(eBook PDF) Business Statistics 4th Edition by Norean D. Sharpe

(eBook PDF) Business Statistics 4th Edition by Norean D. Sharpe – Digital Ebook – Instant Delivery Download

Product details:

• ISBN-10 ‏ : ‎ 0134705211
• ISBN-13 ‏ : ‎ 978-0134705217
• Author: Norean R. Sharpe; Richard D. De Veaux; Paul F. Velleman

Business Statistics, 4th Edition, by Sharpe, De Veaux, and Velleman, narrows the gap between theory and practice, by covering relevant and real-life statistical methods that help business students make good, data-driven decisions. With their unique blend of teaching, consulting, and entrepreneurial experiences, this dynamic author team brings a modern edge to teaching statistics to business students. Focusing on stats in the context of real business issues, with an emphasis on analysis and understanding over computation, the text helps students to be analytical, prepares them to make better business decisions, and shows them how to effectively communicate results.

Table contents:

PART I: EXPLORING AND COLLECTING DATA

1. Data and Decisions (H&M)
2. Visualizing and Describing Categorical Data (Dalia Research)
3. Describing, Displaying, and Visualizing Quantitative Data (AIG)
4. Correlation and Linear Regression (Zillow.com)

PART II: MODELING AND PROBABILITY

5. Randomness and Probability (Credit Reports, the Fair Isaacs Corporation, and Equifax)
6. Random Variables and Probability Models (Metropolitan Life Insurance Company)
7. The Normal and Other Continuous Distributions (The NYSE)

PART III: GATHERING DATA

8. Data Sources: Observational Studies and Surveys (Roper Polls)
9. Data Sources: Experiments (Capital One)

PART IV: INFERENCE FOR DECISION MAKING

10. Sampling Distributions and Confidence Intervals for Proportions (Marketing Credit Cards: The MBNA Story)
11. Confidence Intervals for Means (Guinness & Co.)
12. Testing Hypotheses (Casting Ingots)
13. More About Tests and Intervals (Traveler’s Insurance)
14. Comparing Two Means (Visa Global Organization)
15. Inference for Counts: Chi-Square Tests (SAC Capital)

PART V: MODELS FOR DECISION MAKING

16. Inference for Regression (Nambé Mills)
17. Understanding Residuals (Kellogg’s)
18. Multiple Regression (Zillow.com)
19. Building Multiple Regression Models (Bolliger and Mabillard)
20. Time Series Analysis (Whole Foods Market^®)

PART VI: ANALYTICS

21. Introduction to Big Data and Data Mining (Paralyzed Veterans of America)

PART VII: ONLINE TOPICS

22. Quality Control (Sony)
23. Nonparametric Methods (i4cp)
24. Decision Making and Risk (Data Description, Inc.)
25. Analysis of Experiments and Observational Studies

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