Essential Statistics

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: Courseware + eBook Bundle

Product ISBN
Courseware + eBook 978-1-941552-22-3

Table of Contents

  1. Chapter 1: Introduction and Graphical Displays
    1. 1-1 Introduction
    2. 1-2 Frequency Distributions
    3. 1-3 Dot Plots
    4. 1-4 Bar Charts or Bar Graphs
    5. 1-5 Histograms
    6. 1-6 Frequency and Relative Frequency Polygons
    7. 1-7 Ogives
    8. 1-8 Stem-and-Leaf Plots or Displays
    9. 1-9 Time Series Graphs
    10. 1-10 Pie Graphs or Pie Charts
    11. 1-11 Pareto Charts
    12. Review
  2. Chapter 2: Measures of Central Tendency
    1. 2-1 Introduction
    2. 2-2 The Mean
    3. 2-3 The Median
    4. 2-4 The Mode
    5. 2-5 Shapes of Distributions
    6. Review
  3. Chapter 3: Measures of Variability
    1. 3-1 Introduction
    2. 3-2 The Range
    3. 3-3 The Interquartile Range
    4. 3-4 The Mean Absolute Deviation
    5. 3-5 The Variance and Standard Deviation
    6. 3-6 The Coefficient of Variation
    7. 3-7 The Empirical Rule
    8. 3-8 Measuring Skewness
    9. Review
  4. Chapter 4: Measures of Position
    1. 4-1 Introduction
    2. 4-2 The z-Score or Standard Score
    3. 4-3 Percentiles
    4. 4-4 Outliers
    5. 4-5 Box Plots
    6. Review
  5. Chapter 5: Bivariate Data
    1. 5-1 Introduction
    2. 5-2 Scatter Plots
    3. 5-3 Looking for Patterns in the Data
    4. 5-4 Linear Correlation
    5. 5-5 Correlation and Causation
    6. 5-6 Regression Analysis and the Least Squares Regression Line
    7. 5-7 The Coefficient of Determination
    8. 5-8 Residual Plots
    9. 5-9 Outliers and Influential Points
    10. Review
  6. Chapter 6: Categorical Data
    1. 6-1 Introduction
    2. 6-2 Joint and Marginal Distributions
    3. 6-3 Conditional Distributions
    4. 6-4 Independence in Categorical Variables
    5. 6-5 Simpson's Paradox
    6. Review
  7. Chapter 7: Probability
    1. 7-1 Introduction
    2. 7-2 Randomness and Uncertainty
    3. 7-3 Random Experiments, Sample Space and Events
    4. 7-4 Classical Probability
    5. 7-5 Relative Frequency or Empirical Probability
    6. 7-6 The Law of Large Numbers
    7. 7-7 Subjective Probability
    8. 7-8 Some Basic Rules of Probability
    9. 7-9 Other Rules of Probability
    10. 7-10 Conditional Probability
    11. 7-11 Independence
    12. Review
  8. Chapter 8: Discrete Probability Distributions
    1. 8-1 Introduction
    2. 8-2 Random Variables
    3. 8-3 Probability Distributions for Discrete Random Variables
    4. 8-4 Expected Value for a Discrete Random Variable
    5. 8-5 Variance and Standard Deviation of a Discrete Random Variable
    6. 8-6 Bernoulli Trials and the Binomial Probability Distribution
    7. 8-7 The Geometric Probability Distribution
    8. 8-8 The Poisson Probability Distribution
    9. 8-9 The Hypergeometric Probability Distribution
    10. Review
  9. Chapter 9: The Normal Probability Distribution
    1. 9-1 Introduction
    2. 9-2 The Normal Probability Distribution
    3. 9-3 Properties of the Normal Distribution
    4. 9-4 The Standard Normal Distribution
    5. 9-5 Applications of the Normal Distribution
    6. 9-6 The Normal Approximation to the Binomial Distribution
    7. Review
  10. Chapter 10: Sampling Distributions and the Central Limit Theorem
    1. 10-1 Introduction
    2. 10-2 Sampling Distribution of a Sample Proportion
    3. 10-3 Sampling Distribution of a Sample Mean
    4. 10-4 Sampling Distribution for the Difference Between Two Independent Sample Proportions
    5. 10-5 Sampling Distribution for the Difference Between Two Independent Sample Means
    6. Review
  11. Chapter 11: Confidence Intervals Large Samples
    1. 11-1 Introduction
    2. 11-2 Large Sample Confidence Interval for a Single Population Proportion
    3. 11-3 Large Sample Confidence Interval for a Single Population Mean
    4. 11-4 Large-Sample Confidence Interval for the Difference Between Two Population Proportions
    5. 11-5 Large-Sample Confidence Interval for the Difference Between Two Population Means
    6. Review
  12. Chapter 12: Hypothesis Tests Large Samples
    1. 12-1 Introduction
    2. 12-2 Some Terms Associated with Hypothesis Testing
    3. 12-3 Large Sample Test for a Single Population Proportion
    4. 12-4 Large Sample Test for a Mean
    5. 12-5 Large-Sample Test for the Difference Between Two Population Proportions
    6. 12-6 Large Sample Tests for the Difference Between Two Population Means
    7. Review
  13. Chapter 13: Confidence Intervals Small Samples
    1. 13-1 Introduction
    2. 13-2 The t-Distribution
    3. 13-3 Small Sample Confidence Interval for a Single Population Mean
    4. 13-4 Small Sample Confidence Interval for the Difference Between Two Population Means Using Independent Samples
    5. 13-5 Small Sample Confidence Interval for the Difference Between Two Population Means Using Dependent Samples
    6. Review
  14. Chapter 14: Hypothesis Tests Small Samples
    1. 14-1 Introduction
    2. 14-2 Small Sample Test for a Single Population Mean
    3. 14-3 Small Sample Hypothesis Tests for the Difference Between two Population Means Using Independent Samples
    4. 14-4 Small Sample Hypothesis Tests for the Difference Between Two Population Means Using Dependent Samples
    5. Review
  15. Chapter 15: Chi-Square Tests
    1. 15-1 Introduction
    2. 15-2 The Chi-square Distribution
    3. 15-3 The Chi-Square Test for Goodness-of-Fit
    4. 15-4 The Chi-Square Test for Independence
    5. 15-5 Benford's Law
    6. Review
  16. Chapter 16: One-Way Analysis of Variance
    1. 16-1 Introduction
    2. 16-2 Comparing Population Means Graphically
    3. 16-3 Terminology Associated with Analysis of Variance (ANOVA)
    4. 16-4 The Hypothesis and Assumptions for One-Way ANOVA
    5. 16-5 The F-Distribution and the F Test Statistic
    6. 16-6 One-Way or Single Factor ANOVA Test for Equality of Several Population Means
    7. 16-7 The One-Way ANOVA Model and Validating the Model Assumptions
    8. Review