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# Essential Business Statistics

by Lloyd R. Jaisingh

The Essential Business 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

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. 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: Continuous Probability Distribution
1. 9.1 Introduction
2. 9.2 The Continuous Uniform Probability Distribution
3. 9.3 The Normal Probability Distribution
4. 9.4 Properties of the Normal Distribution
5. 9.5 The Standard Normal Distribution
6. 9.6 Applications of the Normal Distribution
7. 9.7 The Normal Approximation to the Binomial Distribution
8. 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 of a Difference between Two Independent Sample Proportions
5. 10.5 Sampling Distribution of a 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 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 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