ESCP Europe

Item type

Ebook

Language

English

Publication year

2025

Edition no.

8th ed.

ISBN

9781292469843

Note

• 1 user licence

Subjects

DATA ANALYSIS - MODEL - BUSINESS AND MANAGEMENT - DECISION MAKING

Quantitative Analysis for Decision Makers, 8th Edition, by Wisniewski, Shafti and Yeo provides an accessible introduction to quantitative methods of analysis to management decision-making, focusing on the practical application of the techniques rather than on mechanical calculation. A text blending academic and practitioner material, this all-in-one eTextbook offers leading textbook content and a range of digital tools, with integrated resources designed to support your learning.

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 .