction
    Correlation Permits Prediction
    Logic of a Prediction Line
    Equation for the Best-Fitting Line
    Using a Prediction Equation to Predict Scores on Y
    Another Calculation Example
    SPSS Connection
    Module 38. Standard Error of Prediction
    What Is a Confidence Interval?
    Correlation and Prediction Error
    Distribution of Prediction Error
    Calculating the Standard Error of Prediction
    Using the Standard Error of Prediction to Calculate Confidence Intervals
    Factors Influencing the Standard Error of Prediction
    Another Calculation Example
    Module 39. Introduction to Multiple Regression
    What Is Regression?
    Prediction Error, Revisited
    Why Multiple Regression?
    The Multiple Regression Equation
    Multiple Regression and Predicted Variance
    Hypothesis Testing in Multiple Regression
    An Example
    The General Linear Model
    SPSS Connection
    PART XVII. REVIEW: "SAY IT AGAIN, SAM"
    Module 40. Selecting the Appropriate Analysis
    Review of Descriptive Methods
    Review of Inferential Methods
    Appendix A: Normal Curve Table
    Appendix B: Binomial Table
    Appendix C: t Table
    Appendix D: F Table (ANOVA)
    Appendix E: Studentized Range Statistic (for Tukey HSD)
    Appendix F: Chi-Square Table
    Appendix G: Correlation Table
    Appendix H: Odd Solutions to Textbook Exercises
    References
    Index