Preface
1. Introduction
2. The Collection, Organization and Representation of Numerical Data
2.1. The Collection of Data
2.2. The Classification of Data
2.3. Graphical Representation of Data
2.4. Random Sampling
2.5. Random Numbers
2.6. How to Use Random Sampling Numbers
3. Elementary Probability
3.1. Introduction
3.2. Mutually Exclusive Events
3.3. Independent Events
3.4. Introduction to Permutations and Combinations
3.5. Probability Distributions
3.6. Mathematical Expectation and Arithmetic Mean
4. The Binomial and Poisson Distributions
4.1. The Binomial Distribution
4.2. The Mean of the Binomial Distribution
4.3. The Poisson Distribution
4.4. The Mean of the Poisson Distribution
4.5. The Additive Property of the Poisson Distribution
5. Measures of Central Tendency
5.1. Introduction
5.2. The Mean
5.3. The Median
5.4. The Mode
5.5. The Geometric Mean
6 Measures of Dispersion
6.1. Introduction
6.2. The Range
6.3. The Mean Deviation
6.4. The Variance
6.5. The Coefficient of Variation
7 Continuous Distributions
7.1. Introduction
7.2. The Modal and Median Values
7.3. Mathematical Expectation, the Mean and the Variance
7.4. The Mean Deviation about the Mean
7.5. The Rectangular Distribution
8 The Normal Distribution
8.1. Introduction
8.2. Properties of the Normal (or Gaussian) Distribution
8.3. Use of Normal Tables
8.4. Practical Problems
8.5. The Use of the Standardized Variate to Compare the Relative Merits of Variates from Different Normal Distributions
8.6. Arithmetical Probability Graph Paper
8.7. The Normal Approximation to the Binomial Distribution
8.8. The Normal Approximation to the Poisson Distribution
9 Significance Testing and Confidence Intervals
9.1. Introduction
9.2. Tests of a Sample Mean
9.3. Difference of Two Population Means
9.4. Test for Paired Data
9.5. Test for a Population Mean given a Large Sample (Population Variance Unknown)
9.6. Tests for the Difference Between Two Population Means given Two Large Samples (Population Variances Unknown)
9.7. Tests for Population Means given Small Samples (Population Variances Unknown)
9.8. Tests for the Difference Between Two Population Means given Two Small Samples (Population Variances Unknown)
9.9. An Approximate Method for Testing if Two Samples Come from Populations with Equal Means (Sample Sizes Small and Equal)
9.10. Test for Paired Data given Small Samples (Population Variances Unknown)
9.11. Comparison of More Than Two Means
9.12. Confidence Limits
10. Quality Control
10.1. Introduction
10.2. Control Charts for Sample Means
10.3. Control Charts for Ranges
10.4. Control Charts for Fraction Defective
10.5. Allowable Width of Control Limits when Tolerance Limits are Specified
11. Chi-Squared Distribution
11.1. Introduction
11.2. Definition
11.3. Use of Tables
11.4. Test for Variance
11.5. Additive Property of χ2
11.6. Confidence Intervals for χ2
11.7. Observed and Theoretical Frequencies
11.8. Test for the Binomial Distribution using χ2
11.9. Test for the Poisson Distribution using χ2
11.10. Test for Normality using χ2
11.11. Contingency Tables
11.12. Yates Correction
12. The F Distribution (Variance Ratio)
12.1. Introduction
12.2. Definition
12.3. Testing for the Equality of Two Population Variances
12.4. Confidence Limits for the Variance Ratio σ21|σ22
13. Bivariate Distributions
13.1. Introduction
13.2. Confidence Intervals for β1 and β0
13.3. Correlation
13.4. Grouped Data
13.5. Rank Correlation
13.6. Ranking of Equal Variates
13.7. Kendall's Coefficient of Rank Correlation (rκ)
14. Mathematical Expectation, Variance and Covariance
14.1. Introduction
14.2. Variance
14.3. Covariance
14.4. Expectation and Variance of the Sum and Difference of Two Variates
15. Weighted Averages, Death Rates and Time Series
15.1. Weighted Averages
15.2. Index Numbers
15.3. Crude and Standardized Death Rates
15.4. Introduction to Time Series
15.5. Moving Averages
15.6. Analysis of a Time Series
Appendix
Solutions
Index

On Fundamentals of Statistics