McEvoy D.M. A Guide to Business Statistics

JohnWiley & Sons, Inc., 2018. — 189 p. — ISBN: 1119138353.An accessible text that explains fundamental concepts in business statistics that are often obscured by formulae and mathematical notation
A Guide to Business Statistics offers a practical approach to statistics that covers the fundamental concepts in business and economics. The book maintains the level of rigor of a more conventional textbook in business statistics but uses a more stream-lined and intuitive approach. In short, A Guide to Business Statistics provides clarity to the typical statistics textbook cluttered with notation and formulae.
The author an expert in the field offers concise and straightforward explanations to the core principles and techniques in business statistics. The concepts are intro-duced through examples, and the text is designed to be accessible to readers with a variety of backgrounds. To enhance learning, most of the mathematical formulae and notation appears in technical appendices at the end of each chapter. This important resource:
Offers a comprehensive guide to understanding business statistics targeting business and economics students and professionals
Introduces the concepts and techniques through concise and intuitive examples
Focuses on understanding by moving distracting formulae and mathematical notation to appendices
Offers intuition, insights, humor, and practical advice for students of business statistics
Features coverage of sampling techniques, descriptive statistics, probability, sampling distributions, confidence intervals, hypothesis tests, and regression
Written for undergraduate business students, business and economics majors, teachers, and practitioners, A Guide to Business Statistics offers an accessible guide to the key concepts and fundamental principles in statistics.Types of Data
Populations and Samples
Descriptive Statistics
Probability
The Normal Distribution
Sampling Distributions
Confidence Intervals
Hypothesis Tests of a Population Mean
Hypothesis Tests of Categorical Data
Hypothesis Tests Comparing Two Parameters
Simple Linear Regression
Multiple Regression
More Topics in Regression