Description

Book Synopsis


Table of Contents
Part I: Introduction and Descriptive Statistics 1. Introduction: Defining the Role of Statistics in Business 2. Data Structures: Classifying the Various Types of Data Sets 3. Histograms: Looking at the Distribution of Data 4. Landmark Summaries: Interpreting Typical Values and Percentiles 5. Variability: Dealing with Diversity Part II: Probability 6. Probability: Understanding Random Situations 7. Random Variables: Working with Uncertain Numbers Part III: Statistical Inference 8. Random Sampling: Planning Ahead for Data Gathering 9. Confidence Intervals: Admitting That Estimates Are Not Exact 10. Hypothesis Testing: Deciding Between Reality and Coincidence Part IV: Regression and Time Series 11. Correlation and Regression: Measuring and Predicting Relationships 12. Multiple Regression: Predicting One Variable From Several Others 13. Report Writing: Communicating the Results of a Multiple Regression 14. Time Series: Understanding Changes Over Time Part V: Methods and Applications 15. ANOVA: Testing for Differences Among Many Samples and Much More 16. Recent Developments 17. Chi-Squared Analysis: Testing for Patterns in Qualitative Data 18. Quality Control: Recognizing and Managing Variation 19. Statistical (Machine) Learning: Using Complex Models With Large Data Sets

Practical Business Statistics

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    A Paperback / softback by Andrew F. Siegel, Michael R. Wagner

    20 in stock

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      Publisher: Elsevier Science Publishing Co Inc
      Publication Date: 19/04/2022
      ISBN13: 9780128200254, 978-0128200254
      ISBN10: 0128200251

      Description

      Book Synopsis


      Table of Contents
      Part I: Introduction and Descriptive Statistics 1. Introduction: Defining the Role of Statistics in Business 2. Data Structures: Classifying the Various Types of Data Sets 3. Histograms: Looking at the Distribution of Data 4. Landmark Summaries: Interpreting Typical Values and Percentiles 5. Variability: Dealing with Diversity Part II: Probability 6. Probability: Understanding Random Situations 7. Random Variables: Working with Uncertain Numbers Part III: Statistical Inference 8. Random Sampling: Planning Ahead for Data Gathering 9. Confidence Intervals: Admitting That Estimates Are Not Exact 10. Hypothesis Testing: Deciding Between Reality and Coincidence Part IV: Regression and Time Series 11. Correlation and Regression: Measuring and Predicting Relationships 12. Multiple Regression: Predicting One Variable From Several Others 13. Report Writing: Communicating the Results of a Multiple Regression 14. Time Series: Understanding Changes Over Time Part V: Methods and Applications 15. ANOVA: Testing for Differences Among Many Samples and Much More 16. Recent Developments 17. Chi-Squared Analysis: Testing for Patterns in Qualitative Data 18. Quality Control: Recognizing and Managing Variation 19. Statistical (Machine) Learning: Using Complex Models With Large Data Sets

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