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WPC 300 Final Exam Questions with Verified Answers Latest Update
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Principles of Problem Framing - Answer-Tell, find and routinize Tell an interesting and complete story - Answer-The problem you address should be meaningful Solution could be reused for related problems Assumptions, boundaries Find an appropriate solution framework - Answer-Break down the pro...

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  • October 21, 2024
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  • 2024/2025
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  • principles of problem framing answer tell find

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WPC 300 Final Exam Questions with
Verified Answers Latest Update
Principles of Problem Framing - Answer-Tell, find and routinize

Tell an interesting and complete story - Answer-The problem you address should be
meaningful Solution could be reused for related problems Assumptions, boundaries

Find an appropriate solution framework - Answer-Break down the problem into pieces
Iterative process (agile vs waterfall) Identify appropriate analytical/modeling techniques

Routinize the procedure - Answer-Documentation Next similar questions can be solved
quickly Build a system (macros, codes, programs)

Analytics - Answer-is the process of developing actionable decisions or
recommendations for actions based on insights generated from historical data

Primary Data - Answer-Survey Interviews (marketing firm's telephone interviews) Used
a lot in marketing research

Secondary Data - Answer-Firm's proprietary database Internet data (crawlers) [scarpy,
beautifulsoup] Stock/capital market data [compustat, CRSP] Accounting disclosure data
[ from 10K, 10Q]

Simulated Data - Answer-Data based on assumption and simulation Used a lot in
scheduling, routing and queuing

Data Extraction - Answer-Extract data from primary/secondary source.

Data Transformation - Answer-Transform / clean data into proper format or structure for
the purpose of querying & analysis

Data Load - Answer-Load data into final target database, more specifically an
operational data store, data mart or data warehouse

Descriptive Analytics - Answer-- This is a preliminary stage of data processing that
creates a summary of historical data to yield useful information and possibly prepare the
data for further analysis. Questions: (1) What happened? (2) What is happening?
Methods: (1) Standard reporting (2) Dashboards (3) Visual analytics Outcome: Well
defined business problems and opportunities

Diagnostic/Explanatory Analytics - Answer-- this is about looking into the past and
determining why a certain thing happened. This type of analytics usually revolves
around working on a dashboard. Question: (1) Why did it happen? (2) How did it

,happen? Methods: Inferential Statistics, Visual analytics Outcome: Discover/Understand
causal relationships of an outcome

Predictive Analytics - Answer-- Predictive analytics is the use of data, statistical
algorithms and machine learning techniques to identify the likelihood of future outcomes
based on historical data. The goal is to go beyond knowing what has happened to
providing a best assessment of what will happen in the future. Question: (1) What will
happen next? (2) Why will it happen next? Methods: (1) Data mining (2) Text mining (3)
Forecasting Outcome: Accurate projections of future outcomes and events

Prescriptive Analytics - Answer-- Prescriptive analytics answers the question of what to
do by providing information on optimal decisions based on the predicted future
scenarios. The key to prescriptive analytics is being able to use big data, contextual
data and lots of computing power to produce answers in real time. Question: (1) What
should be done about it? (2) Why should you do it? Methods: (1) Optimization (2)
Simulation (3) Expert systems Outcome: Best possible business decision and outcome

Predictive Modeling Applications - Answer-Predict water leakage in a city water pipe
network Predict when a person would go to depression Predict criminal activities at Los
Angeles by LAPD Predict performance for certain stock portfolios Forecast demands for
sales Predict if a customer is likely to buy certain product or services

Prescriptive Data Modeling - Answer-Prescribes the best course of action when making
complex decisions involving tradeoffs between business goals and constraints, using
optimization technology It basically uses simulation and optimization to ask "What
should a business do?" Prescriptive analytics is a combination of data, mathematical
models and various business rules.

Prescriptive Data Modeling Application - Answer-Used in producing credit score which
helps financial institutions decide the probability a customer paying credit bills on time
Asset management in utility companies Optimized operating conditions to maximize
productions and minimize risks Better utilize: capital, personnel, equipment, vehicles
and facilities

Analytics - Answer-Learns by Analyzing Uses step by step procedure Values
quantitative information and models Builds mathematical models and algorithms Seeks
optimal solution

Heuristics - Answer-Learns by acting Uses trial and error Values experience, effort
reduction Relies on common sense Seeks satisficing solution Fast and frugal May lead
to decision biases!

Decision Making Biases - Answer-We tend to believe or seek out information to
preserve our own opinions or beliefs This can cause a gap in how we reason and how
we should reason This causes us to make bad decisions Remember we make better
decisions using critical thinking and being bit analytical.

, Anchoring Bias - Answer-Over-reliant on first piece of information you hear Most of
buying decisions are affected by anchoring effect What do you think black Friday sales
are driven by? Have you ever wondered why retail price of a product tend to be $39.99,
not $40?

Bandwagon Effect - Answer-Group thinking, adopting a decision based on the number
of people who hold a certain belief. The most famous and commonly cited example of
Groupthink is how the US Navy treated the threat of a Japanese attack on Pearl Harbor
in Hawaii. Following a long line to dine in a famous restaurant - think Yelp

Clustering illusion - Answer-Tendency to see patterns in random events Gambler's
fallacy

Zero risk bias - Answer-Because we love certainty and hence ignore risk entity while
making decision What would you decide if you were offered the following two options?
Bet $10 to win a lottery $100 that has 50% chance of winning Bet nothing to get free
$10.

Availability Heuristics - Answer-Overestimate the importance of information that is
available. Example: After you see a movie about a nuclear disaster, you might become
convinced that a nuclear war or accident is highly likely. A person might argue that
smoking is not unhealthy as his father who lived 100 years was a chain smoker and
smoked 3 packs a day for 70 years!

Overconfidence - Answer-Too confident about your ability, especially when you are
considered an expert in your field. Example: A person who is convinced he is going to
get into Harvard and who only applies to Harvard. In this case, the overconfidence of
the person could result in him not getting into any schools if Harvard rejects him.

The endowment effect - Answer-is the phenomenon in which most people would
demand a considerably higher price for a product that they own than they would be
prepared to pay for it (Weber 1993). The endowment effect is a hypothesis that people
value a good more once their property right to it has been established.

The framing effect - Answer-is an example of cognitive bias, in which people react to a
particular choice in different ways depending on how it is presented; e.g. as a loss or as
a gain.

Sunk-cost Fallacy Bias - Answer-Individuals commit the sunk cost fallacy when they
continue a behavior or endeavor as a result of previously invested resources Example:
"I might as well keep eating because I already bought the food." "I might as well
continue dating someone bad for me because I've already invested so much in them."

Decoy Effect Bias - Answer-According to economic theory, we make decisions based
on what will have the most utility to us. Consumers will tend to have a specific change in

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