This book is a compendium, an elementary introduction to the growing field of statistics. In this consize volume we emphasize on the concepts, definitions and terminology.

This volume should prepare the reader to make a good decision based on data. The material, contained in the book, can be covered in a 15-week, 3-hours-per-week semester, with little adjustment as time allows.
Chapter 1 is about collecting, and organizing qualitative and quantitative data, as well as summarizing the data graphically or numericall regardless if the data were discrete or continuous.
Chapter 2 introduces the notion of probability, its axioms, its rules, and applications. In addition to that, Chapter 2 contains material on probability distributions and their characteristics for discrete and continuous cases.
Chapter 3 covers the first main part of inferential statistics; namely estimation in its two branches: point and interval estimation by introducing the sample statistics as estimators for the population parameters.
Chapter 4 is concerned about the second part of inferential statistics, namely hypothesis testing about one parameter of a population, or two parameters of two populations.

Content
Preface
1. Descriptive Statistics
1.1. Introduction
1.2. Descriptive Statistics
1.3. Frequency Distributions
1.4. Graphical Presentation
1.5. Summation Notation
1.6. Numerical Methods for Summarizing Quantitative Data
1.7 Some Properties of the Numerical Measures of Quantitative Data
1.8. Other Measures for Quantitative Data
1.9. Methods of Counting
1.10. Description of Grouped Data
2. Random Variables and Probability Distributions
2.1. Introduction
2.2. Probability
2.3. Operations and Probability calculation on Events
2.4. Random Variables
2.5. Expected Value and Variance of a Random Variable
2.6. Some Discrete Probability Distributions
2.7. Normal Distribution
3. Estimation
3.1. Sampling
3.2. Point Estimation
3.3. Interval Estimation
3.4. Confidence Interval about One Parameter
3.5. Sample Size Determination
3.6. Confidence Interval about two Parameters
4. Testing of Statistical Hypotheses
4.1. Introduction
4.2. Fundamental Concepts
4.3. Methods in Testing a Statistical Hypothesis
4.4. Hypothesis Testing About One Parameter
4.5. Hypothesis Testing Concerning Two Parameters
5. Simple Linear Regression and Correlation
5.1. Introduction
5.2. Regression Models
5.3. Fitting a straight line (First order Model)
5.4. Correlation
5.5. Hypothesis Testing in Regression Analysis
5.6. Confidence Interval on β and β
6. Other Tests and Analysis Of Variance
6.1. Introduction
6.2. Goodness-of-Fit Tests
6.3. Contingency Tables
6.4. The one-Way Analysis of Variance
7. Appendix A Tables
8. References

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