A non--mathematical introductory statistics text that combines clear explanation of concepts, an extensive coverage of useful statistical techniques, and numerous illustrations with live data from diverse fields. Emphasizes assumptions and limitations of the statistical methods so that violations of assumptions can be avoided.

Introduction. Descriptive Study of Data. Elements of Probability. Random Variables and Probability Distributions. Distributions for Counts. Basic Concepts of Testing Hypotheses. The Normal Distribution and Random Samples. Inferences about a Population. Comparing Two Treatments. Regression Analysis: Simple Linear Relation. Regression Analysis: Model Checking and Multiple LinearRegression. Correlation: A Measure of Linear Relationship. Analysis of Categorized Data. Design of Experiments and Analysis of Variance. Nonparametric Inference. Sample Surveys.

Statistical Concepts and Methods The text introduces a broad spectrum of statistical principles at an elementary level, emphasizing understanding the subject rather than just learning the methods. Some of the major qualities and features it offers are: Descriptions of basic statistical methods, demonstrating their logical basis through intuitive reasoning rather than mathematical derivations. (Occasionally adding a few steps of algebra to satisfy a more curious mind.)Inferences drawn from analyzing data (of contemporary interest in many fields).Discussion of various tools of statistical inference, stressing the assumptions behind these techniques and the consequences of violations of the assumptions. (In addition to clearly stating the assumptions in individual problems, steps are indicated for checking possible violations.)Examples and exercises, drawn from real-life settings from various fields to cater to the interests of students in many disciplines. A large number of these contain data gathered from experiments on the campus as well as from published reports in journals and government publications.Treatment of basic probability with interesting examples that motivate the role of probability in statistical inference.Introduction of testing hypotheses early in the text.In-depth coverage of regression and correlation analyses.Sample survey concepts including the advantage of stratifying sources of bias and practical aspects of designing.