Practical Analytics

Many undergraduate programmes still require the students to take elementary mathematics, basic calculus, probability, statistics, and computer programming as part of their foundation education requirement. They may be waived if the courses had been taken at a sufficient level and good grades at high school. It is assumed that no matter what discipline students choose to major in, these analytical skills would complement strong language abilities to equip them to think and learn better in college. Consequently, they can progress to function with better competence in life and future careers. Many students, particularly those heading towards the arts, business or social science majors find the analytical courses challenging. They struggle to meet minimum requirements, but never want to be seen doing analytics again. Hence, the overall educational objective is not quite met.

At home and in the work place, computations nowadays are done using electronic calculators, computers, and more recently, the ubiquitous spreadsheets in personal computers and mobile devices. Deep thinking need not be confined to abstract algebra and calculus only. Diagrams, charts and mapping tools are now commonly employed. There are even computer application software with high levels of sophistication available to support visual analysis that any non-technical person can use with hardly any training. Of course, executives and managers can also called upon "quant jocks" to do the grunt work if needed. There is therefore the need to rethink about these general undergraduate analytical foundation requirements, or at least their course content and pedagogical approach.

Introduction

What is Practical Analytics?

Wikipedia
Analytics . Business Analytics
Data Analytics . Data Science . Big Data
Exploratory Search . Exploratory Analysis
Decision Analysis . Decision Science . Big Model
Problem Finding . Problem Solving

Search

Google
Analytics . Business Analytics
Data Analytics . Data Science . Big Data
Exploratory Search . Exploratory Analysis
Decision Analytics . Decision Science . Big Model
Problem Finding . Problem Solving

Why Practical Analytics?

Bennett 2011. Why Maths Instruction Is Unnecessary, TED
Flynn 2013. Why our IQ Levels are Higher than our Grandparents’, TED
Wolfram 2010. Teaching Kids Real Math With Computers, TED

Others

Wikipedia
Business Intelligence
Future Studies . Predictive Analytics
Design Thinking . Prescriptive Analytics

Search

Google
Business Intelligence
Future Studies . Predictive Analytics
Design Thinking . Prescriptive Analytics

Foundation

Software

Wikipedia
Data Analysis . Data Mining
Maths . Optimization
Discrete Event . Simulation . Stats
Software Engineering . Web Analytics
Data
MS PowerPivot . NodeXL
Ushahidi . XLMiner
Machine Learning
Commercial. Matlab . SAS
Open-source. Python . R . TensorFlow
Top 8 . Others . Best
Google . YouTube
Reports and Dashboard
Achema . Actuate . SpreadsheetGear
Spreadsheets
Business Spreadsheets . MS Excel . LO Calc . OO Calc
Statistics
@Risk, StatTools and DecisionTools . SAS JMP
SimTools.xla and Formlist.xla
R (or GNU S) . Intro . Contributions . Manuals
Spotfire S-Plus . Stat:Fit . StatistiXL . XLStat
Ottawa . Stanford . Toronto

Journal

Operations Research
Decision Sciences . European Journal of Operational Research
Management Science . Interfaces . ORMS Today

Book

Analytics

Davenport, Harris & Morison 2010. Analytics At Work: Smarter Decisions, Better Results, Harvard Business School Press
Davenport & Harris 2007. Competing on Analytics: The New Science of Winning, Harvard Business School Press
Evans 2012. Business Analytics: Methods, Models, and Decisions, Prentice Hall
Kepner & Tregoe 1997. The New Rational Manager, Princeton Research Press
Powell & Baker 2016. Business Analytics: The Art of Modeling with Spreadsheets, 6ed, Wiley
Ragsdale 2007. Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Business Analytics 5ed, revised, South-Western College
Thaler & Sunstein 2009. Nudges: Improving Decisions about Health, Wealth, and Happiness, Penguin Books (Book Site)

Business Modeling

Leong & Cheong 2015. Business Modeling with Spreadsheets, 3ed, McGraw-Hill (Book Site)
Powell & Batt 2008. Modeling for Insight: A Master Class for Business Analysts, Wiley
Savage 2012. Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty, Wiley (Book Site)
Taleb 2008. Fooled by Randomness: The Hidden Role of Chance in Life and In the Markets, Random House
Taleb 2010. The Black Swan: The Impact of the Highly Improbable, 2ed, Random House

