
Basic Statistics for Business and Economics: 2024 Release ISE
McGraw-Hill Education (Publisher)
11th Edition
Published on 19. March 2024
Book
Paperback/Softback
672 pages
978-1-266-91476-8 (ISBN)
Description
Business and Economics is a highly regarded title that equips students with a conceptual understanding and interpretation of statistics and its applications in the business world, while also promoting diversity, equity, and inclusion. The 2024 release takes a step-by-step approach, ensuring that beginners can easily grasp the concepts and succeed in a basic statistics course. With a focus on real-world application, this title uses examples and exercises to illustrate how statistics can be applied to solve current business scenarios. Additionally, the authors recognize the growing importance of data analytics and support the development of these basic skills through an application-based section on data analytics at the end of each chapter along with easily accessible data sets for practice. This title primarily uses Excel, Minitab, and MegaStat to demonstrate statistical analyses, helping users create graphical and descriptive statistics and conduct hypothesis testing.
More details
Edition
11th edition
Language
English
Place of publication
OH
United States
Target group
College/higher education
US School Grade: From College Freshman to College Graduate Student
Illustrations
413 Illustrations
Dimensions
Height: 203 mm
Width: 267 mm
Thickness: 26 mm
Weight
1116 gr
ISBN-13
978-1-266-91476-8 (9781266914768)
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
Douglas A. Lind earned his B.S. in Business from Bowling Green State University, and his Ph.D. and M.B.A. from the University of Toledo. He is Emeritus Professor at Coastal Carolina University and the University of Toledo. Dr. Lind is a co-author of Statistical Techniques in Business and Economics with the late Robert D. Mason and William G. Marchal. He has more than 38 years of college teaching experience, including teaching statistics at the introductory, intermediate, and advanced undergraduate levels, as well as graduate courses in statistics and research methods. Dr. Lind is a past recipient of the Tony DeJute Outstanding Teacher Award.
William G. Marchal earned his B.S. in mathematics from the University of Dayton, his M.A. in mathematics from Catholic University of America, and his D.Sc. in operations research from George Washington University. He is Emeritus Professor of Information Systems and Operations Management at the University of Toledo College of Business Administration. Dr. Marchal has held visiting appointments at the University of Michigan and at George Mason University. He has worked at the Executive Office of the District of Columbia government, the George Washington University Institute for Management Science, and the U.S. Army Chemical Research and Development Center. He has also served as an associate editor of Naval Research Logistics.
Samuel A. Wathen earned his B.S. in forestry from the University of Illinois, an M.B.A. from Oklahoma State University, an M.S. in forest biometrics from Virginia Polytechnic Institute and State University, and his Ph.D. in business administration from the University of Minnesota. He is Distinguished Professor Emeritus of Management and Decision Sciences in the E. Craig Wall Sr. College of Business Administration at Coastal Carolina University. Dr. Wathen's research interests include applied statistics, teaching methods, and manufacturing and service process design. Most recently, he published the article "Using Real-Life Major League Baseball Data in an Introductory Statistics Course" in the Decision Sciences Journal of Innovative Education.
William G. Marchal earned his B.S. in mathematics from the University of Dayton, his M.A. in mathematics from Catholic University of America, and his D.Sc. in operations research from George Washington University. He is Emeritus Professor of Information Systems and Operations Management at the University of Toledo College of Business Administration. Dr. Marchal has held visiting appointments at the University of Michigan and at George Mason University. He has worked at the Executive Office of the District of Columbia government, the George Washington University Institute for Management Science, and the U.S. Army Chemical Research and Development Center. He has also served as an associate editor of Naval Research Logistics.
Samuel A. Wathen earned his B.S. in forestry from the University of Illinois, an M.B.A. from Oklahoma State University, an M.S. in forest biometrics from Virginia Polytechnic Institute and State University, and his Ph.D. in business administration from the University of Minnesota. He is Distinguished Professor Emeritus of Management and Decision Sciences in the E. Craig Wall Sr. College of Business Administration at Coastal Carolina University. Dr. Wathen's research interests include applied statistics, teaching methods, and manufacturing and service process design. Most recently, he published the article "Using Real-Life Major League Baseball Data in an Introductory Statistics Course" in the Decision Sciences Journal of Innovative Education.
Content
1 What Is Statistics?
2 Describing Data Frequency Tables, Frequency Distributions, and Graphic Presentation
3 Describing Data Numerical Measures
4 Describing Data Displaying and Exploring Data
5 A Survey of Probability Concepts
6 Discrete Probability Distributions
7 Continuous Probability Distributions
8 Sampling, Sampling Methods, and the Central Limit Theorem
9 Estimation and Confidence Intervals
10 One-Sample Tests of Hypothesis
11 Two-Sample Tests of Hypothesis
12 Analysis of Variance
13 Correlation and Linear Regression
14 Multiple Regression Analysis
15 Nonparametric Methods Nominal Level Hypothesis Tests
2 Describing Data Frequency Tables, Frequency Distributions, and Graphic Presentation
3 Describing Data Numerical Measures
4 Describing Data Displaying and Exploring Data
5 A Survey of Probability Concepts
6 Discrete Probability Distributions
7 Continuous Probability Distributions
8 Sampling, Sampling Methods, and the Central Limit Theorem
9 Estimation and Confidence Intervals
10 One-Sample Tests of Hypothesis
11 Two-Sample Tests of Hypothesis
12 Analysis of Variance
13 Correlation and Linear Regression
14 Multiple Regression Analysis
15 Nonparametric Methods Nominal Level Hypothesis Tests