Quantitative Analysis for Decision Makers
Paperback Engels 2025 8e druk 9781292469850Samenvatting
Help your students understand how quantitative analysis supports effective management decision-making in today's fast-moving world
Quantitative Analysis for Decision Makers, 8th Edition, by Wisniewski, Shafti and Yeo provides an accessible introduction to the quantitative methods of analysis that are routinely used across the public and private sectors to support effective management decision making.
Adopting a learning-by-doing approach throughout, the text provides a clear explanation of each technique illustrating their practical application with the use of real data sets and with examples from government bodies and prominent businesses, including Google, Marks & Spencer, Tesla, Netflix, WWF and many more.
The text is suitable for business and management undergraduate and postgraduate students and for MBA students taking a quantitative course as part of their studies.
The new edition offers: Updated case illustrations from global business organisations like Tesla, Netflix, WWF, Google, Unilever Extended discussion of how artificial intelligence (AI) impacts on quantitative analysis and decision making. Updated ‘QADM in action’ case studies illustrating how organisations benefit from the use of analytical techniques in the real world. Coverage of recent developments such as Big Data and business analytics; multi-criteria decision analysis and data mining; agent-based simulation; data visualisation. Examples and cases have been updated to reflect global events such as the Covid pandemic and geopolitical uncertainties. Fully worked examples and exercises supported by Excel data sets to show how to approach a particular problem using the techniques
About the authors:
Mik Wisniewski has almost five decades of experience in Quantitative Analysis. He has taught at a number of leading universities, worked in both industry and government and has extensive consultancy experience in the UK and across Europe, Africa, the Middle East and Asia.
Dr Farhad Shafti is a senior academic with expertise in Management Science. He has extensive experience teaching in highly ranked universities, covering undergraduate, postgraduate and MBA studies in the UK and overseas.
Dr Wee Meng Yeo is a senior lecturer at Adam Smith Business School, Glasgow. He has considerable expertise in the areas of operations management, forecasting and inventory control and has worked in the UK and the Far East.
Pearson, the world's learning company.
Specificaties
Lezersrecensies
Inhoudsopgave
- 1 Introduction
- Decisions, decisions and more decisions
- Data, information and analysis
- So where does quantitative analysis fit in?
- So who uses quantitative analysis?
- What’s quantitative analysis got to do with managers and with me?
- Models in quantitative decision making
- Using the text
- Summary
- 2 Tools of the Trade
- Some basic terminology
- Fractions, proportions, percentages
- Rounding and significant figures
- Common notation
- Powers and roots
- Logarithms
- Summation and factorials
- Equations and mathematical models
- Graphs
- Log graphs
- Real and money terms
- Worked example
- Summary
- Exercises
- 3 Presenting Management Information
- A business example
- Bar charts
- Pie charts
- Frequency distributions
- Percentage and cumulative frequencies
- Histograms
- Frequency polygons
- Ogives
- Lorenz curves (Pareto diagrams)
- Time-series graphs (line charts)
- Z charts
- Scatter diagrams
- Radar charts
- Which chart to use
- General principles of graphical presentation
- Worked example
- Summary
- Exercises
- 4 Management Statistics
- A business example
- Why are management statistics needed?
- Measures of average
- Measures of variability
- Using the statistics
- Calculating statistics for aggregated data
- Index numbers
- Worked example
- Summary
- Exercises
- 5 Probability and Probability Distributions
- Terminology
- The multiplication rule
- The addition rule
- A business application
- Probability distributions
- The Binomial distribution
- The Normal distribution
- Worked example
- Summary
- Exercises
- 6 Decision Making Under Uncertainty
- The decision problem
- The maximax criterion
- The maximin criterion
- The minimax regret criterion
- Decision making using probability information
- Risk
- Decision trees
- The value of perfect information
- Worked example
- Summary
- Exercises
- 7 Statistical Inference: Making Sense of Sample Information
- Populations and samples
- Sampling distributions
- The Central Limit Theorem
- Characteristics of the sampling distribution
- Confidence intervals
- Other confidence intervals
- Confidence intervals for percentages and proportions
- Interpreting confidence intervals
- Hypothesis tests
- Tests on a sample mean
- Tests on the difference between two means
- Tests on two proportions or percentages
- Tests on small samples
- Inferential statistics using a computer package
- p values in hypothesis tests
- c2 tests
- Worked example
- Summary
- Exercises
- 8 Quality Control and Quality Management
- The importance of quality
- Techniques in quality management
- Statistical process control
- Control charts
- Control charts for attribute variables
- Specification limits versus control limits
- Pareto charts
- Ishikawa diagrams
- Six sigma
- Worked example
- Summary
- Exercises
- 9 Forecasting I: Moving Averages and Time Series
- The need for forecasting
- Approaches to forecasting
- Trend projections
- Time-series models
- Worked example
- Summary
- Exercises
- 10 Forecasting II: Regression
- The principles of simple linear regression
- The correlation coefficient
- The line of best fit
- Using the regression equation
- Further statistical evaluation of the regression equation
- Non-linear regression
- Multiple regression
- The forecasting process
- Worked example
- Summary
- Exercises
- 11 Linear Programming
- The business problem
- Formulating the problem
- Graphical solution to the LP formulation
- Sensitivity analysis
- Computer solutions
- Assumptions of the basic model
- Dealing with more than two variables
- Extensions to the basic LP model
- Worked example
- Summary
- Exercises
- 12 Inventory Control
- The inventory control problem
- Costs involved in inventory control
- The inventory control decision
- The economic order quantity model
- The reorder cycle
- Robustness of EOQ decision
- Assumptions of the EOQ model
- Incorporating lead time
- Some technical insights
- Classification of inventory
- MRP and JIT
- AI and inventory management
- Worked example
- Summary
- Exercises
- 13 Project Management
- Characteristics of a project
- Project management
- Business example
- Network diagrams
- Developing the network diagram
- Using the network diagram
- A technical point
- Gantt charts
- Uncertainty
- Project costs and crashing
- Worked example
- Summary
- Exercises
- 14 Simulation
- The principles of simulation
- Business example
- Developing the simulation model
- A simulation flowchart
- Using the model
- Worked example
- Summary
- Exercises
- 15 Financial Decision Making
- Interest
- Nominal and effective interest
- Present value
- Investment appraisal
- Replacing equipment
- Worked example
- Summary
- Exercises
Rubrieken
- advisering
- algemeen management
- coaching en trainen
- communicatie en media
- economie
- financieel management
- inkoop en logistiek
- internet en social media
- it-management / ict
- juridisch
- leiderschap
- marketing
- mens en maatschappij
- non-profit
- ondernemen
- organisatiekunde
- personal finance
- personeelsmanagement
- persoonlijke effectiviteit
- projectmanagement
- psychologie
- reclame en verkoop
- strategisch management
- verandermanagement
- werk en loopbaan