Data Science & Machine Learning

Guttag 2016. Introduction to Computation and Programming Using Python: Application to Understanding Data
Machine Learning
Must Read . Amazon . Google
WikiBooks. Data Science: An Introduction

Project Management

Mantel, Meredith, Shafer, & Sutton 2010. Project Management in Practice, 4ed, Wiley
Meredith & Mantel 2011. Project Management: A Managerial Approach, 8ed, Wiley

Real Option

Mun 2005. Real Options Analysis: Tools and Techniques for Valuing Strategic Investments & Decisions, 2ed, Wiley
Mun 2003. Real Options Analysis Course: Business Cases and Software Applications, Wiley

Risk Analysis

Evans & Olson 2001. Introduction to Simulation and Risk Analysis, 2ed, Prentice Hall
Mun 2004. Applied Risk Analysis: Moving Beyond Uncertainty in Business, Wiley

Statistics & Decision Analysis

Barnett
2015. Applied Probability: Models and Intuition, Dynamic Ideas
2015. Applied Statistics: Models and Intuition, Dynamic Ideas
Evans 2012. Statistics, Data Analysis, and Decision Modeling, 5ed, Prentice Hall
Evans 2002. Essentials of Business Statistics, Prentice Hall

Education & Practice

Course

Coursera
Data Science at Scale, University of Washington
Python for Everybody
Applied Data Science with Python
Deep Learning
Mathematics for Machine Learning
Machine Learning
Project in Mining Massive Data Sets, Stanford University

Teaching

Beasley. OR-Notes

Learning

Coursera. Home Site
Penn . Johns Hopkins . Michigan
Stanford . San Diego . Duke
edX. Home Site
MIT . Harvard . Berkeley . Texas
Maryland . Queensland . British Columbia
Delft . Aachen . Australian National
Georgetown . Sorbonne . Boston
OpenCourseWare. Consortium
Carnegie Mellon . Harvard (Medicine)
Michigan . MIT . Oxford . Stanford . Yale

Practice

Companies
Pymetrics . Sigmoidal . Strong Analytics
Top. CIO . Datamation . Domo . Google
Blog. Towards Data Science
Wikipedia. Professional Fields
Business Analytics . Data Science . Operations Research
Computer Science . Systems Analysis
Industrial Engineering . Systems Engineering

Analytic Computing

Computer Programming

Wikipedia
Computer Programming
Software Development . Design . Engineering

Search

Google
Computer Programming
Software Development . Design . Engineering
YouTube
Computer Programming
Software Development . Design . Engineering

Numerical Analysis

Algorithms
Search Method. Binary . Linear . Interpolation . Recipes
Find Root. Methods
Bisection . False Position . Ridder
Newton-Raphson . Inverse Quadratic
Secant . Muller . Brent
Find Extrema
Fibonacci . Golden Section
Ternary . Successive Parabolic
Financial Numerical Recipes in C
Book (pdf) . Web Book
Numerical Recipes in C
Book (pdf)

Others

Wikipedia
Numerical Analysis . Topics
Computational Science . Iterative Method
Convergence . Discretization . Visualization

Search

Google
Numerical Analysis
Computational Science . Iterative Method
Convergence . Discretization

Visualization

Freeman 2013. Computer Program Reveals Invisible Motion in Video, Massachusetts Institute of Technology
Rosling, Hans (1948 - 2017)
Gapminder for a fact-based world view [Videos]

Others

Wikipedia
Data Visualization
Pattern Recognition . Tree Mapping

Search

Google
Data Visualization
Pattern Recognition . Tree Mapping
YouTube
Data Visualization
Pattern Recognition . Tree Mapping

Machine Learning

Crash Course
Computer Science. Lectures ...
34 Machine Learning . 35 Computer Vision .
36 Natural Language . 37 Robots .
38 Psychology . 39 Edu Tech . 40 Future
Statistics. Lectures ...
36 Supervised . 37 Unsupervised
38 Big Data Intro . 39 Big Data Problems .
40 Courts
Excel
Template . Google . YouTube
Lectures
MIT. Intro to Computational Thinking and Data Science
Lectures (Eric Grimson & John Guttag, 6.0002) ...
9 Experimental Data . 10 Data (2) .
11 Machine Learning . 12 Clustering .
13 Classification . 14 . 15
MIT. Artificial Intelligence
Lectures (Patrick H Winston, 6.034) ... 23
MIT. Machine Learning
Lecture Notes (Tommi Jaakkola, 6.867)
MIT. Introduction to Deep Learning
Lectures (Alexander Amini, 6.S191) ... 11
MIT. Statistics for Applications
Lectures (Philippe Rigollet, 18.650) ...
13 Regression ... 19 Principal Component ...
21 Generalized Linear Model ... 24
Michigan. Python 2.7 for Everybody
Lectures (Charles Severance, Coursera) ...
Stanford. Machine Learning
Lectures (Andrew Ng, CS229) ... 20 or
Lectures (Andrew Ng, Coursera) ... 19
Toronto. Neural Networks for Machine Learning
Slides and Notes (Roger Grosse, CSC321)
Lectures (Geoffrey Hinton, Coursera) ... 16.4

