Essen.Of Stat. for Behavioral Sci. - Access - 8th Edition - by GRAVETTER - ISBN 9781285592480

Essen.Of Stat. for Behavioral Sci. - Ac...
8th Edition
GRAVETTER
Publisher: CENGAGE L
ISBN: 9781285592480

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Chapter 3.3 - The MedianChapter 3.5 - Selecting A Measure Of Central TendencyChapter 3.6 - Central Tendency And The Shape Of The DistributionChapter 4 - Measures Of VariabilityChapter 4.3 - Standard Deviation And Variance For A PopulationChapter 4.4 - Standard Deviation And Variance For A SampleChapter 4.5 - More About Variance And Standard DeviationChapter 5 - z-Scores: Location Of Scores And Standardized DistributionsChapter 5.2 - z-Scores And Locations In A DistributionChapter 5.3 - Using z-Scores To Standardize A DistributionChapter 5.4 - Other Standardized Distributions Based On z-ScoresChapter 5.6 - Looking Ahead To Inferential StatisticsChapter 6 - ProbabilityChapter 6.1 - Introduction To ProbabilityChapter 6.2 - Probability And The Normal DistributionChapter 6.3 - Probabilities And Proportions For Scores From A Normal DistributionChapter 7 - Probability And Samples: The Distribution Of Sample MeansChapter 7.2 - The Distribution Of Sample MeansChapter 7.3 - Probability And The Distribution Of Sample MeansChapter 7.4 - More About Standard ErrorChapter 7.5 - Looking Ahead To Inferential StatisticsChapter 8 - Introduction To Hypothesis TestingChapter 8.1 - The Logic Of Hypothesis TestingChapter 8.2 - Uncertainty And Errors In Hypothesis TestingChapter 8.3 - More About Hypothesis TestsChapter 8.4 - Directional (One-Tailed) Hypothesis TestsChapter 8.5 - Concerns About Hypothesis Testing: Measuring Effect SizeChapter 8.6 - Statistical PowerChapter 9 - Introduction To The T StatisticChapter 9.1 - The T Statistic: An Alternative To ZChapter 9.2 - Hypothesis Tests With The T StatisticChapter 9.3 - Measuring Effect Size For The T StatisticChapter 9.4 - Directional Hypotheses And One-Tailed TestsChapter 10 - The T Test For Two Independent SamplesChapter 10.2 - The T Statistic For An Independent-Measures Research DesignChapter 10.3 - Hypothesis Tests And Effect Size With The Independent-Measures T StatisticChapter 10.4 - Assumptions Underlying The Independent-Measures T FormulaChapter 11 - The T Test For Two Related SamplesChapter 11.2 - The T Statistic For A Repeated-Measures Research DesignChapter 11.3 - Hypothesis Tests And Effect Size For The Repeated-Measures DesignChapter 11.4 - Uses And Assumptions For Repeated-Measures T TestsChapter 12 - Introduction To Analysis Of VarianceChapter 12.2 - The Logic Of AnovaChapter 12.3 - Anova Notation And FormulasChapter 12.4 - The Distribution Of F-RatiosChapter 12.5 - Examples Of Hypothesis Testing And Effect Size With AnovaChapter 12.6 - Post Hoc TestsChapter 12.7 - The Relationships Between Anova And T TestsChapter 13 - Repeated-Measures And Two-Factor Analysis Of VarianceChapter 13.2 - Repeated-Measures AnovaChapter 13.3 - Two-Factor Anova (Independent Measures)Chapter 14 - CorrelationChapter 14.1 - IntroductionChapter 14.2 - The Pearson CorrelationChapter 14.3 - Using And Interpreting The Pearson CorrelationChapter 14.4 - Hypothesis Tests With The Pearson CorrelationChapter 14.5 - Alternatives To The Pearson CorrelationChapter 14.6 - Introduction To Linear Equations And RegressionChapter 15 - The Chi-Square Statistic: Tests For Goodness Of Fit And IndependenceChapter 15.2 - The Chi-Square Test For Goodness Of FitChapter 15.3 - The Chi-Square Test For IndependenceChapter 15.5 - Assumptions And Restrictions For Chi-Square Tests

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