
Essential Statistics
by Lloyd R. Jaisingh
The Essential Statistics eBook is intended for use in a statistics course and has many interactive features and tests to benefit the student. The eBook contains a multitude of definitions, tables, graphs, excel data sets, and e-Self Reviews.
Formats: eBook
Table of Contents
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Chapter 1: Introduction and Graphical Displays
- 1.1 Introduction
- 1.2 Frequency Distributions
- 1.3 Dot Plots
- 1.4 Bar Charts or Bar Graphs
- 1.5 Histograms
- 1.6 Frequency and Relative Frequency Polygons
- 1.7 Ogives
- 1.8 Stem-and-Leaf Plots or Displays
- 1.9 Time Series Graphs
- 1.10 Pie Graphs or Pie Charts
- 1.11 Pareto Charts
- Review
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Chapter 2: Measures of Central Tendency
- 2.1 Introduction
- 2.2 The Mean
- 2.3 The Median
- 2.4 The Mode
- 2.5 Shapes of Distributions
- Review
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Chapter 3: Measures of Variability
- 3.1 Introduction
- 3.2 The Range
- 3.3 The Interquartile Range
- 3.4 The Mean Absolute Deviation
- 3.5 The Variance and Standard Deviation
- 3.6 The Coefficient of Variation
- 3.7 The Empirical Rule
- 3.8 Measuring Skewness
- Review
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Chapter 4: Measures of Position
- 4.1 Introduction
- 4.2 The z-Score or Standard Score
- 4.3 Percentiles
- 4.4 Outliers
- 4.5 Box Plots
- Review
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Chapter 5: Bivariate Data
- 5.1 Introduction
- 5.2 Scatter Plots
- 5.3 Looking for Patterns in the Data
- 5.4 Linear Correlation
- 5.5 Correlation and Causation
- 5.6 Regression Analysis and the Least Squares Regression Line
- 5.7 The Coefficient of Determination
- 5.8 Residual Plots
- 5.9 Outliers and Influential Points
- Review
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Chapter 6: Categorical Data
- 6.1 Introduction
- 6.2 Joint and Marginal Distributions
- 6.3 Conditional Distributions
- 6.4 Independence in Categorical Variables
- 6.5 Simpson's Paradox
- Review
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Chapter 7: Probability
- 7.1 Introduction
- 7.2 Randomness and Uncertainty
- 7.3 Random Experiments, Sample Space and Events
- 7.4 Classical Probability
- 7.5 Relative Frequency or Empirical Probability
- 7.6 The Law of Large Numbers
- 7.7 Subjective Probability
- 7.8 Some Basic Rules of Probability
- 7.9 Other Rules of Probability
- 7.10 Conditional Probability
- 7.11 Independence
- Review
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Chapter 8: Discrete Probability Distributions
- 8.1 Introduction
- 8.2 Random Variables
- 8.3 Probability Distributions for Discrete Random Variables
- 8.4 Expected Value for a Discrete Random Variable
- 8.5 Variance and Standard Deviation of a Discrete Random Variable
- 8.6 Bernoulli Trials and the Binomial Probability Distribution
- 8.7 The Geometric Probability Distribution
- 8.8 The Poisson Probability Distribution
- 8.9 The Hypergeometric Probability Distribution
- Review
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Chapter 9: The Normal Probability Distribution
- 9.1 Introduction
- 9.2 The Normal Probability Distribution
- 9.3 Properties of the Normal Distribution
- 9.4 The Standard Normal Distribution
- 9.5 Applications of the Normal Distribution
- 9.6 The Normal Approximation to the Binomial Distribution
- Review
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Chapter 10: Sampling Distributions and the Central Limit Theorem
- 10.1 Introduction
- 10.2 Sampling Distribution of a Sample Proportion
- 10.3 Sampling Distribution of a Sample Mean
- 10.4 Sampling Distribution for the Difference Between Two Independent Sample Proportions
- 10.5 Sampling Distribution for the Difference Between Two Independent Sample Means
- Review
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Chapter 11: Confidence Intervals Large Samples
- 11.1 Introduction
- 11.2 Large Sample Confidence Interval for a Single Population Proportion
- 11.3 Large Sample Confidence Interval for a Single Population Mean
- 11.4 Large-Sample Confidence Interval for the Difference Between Two Population Proportions
- 11.5 Large-Sample Confidence Interval for the Difference Between Two Population Means
- Review
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Chapter 12: Hypothesis Tests Large Samples
- 12.1 Introduction
- 12.2 Some Terms Associated with Hypothesis Testing
- 12.3 Large Sample Test for a Single Population Proportion
- 12.4 Large Sample Test for a Mean
- 12.5 Large-Sample Test for the Difference Between Two Population Proportions
- 12.6 Large Sample Tests for the Difference Between Two Population Means
- Review
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Chapter 13: Confidence Intervals Small Samples
- 13.1 Introduction
- 13.2 The t-Distribution
- 13.3 Small Sample Confidence Interval for a Single Population Mean
- 13.4 Small Sample Confidence Interval for the Difference Between Two Population Means Using Independent Samples
- 13.5 Small Sample Confidence Interval for the Difference Between Two Population Means Using Dependent Samples
- Review
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Chapter 14: Hypothesis Tests Small Samples
- 14.1 Introduction
- 14.2 Small Sample Test for a Single Population Mean
- 14.3 Small Sample Hypothesis Tests for the Difference Between two Population Means Using Independent Samples
- 14.4 Small Sample Hypothesis Tests for the Difference Between Two Population Means Using Dependent Samples
- Review
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Chapter 15: Chi-Square Tests
- 15.1 Introduction
- 15.2 The Chi-square Distribution
- 15.3 The Chi-Square Test for Goodness-of-Fit
- 15.4 The Chi-Square Test for Independence
- 15.5 Benford's Law
- Review
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Chapter 16: One-Way Analysis of Variance
- 16.1 Introduction
- 16.2 Comparing Population Means Graphically
- 16.3 Terminology Associated with Analysis of Variance (ANOVA)
- 16.4 The Hypothesis and Assumptions for One-Way ANOVA
- 16.5 The F-Distribution and the F Test Statistic
- 16.6 One-Way or Single Factor ANOVA Test for Equality of Several Population Means
- 16.7 The One-Way ANOVA Model and Validating the Model Assumptions
- Review