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Business Analytics : Data Analysis and Decision Making / S. Christian Albright and Wayne L. Winston

By: Contributor(s): Material type: TextTextPublication details: New Delhi Cengage Learning India Pvt. Ltd. 2020Edition: 6th.edDescription: xxiv, 952p. : ill. ; 25cmISBN:
  • 9789353502553
Subject(s): DDC classification:
  • 23rd 658.40300285554 ALB
Online resources:
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Item type Current library Call number Status Notes Date due Barcode
Reference Book VIT-AP General Stacks 658.40300285554 ALB (Browse shelf(Opens below)) Not For Loan (Restricted Access) MGT 019527

It includes Appendix, References and Index pages

Students will master data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 6E! Popular with students, instructors, and practitioners, this quantitative methods text delivers the tools to succeed with its proven teach-by-example approach, student-friendly writing style, and complete Excel 2016 integration. It is also compatible with Excel 2013, 2010, and 2007. Completely rewritten, Chapter 17, Data Mining, and Chapter 18, Importing Data into Excel, offer increased emphasis on tools commonly included under the Business Analytics umbrella -- such as Microsoft Excel’s “Power BI” suite. Up-to-date problem sets and cases provide realistic examples to show the relevance of the material.

Table of Contents:

1. Introduction to Business Analytics.

Part 1: EXPLORING DATA.

2. Describing the Distribution of a Single Variable.

3. Finding Relationships among Variables.

Part 2: PROBABILITY AND DECISION MAKING UNDER UNCERTAINTY.

4. Probability and Probability Distributions.

5. Normal, Binomial, Poisson, and Exponential Distributions.

6. Decision Making under Uncertainty.

Part 3: STATISTICAL INFERENCE.

7. Sampling and Sampling Distributions.

8. Confidence Interval Estimation.

9. Hypothesis Testing.

Part 4: REGRESSION ANALYSIS AND TIME SERIES FORECASTING.

10. Regression Analysis: Estimating Relationships.

11. Regression Analysis: Statistical Inference.

12. Time Series Analysis and Forecasting.

Part 5: OPTIMIZATION AND SIMULATION MODELING.

13. Introduction to Optimization Modeling.

14. Optimization Models.

15. Introduction to Simulation Modeling.

16. Simulation Models.

Part 6: ADVANCED DATA ANALYSIS.

17. Data Mining.

Part 7: BONUS ONLINE MATERIAL.

18. Importing Data into Excel.

19. Analysis of Variance and Experimental Design.

20. Statistical Process Control.

Appendix A: Statistical Reporting.

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