Exam Questions and CORRECT Answers
Data Analytics - CORRECT ANSWER - analyzing large amounts of historical data to
generate insights and to create predictive models
Business Analytics - CORRECT ANSWER - analyzing large amounts of historical data to
generate insights and to create predictive models while taking business content, tools, and
context into consideration
Descriptive Analytics - CORRECT ANSWER - [Hindsight]
Historical performance
Underlying question: What happened?
Methods: Mean, Median, variance, percent change, basic visualization
Predictive analytics - CORRECT ANSWER - [Insight]
Drivers of performance
Underlying Question: What might happen in the future?
Methods: Correlation, Regression, Forecasting
Prescriptive Analytics - CORRECT ANSWER - [Foresight]
Altering Performance
Underlying Question: What should I do next?
Methods: Regression, Experiments, Simulation, Optimization
Business Analytics: 4 step process - CORRECT ANSWER - Business Problem
Information Required/Data Identification or collection
Analysis tools
Decisions
, Business problem Step: 1 - CORRECT ANSWER - Asking the right question
select the most significant question
break down large problems into small digestible questions
develop a plan to answer each of those digestible questions
Information required/data identification or collection: Step 2 - CORRECT ANSWER -
Data mapping and preparation
identify appropriate data and map it to the digestible question
prepare and clean data
alternative data collection approaches
Analysis tools: Step 3 - CORRECT ANSWER - Data Analysis
select and apply the most appropriate statistical/analytical methods for each digestible question
develop useful/appropriate robust analysis
Decisions: Step 4 - CORRECT ANSWER - Decision Making
Integrate answers of multiple digestible questions to address a complex decision-making
problem faced by the firm
provide multiple scenarios
iterate step 2 through step 4 if needed
Why do we use Statistical Models? - CORRECT ANSWER - Functional Relation: y= f(x)
Statistical Relation: y1 = b0 + b1x1 +ei
Causes of variation that are based on random reasons that we cannot identify
Prediction VS. reality: the error represents the difference between the actual observation versus
the predicted observation.