WPC 300 Midterm 1 UPDATED Questions
and CORRECT Answers
Heuristic - CORRECT ANSWER - Learns by acting, uses trial and error, values
experiences, relies on common sense, seeks satisfying solutions
Analytic - CORRECT ANSWER - Learns by analyzing, uses step by step procedure,
values quantitative and models, builds mathematical models, seeks optimal solution
Data extraction - CORRECT ANSWER - Extract data from primary/secondary source
Data transformation - CORRECT ANSWER - Transform/clean data into proper format or
structure for the purpose of querying and analysis
Data load - CORRECT ANSWER - Load data into final target database, more specifically
as operational data store, data mart or data warehouse
Descriptive Modeling - CORRECT ANSWER - Basic plots of variables
Find patterns in data
Descriptive statistics
Correlations
Outliers
Sampling
Some data mining techniques - clustering
Explanatory modeling - CORRECT ANSWER - Develop model to understand a (causal)
relationship
Predictive analysis - CORRECT ANSWER - Linear regression
, Data mining
Classification
Decision tree
Association rule (market basket analysis)
Text mining
Simulation
Problem Framing - CORRECT ANSWER - Tell an interesting and complete story, find an
appropriate solution framework, routinize the procedure
Agile - CORRECT ANSWER - Empirical process control
Waterfall - CORRECT ANSWER - Defined process control
Hypothesis - CORRECT ANSWER - Educated Guess
Data - CORRECT ANSWER - Discrete, unorganized, raw facts
Information - CORRECT ANSWER - the transformation of those facts into meaning
Primary Data - CORRECT ANSWER - Survey, Interviews (marketing firm's telephone
interviews), Used a lot in marketing research
Secondary Data - CORRECT ANSWER - Firm's proprietary database, Internet data
(crawlers) [scarpy, beautifulsoup], Stock/capital market data (compustat, CRSP), Accounting
disclosure data (from 10k, 10Q)
Simulated Data - CORRECT ANSWER - Data based on assumption and simulation, Used
a lot in scheduling, routing and queuing
and CORRECT Answers
Heuristic - CORRECT ANSWER - Learns by acting, uses trial and error, values
experiences, relies on common sense, seeks satisfying solutions
Analytic - CORRECT ANSWER - Learns by analyzing, uses step by step procedure,
values quantitative and models, builds mathematical models, seeks optimal solution
Data extraction - CORRECT ANSWER - Extract data from primary/secondary source
Data transformation - CORRECT ANSWER - Transform/clean data into proper format or
structure for the purpose of querying and analysis
Data load - CORRECT ANSWER - Load data into final target database, more specifically
as operational data store, data mart or data warehouse
Descriptive Modeling - CORRECT ANSWER - Basic plots of variables
Find patterns in data
Descriptive statistics
Correlations
Outliers
Sampling
Some data mining techniques - clustering
Explanatory modeling - CORRECT ANSWER - Develop model to understand a (causal)
relationship
Predictive analysis - CORRECT ANSWER - Linear regression
, Data mining
Classification
Decision tree
Association rule (market basket analysis)
Text mining
Simulation
Problem Framing - CORRECT ANSWER - Tell an interesting and complete story, find an
appropriate solution framework, routinize the procedure
Agile - CORRECT ANSWER - Empirical process control
Waterfall - CORRECT ANSWER - Defined process control
Hypothesis - CORRECT ANSWER - Educated Guess
Data - CORRECT ANSWER - Discrete, unorganized, raw facts
Information - CORRECT ANSWER - the transformation of those facts into meaning
Primary Data - CORRECT ANSWER - Survey, Interviews (marketing firm's telephone
interviews), Used a lot in marketing research
Secondary Data - CORRECT ANSWER - Firm's proprietary database, Internet data
(crawlers) [scarpy, beautifulsoup], Stock/capital market data (compustat, CRSP), Accounting
disclosure data (from 10k, 10Q)
Simulated Data - CORRECT ANSWER - Data based on assumption and simulation, Used
a lot in scheduling, routing and queuing