Others

Researchers
Leaders and Pioneers
Geoffrey Hinton . State of AI
Andrew Ng . State of AI
Wikipedia
Artificial Intelligence . Outline . Topics
Expert System . Intelligent Agent . Applications
Machine Learning . Deep . Outline . Portal
Supervised ML Algorithms
(Continuous) Regression . Linear . Polynomial .
Decision Trees . Random Forests
(Categorical) KNN . Trees . Logistic Regression .
Naïve-Bayes . SVM
Unsupervised ML Algorithms
(Continuous) Clustering . Dimensionality Reduction .
SVD . PCA . K-means
(Categorical) Association Analysis . A priori .
FP-Growth . Hidden Markov Model
ML Algorithms (Continue)
Neural Networks . Reinforcement Learning

Search

Google
Artificial Intelligence
Expert System . Intelligent Agent
Machine Learning . Deep Learning
ML Algorithms. Supervised . Unsupervised .
Neural Networks . Reinforcement Learning
ML Frameworks. Scikit Learn . TensorFlow .
Azure . Caffee . Theano . Spark . Torch and more
YouTube
Artificial Intelligence
Expert System . Intelligent Agent
Machine Learning . Deep Learning
ML Algorithms. Supervised . Unsupervised .
Neural Networks . Reinforcement Learning
ML Frameworks. Scikit Learn . TensorFlow .
Azure . Caffee . Theano . Spark . Torch and more

Analytical Methods

Mathematics

Function Approximation
Interpolation
2D. Linear . Bilinear . Piecewise
Cubic . Bicubic . Flat . Spline
3D. Trilinear . Tricubic
Extrapolation
Linear . Polynomial
Series. Power . Taylor . Fourier

Others

Mathematics
Interactive Mathematics
Mathematical Thinking
Online Math Learning
Wiki Portal . Wolfram
Wikipedia
Mathematics . Outline . Topics
Applications . Education
Necessary and Sufficient . Proof

Search

Google
Mathematics

Probability

Application and Derivation
Discrete. Uniform
Bernoulli . Binomial . Poisson
Continuous. Uniform . Normal
Beta . Exponential . Weibull
Wikipedia
Probability . Topics . Outline
Random Variable . Applications
Chain Rule . Conditional . Joint Probability
Confusion of the Inverse . Monty Hall Problem
Probability Distribution . List
Mass Function . Density Function . Cumulative
Chebyshev's Inequality . Empirical Rule
Discrete. Uniform . Bernoulli . Binomial . Poisson
Continuous. Uniform . Normal . Student's T
Beta . Exponential . Erlang . Gamma . Triangular . Weibull

Search

Google
Probability . Random Variable
Chain Rule . Conditional Probability
Confusion of the Inverse . Monty Hall Problem
Discrete. Uniform . Bernoulli . Binomial . Poisson
Continuous. Uniform . Normal . Student's T
Beta . Exponential . Erlang . Gamma . Triangular . Weibull

Statistics

Best 2001
Damned Lies and Statistics, University of California Press
Crash Course
Statistics
Fisher, Ronald Aylmer (1989 - 1962)
Design of Experiments . Statistical Methods
How Statistics Revolutionized Science [Book]
Leong 2015
Exercise: DataFit. Fitting data to statistical distribution
Exercise: HotelApex. Estimating demand distribution from sales [Teach]
Nightingale, Florence (1820 - 1910)
Statistics and Sanitary Reform
Vigen 2015
Spurious Correlations, Hachette Books

