Statistical Thinking for Managers
J.A. John, David Whitaker, David G. Johnson
336 pages, parution le 01/09/2001
Résumé
All business activities are subject to variability. As a
consequence, managers and business students need the
ability to think statistically about how to deal with the
resulting uncertainty, and its effect on decision-making in
management and commerce. To give them that ability, there
is a growing recognition that we must change the way
business statistics is taught. Traditional texts tend to
focus on probability, mathematical detail, and heavy
computation, and thus fail to meet the real needs of future
business managers. Statistical Thinking for Managers takes
a very different, very practical, approach that presents
even sophisticated statistics concepts with a minimum of
mathematics. It focuses on statistical thinking and
discusses a range of topics that specifically apply to
managers in business. Its scenario-based, interactive
format and integrated use of Excel facilitate and reinforce
the learning experience. Through this innovative treatment,
readers will gain the ability to:
- Appreciate basic statistical ideas
- Use a scientific approach to problem solving
- Understand the nature of variability
- Use meaningful information to make informed decisions
- Think in terms of processes and systems and develop strategies for process improvementDesigned as an introductory text in business statistics, Statistical Thinking for Managers challenges the way students look at business problems and issues.
Contents
- Variation
- Airport Immigration
- Debt Recovery
- Fire Insurance
- Budget Deviations
- Red Beads Experiment
- Some Conclusions
- Data for the Beads Experiment
- Exercises
- Problem Solving
- A Scientific Approach to Problem Solving
- The Need for Data
- Deciding What to Measure
- Mapping the Process
- Cause Analysis
- Collecting Data
- Evaluating the Results
- Standardising and Planning for Future Improvements
- Exercises
- Looking at Data
- Types of Data
- Presentation of Data
- Rounding Data
- Effective Tables
- Graphs
- Bar Charts
- Pie Charts
- Pareto Diagrams
- Run Charts
- Stem and Leaf Diagrams
- Median, Range and Quartiles
- Box Plots
- Stratification
- Exercises
- Modelling Data
- Introduction
- Distributions
- Arithmetic Mean
- Standard Deviation
- Calculating the Mean and Standard Deviation
- Interpreting the Standard Deviation
- Descriptive Statistics
- Modelling Julia's Diner
- Distribution Shapes
- The Normal Distribution
- Normal Tables
- Exercises
- Attribute Data
- Analysing Attribute Data
- Looking at Margins
- Two-way Tables
- Binary Data
- Working with Proportions
- Working with Counts
- Exercises
- Sampling
- Collecting Data
- Sampling
- Sampling Concepts
- Choosing the Sample
- Sampling in Practice
- Random Sampling
- Non-random Sampling
- The Accuracy of Sample Estimates
- Data for the Wood Experiment
- Exercises
- Estimation
- Sampling Error
- Estimating a Proportion
- Sample size for Proportions
- Estimating a Mean
- Sample size for Means
- Unknown Population Standard Deviation
- Finite Populations
- What Affects the Margin of Error?
- Tests of Hypotheses
- Exercises
- Regression Analysis
- Introduction
- Scatterplots
- Relationships Between Variables
- Regression Analysis
- Least Squares Method
- Correlation
- Regression Assumptions
- Analysis of Residuals
- Unusual Observations
- Prediction from Regression
- Margin of Error
- Exercises
- Multiple Regression
- Introduction
- Multiple Correlation Coefficient
- Multiple Regression
- Polynomial Regression
- Using Dummy Variables
- Exercises
- Forecasting
- Introduction
- Time Series
- Identifying the Trend
- Estimating Seasonal Effects
- Exponential Smoothing
- Differencing
- Residual Analysis
- Forecasting Accuracy
- Exercises
- Statistical Process Control
- Introduction
- Processes
- Benefits of Reducing Variation
- Process Adjustment
- Common Cause Highway
- Three Sigma Limits
- Analysis of Patterns
- Stability and Predictability
- The 85/15 Rule
- Implementing SPC
- Data for the Dice Experiment
- Data for the Quincunx Experiment
- Exercises
- Control Charts
- Introduction
- Control Charts for Process Variables
- Interpreting the X-Bar and R Charts
- Individuals Chart
- Attribute Charts
- Exercises
- Improvement Strategies
- Monitoring the Process
- Sensitivity of Control Charts
- Specifications
- Specifications and Control Limits
- Process Capability
- Improvement Strategies
- Special Cause Strategies
- Common Cause Strategies
- Experimentation
- Data for the Helicopter Experiment
- Exercises
- Postscript
- Decisions Based on Data
- Thinking Statistically: the Key Principles
- What We have not Done
- Statistical Computing
- Bibliography and Further Reading
- Appendix A: Introduction to Excel
- Introduction
- An Excel Spreadsheet
- Entering and Editing Data
- Entering Formulae
- Absolute Cell References
- Inserting Rows and Columns & Formatting Cells
- Standard Functions
- Excel Add-ins
- Graphs and Charts
- Printing and Saving a Workbook
- Appendix B: Statistical Tables
- Normal Distribution
- Percentage Points of the t-Distribution
- Percentage Points of the X 2-Distribution
- Random Numbers
- Constants for Control Charts
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Chapman and Hall / CRC |
| Auteur(s) | J.A. John, David Whitaker, David G. Johnson |
| Parution | 01/09/2001 |
| Nb. de pages | 336 |
| Format | 17,6 x 25,3 |
| Couverture | Broché |
| Poids | 617g |
| Intérieur | Noir et Blanc |
| EAN13 | 9781584882480 |
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