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Loose-Leaf for Applied Statistics in Business and Economics by Lori Seward and David Doane (2015, Ringbound)

About this product

Product Identifiers

PublisherMcgraw-Hill Education
ISBN-10125932852X
ISBN-139781259328527
eBay Product ID (ePID)19038482281

Product Key Features

Number of Pages864 Pages
Publication NameLoose-Leaf for Applied Statistics in Business and Economics
LanguageEnglish
SubjectStatistics
Publication Year2015
TypeTextbook
Subject AreaBusiness & Economics
AuthorLori Seward, David Doane
FormatRingbound

Dimensions

Item Height1.1 in
Item Weight52.9 Oz
Item Length10.8 in
Item Width8.4 in

Additional Product Features

Edition Number5
Intended AudienceCollege Audience
Grade FromCollege Freshman
IllustratedYes
Grade ToCollege Graduate Student
Table Of ContentChapter 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
SynopsisApplied Statistics in Business and Economics provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing students to know the why rather than just the how. Four distinct objectives have been met to follow this premise: Objective 1: Communicate the Meaning of Variation in a Business Context Objective 2: Use Real Data and Real Business Applications Objective 3: Incorporate Current Statistical Practices and Offer Practical Advice Objective 4: Provide More In-Depth Explanation of the Why and Let the Software Take Care of the How The emphasis of the 5th edition remains the same: thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing limitations of statistics.

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