Others

Bell 2000. Teaching Business Statistics with Microsoft Excel, INFORMS Transactions on Education 1(1):18-26
DISCUS. Discovering Important Statistical Concepts Using Spreadsheets, Faculty of Engineering and Computing, Coventry University
Erkut & lngolfsson 2000. Let’s put the squares in Least Squares, INFORMS Transactions on Education 1(1):47-50
Johnson & Drougas 2004. Illustrating Type I and Type II Errors via Spreadsheet Simulation in the Business Statistics Course, Decision Sciences Journal of Innovative Education 2(1):89-95
Wikipedia
Statistics . Topics . Outline . Applications
Descriptive . Inference
Measurement . Random Variable
Univariate . Multivariate
Charts. Frequency . Venn . MECE
Pareto . Pie Chart . Tree Map
Stem and Leaf . Histogram . Box Plot
Summary Stats . Moment
Central Tendency . Dispersion
Standard Deviation . COV
Sampling . Standard Error . Central Limit
Estimation . Max Likely . Confidence Interval
Goodness of Fit . Kolmogorov-Smirnov
Inference . Hypothesis . Experiments
Null Hypothesis . Alternative
One- and Two-Tailed . Paired
Z Test . T Test . F Test . ANOVA
Regression . Linear . Logistics
Multivariate . Polynomial
Causation . Independence

Search

Google
Statistics . Topics . Outline . Applications
Random Variable . Univariate . Multivariate
Graphical . Pareto . Pie Chart . Tree Map
Stem and Leaf . Histogram . Box Plot
Sampling . Standard Error . Central Limit
Estimation . Max Likely . Confidence Interval
Goodness of Fit . Kolmogorov-Smirnov
Inference . Hypothesis . Experiments
One- and Two-Tailed . Paired
Z Test . T Test . F Test . ANOVA
Regression . Linear . Logistics
Multivariate . Polynomial
Causation . Independence

Decision Analysis

Hammond, Keeney & Raiffa 1998. The Hidden Traps in Decision Making, Harvard Business Review 76(5):47-58

Others

Wikipedia
Decision Analysis

Search

Google
Decision Analysis

Monte-Carlo Simulation

Leong 2015
Exercise. MontyHall. Evaluates probabilistic outcome [Teach]
Exercise. DataSim. Generating univariate random variates [Teach]
Exercise. Resampling. Generating of multivariate random variates [Teach]
Leong & Lee 2008. Spreadsheet Data Resampling for Monte-Carlo Simulation, Spreadsheet in Education 3(1):70-78
Leong 2007. Monte Carlo Spreadsheet Simulation using Resampling, INFORMS Transactions on Education 7(3):188-200

Others

Duckworth & Stevenson 2003. Resampling Methods: Not Just for Statistician Anymore, Iowa State University
Evans 2000. Spreadsheets as a Tool for Teaching Simulation, INFORMS Transactions on Education 1(1):27-37
Savage 2002. The Flaw of Averages, Harvard Business Review, November
Savage 2000. Blitzogram: Interactive Histogram, INFORMS Transactions on Education 1(2):77-87
Wikipedia
Simulation . Computer Simulation
Discrete Event . Monte Carlo
Random Variable . Variance Reduction
Random Number Generator . Sampling

Search

Google
Simulation . Computer Simulation
Discrete Event . Monte Carlo
Random Variable . Variance Reduction
Random Number Generator . Sampling
YouTube
Simulation . Computer Simulation
Discrete Event . Monte Carlo
Random Variable . Variance Reduction
Random Number Generator . Sampling

Optimization

Evans 2008. Some Practical Issues with Excel Solver: Lessons for Students and Instructors, INFORMS Transactions on Education 8(2):89-95
Fylstra, Lasdon, Watson & Waren 1998. Design and Use of the Microsoft Excel Solver, Interfaces 28(5):29-55
Peltier Tech. Avoiding Solver Reference Problem
LeBlanc & Galbreth 2007. Implementing Large-Scale Optimization Models in Excel Using VBA, Interfaces 37(4):370-382
Wikipedia
Optimization . Local Search
Genetic Algorithm . Heuristics

Search

Google
Optimization . Local Search
Genetic Algorithm . Heuristics
Massachusetts Institute of Technology. Operations Research Center

Data Analytics

Data Warehouse

Wikipedia
Database . Data Mart . Data Warehouse

Search

Google
Database . Data Mart . Data Warehouse

Big Data

LaValle, Lesser, Shockley, Hopkins & Kruschwitz 2011. Big Data, Analytics And The Path From Insights To Value, MIT Sloan Management Review 52(2):21-32

Others