Statistics with JMP

Statistics with JMP: Hypothesis Tests, ANOVA and Regression Peter Goos, University of Leuven and University of Antwerp, Belgium David Meintrup, University of Applied Sciences Ingolstadt, Germany A first course on basic statistical methodology using JMP This book provides a first course on parameter...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Goos, Peter
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2016.
Colección:New York Academy of Sciences Ser.
Temas:
Electronic books.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Statistics with JMP: Hypothesis Tests, Anova and Regression
  • Contents
  • Preface
  • Software
  • Data Files
  • Acknowledgments
  • Part One Estimators and Tests
  • 1 Estimating Population Parameters
  • 1.1 Introduction: Estimators Versus Estimates
  • 1.2 Estimating a Mean Value
  • 1.2.1 The Mean of a Normally Distributed Population
  • 1.2.2 The Mean of an Exponentially Distributed Population
  • 1.3 Criteria for Estimators
  • 1.3.1 Unbiased Estimators
  • 1.3.2 The Efficiency of an Estimator
  • 1.4 Methods for the Calculation of Estimators
  • 1.5 The Sample Mean
  • 1.5.1 The Expected Value and the Variance
  • 1.5.2 The Probability Density of the Sample Mean for a Normally Distributed Population
  • 1.5.3 The Probability Density of the Sample Mean for a Nonnormally Distributed Population
  • 1.5.4 An Illustration of the Central Limit Theorem
  • 1.6 The Sample Proportion
  • 1.7 The Sample Variance
  • 1.7.1 The Expected Value
  • 1.7.2 The 2-Distribution
  • 1.7.3 The Relation Between the Standard Normal and the 2-Distribution
  • 1.7.4 The Probability Density of the Sample Variance
  • 1.8 The Sample Standard Deviation
  • 1.9 Applications
  • 2 Interval Estimators
  • 2.1 Point and Interval Estimators
  • 2.2 Confidence Intervals for a Population Mean with Known Variance
  • 2.2.1 The Percentiles of the Standard Normal Density
  • 2.2.2 Computing a Confidence Interval
  • 2.2.3 The Width of a Confidence Interval
  • 2.2.4 The Margin of Error
  • 2.3 Confidence Intervals for a Population Mean with Unknown Variance
  • 2.3.1 The Student t-Distribution
  • 2.3.2 The Application of the t-Distribution to Construct Confidence Intervals
  • 2.4 Confidence Intervals for a Population Proportion
  • 2.4.1 A First Interval Estimator Based on the Normal Distribution
  • 2.4.2 A Second Interval Estimator Based on the Normal Distribution
  • 2.4.3 An Interval Estimator Based on the Binomial Distribution
  • 2.5 Confidence Intervals for a Population Variance
  • 2.6 More Confidence Intervals in JMP
  • 2.7 Determining the Sample Size
  • 2.7.1 The Population Mean
  • 2.7.2 The Population Proportion
  • 3 Hypothesis Tests
  • 3.1 Key Concepts
  • 3.2 Testing Hypotheses About a Population Mean
  • 3.2.1 The Right-Tailed Test
  • 3.2.2 The Left-Tailed Test
  • 3.2.3 The Two-Tailed Test
  • 3.3 The Probability of a Type II Error and the Power
  • 3.4 Determination of the Sample Size
  • 3.5 JMP
  • 3.6 Some Important Notes Concerning Hypothesis Testing
  • 3.6.1 Fixing the Significance Level
  • 3.6.2 A Note on the "Acceptance" of the Null Hypothesis
  • 3.6.3 Statistical and Practical Significance
  • Part Two One Population
  • 4 Hypothesis Tests for a Population Mean, Proportion, or Variance
  • 4.1 Hypothesis Tests for One Population Mean
  • 4.1.1 The Right-Tailed Test
  • 4.1.2 The Left-Tailed Test
  • 4.1.3 The Two-Tailed Test
  • 4.1.4 Nonnormal Data
  • 4.1.5 The Use of JMP
  • 4.2 Hypothesis Tests for a Population Proportion
  • 4.2.1 Tests Based on the Normal Distribution

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