Bundle: Essentials of Statistics for Th...9th EditionFrederick J Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano Publisher: Cengage LearningISBN: 9781337593830
Bundle: Essentials of Statistics for Th...
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Chapter 1 - Introduction To StatisticsChapter 1.1 - Statistics, Science, And ObservationsChapter 1.2 - Variables And MeasurementChapter 1.3 - Three Data Structures, Research Methods, And StatisticsChapter 1.4 - Statistical NotationChapter 2 - Frequency DistributionsChapter 2.1 - Frequency Distributions And Frequency Distribution TablesChapter 2.2 - Grouped Frequency Distribution TablesChapter 2.3 - Frequency Distribution GraphsChapter 3 - Central Tendency
Chapter 3.2 - The MeanChapter 3.3 - The MedianChapter 3.4 - The ModeChapter 3.5 - Central Tendency And The Shape Of The DistributionChapter 3.6 - Selecting A Measure Of Central TendencyChapter 4 - VariabilityChapter 4.1 - Introduction To VariabilityChapter 4.2 - Defining Variance And Standard DeviationChapter 4.3 - Measuring Variance And Standard Deviation For A PopulationChapter 4.4 - Measuring Variance And Standard Deviation For A SampleChapter 4.5 - Sample Variance As An Unbiased StatisticChapter 4.6 - 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 - Other Relationships Between z, X, The Mean, And The Standard DeviationChapter 5.4 - Using z-Scores To Standardize A DistributionChapter 5.5 - 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 6.4 - Looking Ahead To Inferential StatisticsChapter 7 - Probability And Samples: The Distribution Of Sample MeansChapter 7.1 - Samples, Populations, And The Distribution Of Sample MeansChapter 7.2 - Shape, Central Tendency, And Variability For The Distribution Of Sample MeansChapter 7.3 - z-Scores And Probability For 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 Fortwo Independent SamplesChapter 10.1 - Introduction To The Independent-Measures DesignChapter 10.2 - The Hypotheses And The Independent-Measures T StatisticChapter 10.3 - Hypothesis Tests With The Independent-Measures T StatisticChapter 10.4 - Effect Size And Confidence Intervals For The Independent-Measures TChapter 10.5 - The Role Of Sample Variance And Sample Size In The Independent-Measures T TestChapter 11 - The T Test For Two Related SamplesChapter 11.1 - Introduction To Repeated-Measures DesignsChapter 11.2 - The T Statistic For A Repeated-Measures Research DesignChapter 11.3 - Hypothesis Tests For The Repeated-Measures DesignChapter 11.4 - Effect Size, Confidence Intervals, And The Role Of Sample Size And Sample Variance For The Repeated-Measures TChapter 11.5 - Comparing Repeated· And Independent-Measures DesignsChapter 12 - Introduction To Analysis Of VarianceChapter 12.1 - Introduction (An Overview Of Analysis Of Variance)Chapter 12.2 - The Logic Of Analysis Of VarianceChapter 12.3 - Anova Notation And FormulasChapter 12.4 - Examples Of Hypothesis Testing And Effect Size With An OvaChapter 12.5 - Post Hoc TestsChapter 12.6 - More About An OvaChapter 13 - Repeated-Measures And Two-Factor Analysis Of VarianceChapter 13.1 - Introduction To The Repeated-Measures AnovaChapter 13.2 - Hypothesis Testing And Effect Size With The Repeated-Measures AnovaChapter 13.3 - More About The Repeated-Measures DesignChapter 13.4 - An Overview Of The Two-Factor, Independent-Measures AnovaChapter 13.5 - An Example Of The Two-Factor Anova And Effect SizeChapter 14 - Correlation And RegressionChapter 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 IndependanceChapter 15.1 - Introduction To Chi-Square: The Test For Goodness Of FitChapter 15.2 - An Example Of The Chi-Square Test For Goodness Of FitChapter 15.3 - The Chi-Square Test For IndependenceChapter 15.4 - Effect Size And Assumptions For The Chi-Square TestsChapter 15.5 - The Relationship Between Chi-Square And Other Statistical Procedures
Book Details
A brief version of Gravetter and Wallnau's proven best seller, ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, 9th Edition delivers straightforward instruction, unrivaled accuracy, learning aids, and a wealth of real-world examples and illustrations. The authors explain statistical procedures so students can go beyond memorizing formulas and begin gaining a conceptual understanding of statistics. By skillfully integrating applications that reinforce concepts, they ensure that even students with a weak background in mathematics can understand the material and become savvy consumers of statistical information. Also available: the MindTap digital learning experience and the Aplia online homework tool.
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Chapter 1.1, Problem 1LCChapter 1.2, Problem 2LCChapter 1, Problem 1PChapter 1, Problem 7PChapter 1, Problem 11PChapter 1, Problem 14PChapter 1, Problem 19PChapter 1, Problem 23PChapter 2, Problem 1P
Chapter 3, Problem 1PChapter 3, Problem 5PChapter 4, Problem 1PChapter 4, Problem 21PChapter 4, Problem 23PChapter 5, Problem 1PChapter 5, Problem 24PChapter 5, Problem 25PChapter 6, Problem 1PChapter 6, Problem 10PChapter 6, Problem 17PChapter 7, Problem 1PChapter 7, Problem 11PChapter 7, Problem 13PChapter 8, Problem 1PChapter 8, Problem 9PChapter 8, Problem 10PChapter 9, Problem 1PChapter 9, Problem 16PChapter 9, Problem 17PChapter 10, Problem 1PChapter 10, Problem 23PChapter 10, Problem 24PChapter 11, Problem 1PChapter 11, Problem 2PChapter 11, Problem 7PChapter 11, Problem 14PChapter 12, Problem 1PChapter 12, Problem 20PChapter 12, Problem 22PChapter 13, Problem 1PChapter 13, Problem 11PChapter 13, Problem 23PChapter 14, Problem 1PChapter 14, Problem 8PChapter 14, Problem 10PExplanation: In a nonparametric test data is not required to fit a normal distribution, in-fact, it...Chapter 15, Problem 4PChapter 15, Problem 13P
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