Bakir S.T., Shayib M.A. Applied statistical methods

Б.м.: CreateSpace, 2013. — 300 p.Applied Statistics is a compendium, an elementary introduction to the growing field of statistics. In this consize volume we emphasize on the concepts, definitions and terminology. With no doubt in mind, linking the three building blocks, mentioned above, will provide any person with a strong hold on the
subject of statistics.
The material had been presented in such a way that only College Algebra can be a prerequisite for the course that covers the whole text in one semester. The material is presented in 6 chapters.
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. In this chapter there is an outline, and procedure on how to implement the steps in hypothsis testing when using the two methods; the classical or the traditional method and the p-value method. The detailed exposure of the two methods will enable the reader, and the student to reach a comprehensive and sound conclusion by using information found in data.
Up till chapter 5, the discussions were with data based on one variable aspect of the population that of interest. Chapter 5 will introduce how to deal with two related variables and find a simple linear relationship, if it exists, between them. In other words, chapter 5 is restricted to simple linear regression between an explanatory variable and a response variable related to it. Moeover, the correlation concept and definition are introduced in order to measure the strength of that linear relationship which was found earlier.
Chapter 6 deals with another route of checking on data of one variable, or factor, and on the independence or dependence between two factors. Chapter 6 goes on to introduce other tests in statistics and to check on tests that make a decision whether more than two means are the same or not. Chapter 6 introduces the One-Way Analysis of Variance, or ANOVA.
The treatise is wrapped up with an appendix that has 8 tables for use when reading the textbook