Basic Business Statistics
Concepts and Applications
6th Edition
Published in September 1995
Book
Paperback/Softback
928 pages
978-0-13-317737-4 (ISBN)
Description
This text adopts a practical, data analytic approach to the teaching of business statistics through the development and use of a survey (and database) that integrates various topics, permitting a cohesive study of the subject. It integrates student problems, projects and case studies; contains two distinct types of summary sections to facilitate a total, functional understanding; and discusses the use of software packages like MINITAB, SAS, SPSS and STATISTIX, with output illustrations and opportunities for hands-on applications interwoven throughout the text. It is written for introductory business statistics courses at undergraduate and postgraduate level.
More details
Edition
6th Revised edition
Language
English
Place of publication
Harlow
United Kingdom
Publishing group
Pearson Education Limited
Target group
College/higher education
Edition type
Revised edition
Illustrations
appendices
Dimensions
Height: 235 mm
Width: 178 mm
Weight
1923 gr
ISBN-13
978-0-13-317737-4 (9780133177374)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Berenson
Basic Business Statistics
Book
12/1998
7th Edition
Pearson Education (US)
€43.32
Article exhausted; check for reprint
Previous edition
Book
07/1992
5th Edition
Prentice-Hall
€33.37
Article exhausted; check for reprint
Content
Data Collection. Presenting Numerical Data in Tables and Charts. Summarizing and Describing Numerical Data. Presenting Categorical Data in Tables and Charts. Basic Probability. Some Important Discrete Probability Distributions. The Normal Distribution. Sampling Distributions. Estimation. Fundamentals of Hypothesis Testing. One-Sample Tests with Numerical Data. Two-Sample Tests with Numerical Data. Anova and Other C Sample Tests with Numerical Data. Hypothesis Testing with Categorical Data. Statistical Applications in Quality and Productivity Management. The Simple Linear Regression Model and Correlation. Multiple Regression. Time Series Analysis. Answers to Selected Problems.