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Probability and Statistics EBook

Publisher: 
Online
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0.00
ISBN: 
00000000000000
Date Received: 
Friday, July 23, 2010
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Multiple Authors
Publication Date: 
2009
Format: 
Electronic Book
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Category: 
Textbook
  • 1 Preface
    • 1.1 Format
    • 1.2 Learning and Instructional Usage
  • 2 Chapter I: Introduction to Statistics
    • 2.1 The Nature of Data and Variation
    • 2.2 Uses and Abuses of Statistics
    • 2.3 Design of Experiments
    • 2.4 Statistics with Tools (Calculators and Computers)
  • 3 Chapter II: Describing, Exploring, and Comparing Data
    • 3.1 Types of Data
    • 3.2 Summarizing Data with Frequency Tables
    • 3.3 Pictures of Data
    • 3.4 Measures of Central Tendency
    • 3.5 Measures of Variation
    • 3.6 Measures of Shape
    • 3.7 Statistics
    • 3.8 Graphs and Exploratory Data Analysis
  • 4 Chapter III: Probability
    • 4.1 Fundamentals
    • 4.2 Rules for Computing Probabilities
    • 4.3 Probabilities Through Simulations
    • 4.4 Counting
  • 5 Chapter IV: Probability Distributions
    • 5.1 Random Variables
    • 5.2 Expectation (Mean) and Variance
    • 5.3 Bernoulli and Binomial Experiments
    • 5.4 Multinomial Experiments
    • 5.5 Geometric, Hypergeometric, Negative Binomial and Negative Multinomial
    • 5.6 Poisson Distribution
  • 6 Chapter V: Normal Probability Distribution
    • 6.1 The Standard Normal Distribution
    • 6.2 Nonstandard Normal Distribution: Finding Probabilities
    • 6.3 Nonstandard Normal Distribution: Finding Scores (Critical Values)
  • 7 Chapter VI: Relations Between Distributions
    • 7.1 The Central Limit Theorem
    • 7.2 Law of Large Numbers
    • 7.3 Normal Distribution as Approximation to Binomial Distribution
    • 7.4 Poisson Approximation to Binomial Distribution
    • 7.5 Binomial Approximation to Hypergeometric
    • 7.6 Normal Approximation to Poisson
  • 8 Chapter VII: Point and Interval Estimates
    • 8.1 Method of Moments and Maximum Likelihood Estimation
    • 8.2 Estimating a Population Mean: Large Samples
    • 8.3 Estimating a Population Mean: Small Samples
    • 8.4 Student's T distribution
    • 8.5 Estimating a Population Proportion
    • 8.6 Estimating a Population Variance
    • 8.7 Confidence Intervals Activity
  • 9 Chapter VIII: Hypothesis Testing
    • 9.1 Fundamentals of Hypothesis Testing
    • 9.2 Testing a Claim about a Mean: Large Samples
    • 9.3 Testing a Claim about a Mean: Small Samples
    • 9.4 Testing a Claim about a Proportion
    • 9.5 Testing a Claim about a Standard Deviation or Variance
  • 10 Chapter IX: Inferences From Two Samples
    • 10.1 Inferences About Two Means: Dependent Samples
    • 10.2 Inferences About Two Means: Independent Samples
    • 10.3 Comparing Two Variances
    • 10.4 Inferences about Two Proportions
  • 11 Chapter X: Correlation and Regression
    • 11.1 Correlation
    • 11.2 Regression
    • 11.3 Variation and Prediction Intervals
    • 11.4 Multiple Regression
  • 12 Chapter XI: Analysis of Variance (ANOVA)
    • 12.1 One-Way ANOVA
    • 12.2 Two-Way ANOVA
  • 13 Chapter XII: Non-Parametric Inference
    • 13.1 Differences of Medians (Centers) of Two Paired Samples
    • 13.2 Differences of Medians (Centers) of Two Independent Samples
    • 13.3 Differences of Proportions of Two Samples
    • 13.4 Differences of Means of Several Independent Samples
    • 13.5 Differences of Variances of Independent Samples (Variance Homogeneity)
  • 14 Chapter XIII: Multinomial Experiments and Contingency Tables
    • 14.1 Multinomial Experiments: Goodness-of-Fit
    • 14.2 Contingency Tables: Independence and Homogeneity
  • 15 Chapter XIV:Bayesian Statistics
    • 15.1 Preliminaries
    • 15.2 Bayesian Inference for the Normal Distribution
    • 15.3 Some Other Common Distributions
    • 15.4 Hypothesis Testing
    • 15.5 Two Sample Problems
    • 15.6 Hierarchical Models
    • 15.7 The Gibbs Sampler and Other Numerical Methods
  • 16 Additional EBook Chapters (under Development)
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