
Applied Statistics in Business and Economics
McGraw-Hill Education (Publisher)
7th Edition
Published on 11. March 2021
Book
Hardback
978-1-260-71628-3 (ISBN)
Description
Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how. The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics. It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.
More details
Edition
7th edition
Language
English
Place of publication
OH
United States
Target group
College/higher education
Illustrations
Illustrations
Weight
1755 gr
ISBN-13
978-1-260-71628-3 (9781260716283)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
David P. Doane is Professor of Quantitative Methods in Oakland University's Department of Decision and Information Sciences. He earned his Bachelor of Arts degree in mathematics and economics at the University of Kansas and his PhD from Purdue University's Krannert Graduate School.
Lori E. Seward is an Instructor in the Decisions Sciences Department in the College of Business at The University of Colorado at Denver and Health Sciences Center. She earned her Bachelor of Science and Master of Science degrees in Industrial Engineering at Virginia Tech. After several years working as a reliability and quality engineer in the paper and automotive industries, she earned her PhD from Virginia Tech.
Lori E. Seward is an Instructor in the Decisions Sciences Department in the College of Business at The University of Colorado at Denver and Health Sciences Center. She earned her Bachelor of Science and Master of Science degrees in Industrial Engineering at Virginia Tech. After several years working as a reliability and quality engineer in the paper and automotive industries, she earned her PhD from Virginia Tech.
Content
Chapter 1: Overview of Statistics
Chapter 2: Data Collection
Chapter 3: Describing Data Visually
Chapter 4: Descriptive Statistics
Chapter 5: Probability
Chapter 6: Discrete Probability Distributions
Chapter 7: Continuous Probability Distributions
Chapter 8: Sampling Distributions and Estimation
Chapter 9: One-Sample Hypothesis Tests
Chapter 10: Two-Sample Hypothesis Tests
Chapter 11: Analysis of Variance
Chapter 12: Simple Regression
Chapter 13: Multiple Regression
Chapter 14: Time-Series Analysis
Chapter 15: Chi-Square Tests
Chapter 16: Nonparametric Tests
Chapter 17: Quality Management
Chapter 18: Simulation 1
Chapter 2: Data Collection
Chapter 3: Describing Data Visually
Chapter 4: Descriptive Statistics
Chapter 5: Probability
Chapter 6: Discrete Probability Distributions
Chapter 7: Continuous Probability Distributions
Chapter 8: Sampling Distributions and Estimation
Chapter 9: One-Sample Hypothesis Tests
Chapter 10: Two-Sample Hypothesis Tests
Chapter 11: Analysis of Variance
Chapter 12: Simple Regression
Chapter 13: Multiple Regression
Chapter 14: Time-Series Analysis
Chapter 15: Chi-Square Tests
Chapter 16: Nonparametric Tests
Chapter 17: Quality Management
Chapter 18: Simulation 1