Introduction
Technology
has two important implications in the business world :
1) It has made possible to collect huge amounts of data.
2) It has given more people the power and responsibility to analyze data and make decisions on the basis of quantitative analysis.
People entering the business world can no longer push all the quantitative analysis to the technical specialists. Instead, it has become a part of their daily jobs. Direct marketers, Hotel & airline industry, Financial planning services etc. are some of the businesses that have gained advantage using quantitative methods. The book primarily emphasizes on the use of quantitative methods to analyze data & make decisions.
An Overview
There are three important themes that run throughout the book.
1) Data analysis which includes the following subthemes:
·
Inference
· Relationships
2) Decision making which has the following subthemes
· Optimization
· Decision analysis
with uncertainty
· Sensitivity
analysis
3) Dealing with uncertainty, which requires a basic understanding of probability.Uncertainty has two subthemes:
· Measuring
· Modeling
The chapter also provides an overview of the following topics covered in the other chapters of the book.
·
Data Sets: Used to create graphical, tabular and
numerical summaries.
·
Probability: Basic rules of probability, normal and
binomial probability distribution.
·
Applying probability to decision
making under uncertainty.
·
Sampling and Statistical inference: Estimate one or
more characteristics of a population using a sample of that population.
·
Quality Control (Statistical process control):
Gathering data on processes and analyzing data using statistical techniques.
·
Regression Analysis: Used to study the relationship
between variables.
·
Times Series Analysis: Regression based forecasting,
extrapolation
·
Spreadsheet Optimization:Llinear programming
· Computer Simulation Models
Business problems are usually of complex nature and hence require powerful software to find solutions. Microsoft Excel being a very flexible, powerful and easy to use software package is the most heavily used spreadsheet package. It contains or has available add-ins that can handle complex problems or computing. Below is the list of add- ins and software packages that are used extensively throughout the book to solve various quantitative problems.
·
Solver – Utilizes powerful algorithms to
perform spreadsheet optimization.
·
Statpro – Is a statistical software package used to
generate statistical output such as histograms, scatter plots, and time series
plots.
·
RandFns – Used to generate random values
·
Solver Table – Used to change input data to
see how optimal solutions will change during analysis.
·
Decisions Tools Suite – A suite of excel add
ins used for analysis.
·
@Risk – Is a simulation that enables us to run
replications of a spreadsheet simulation.
·
Precision Tree – Is used to analyze decision
problems with uncertainty.
·
Top Rank – Performs a sensitivity analysis to see
which inputs have the largest effect on the output.
·
Best Fit – Used to determine the most appropriate
probability distribution for spreadsheet modeling.
·
Risk View –A drawing tool used to see what a
selected distribution will look like.
A preview of few examples from later chapters of the book illustrates the types of problems that can be solved using the various softwares.
There are 3 types of models:
·
Graphical models attempt to portray graphically, how
different elements of a problem are related.
·
Algebraic models specify a set relationship in a
very precise way.
·
Spreadsheet models are alternatives to algebraic
models, where various quantities are related in a spreadsheet with cell
formulas.
·
Define the problem.
·
Collect and summarize data.
·
Formulate a model.
·
Verify the model.
·
Select one or more suitable decisions.
·
Present the results to the organization.
·
Implement the model and update it through time.