Doane / Seward | Applied Statistics in Business and Economics | Buch | 978-0-07-337369-0 | sack.de

Buch, Englisch, 864 Seiten, Format (B × H): 218 mm x 285 mm, Gewicht: 1951 g

Doane / Seward

Applied Statistics in Business and Economics


Buch, Englisch, 864 Seiten, Format (B × H): 218 mm x 285 mm, Gewicht: 1951 g

ISBN: 978-0-07-337369-0
Verlag: McGraw-Hill Education - Europe

Applied Statistics in Business & Economics, 3rd Edition provides a comprehensive introduction to Statistics concepts and applications in business and economics. The text and online supplements emphasize thinking about data, choosing appropriate data analytic tools, and using computers effectively. The authors demonstrate easily mastered software techniques using the common software available.
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Autoren/Hrsg.

Doane, David
Seward, Lori

Fachgebiete

Weitere Infos & Material

Chapter One Overview of StatisticsChapter Two Data CollectionChapter Three Describing Data VisuallyChapter Four Descriptive StatisticsChapter Five ProbabilityChapter Six Discrete Probability DistributionsChapter Seven Continuous DistributionsChapter Eight Sampling Distributions and EstimationChapter Nine One Sample Hypothesis TestsChapter Ten Two Sample Hypothesis TestsChapter Eleven Analysis of VarianceChapter Twelve Simple RegressionChapter Thirteen Multiple RegressionChapter Fourteen Time Series AnalysisChapter Fifteen Chi-Square TestsChapter Sixteen Nonparametric TestsChapter Seventeen Quality Management

Doane, David
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.

Seward, Lori
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.

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