WPC 300 MIDTERM UPDATED ACTUAL QUESTIONS AND
CORRECT ANSWERS
Question:
1. Heuristics
Answer:
• Experience
• Intuition
• Rules of thumb
• Think fast
Question:
2. Analytics
Answer:
the process of developing actionable decisions or recommendations for actions based on insights generated
from historical data
• Observe what has worked
• Experimentation
• Collect data and analyze data
• Find patterns
• Boundary and Generalizability
• Think slow
Question:
3. A Scientific Perspective to Problem Solving
Answer:
- Heuristics vs Analytics
Question:
4. Decision Making Biases
Answer:
- Understand situations where biases arise
- Based on a situation, you should be able to identify what kind of cognitive bias
that is
- Differentiate the major kinds of biases discussed
Question:
5. Analytics Process - Identify a problem
Answer:
- Interpret Results
- Find dataset (Data collection)
- Prepare data (ETL)
- Analyze data with a data model (Descriptive, Explanatory, Predictive, and Prescriptive)
, Question:
6. problem finding
Answer:
1. Tell an interesting and complete story
• The problem you address should be meaningful
• Solution could be reused for related problems
• Assumptions, boundaries
2. Find an appropriate solution framework
• Break down the problem into pieces
• Iterative process (agile vs. waterfall)
• Identify appropriate analytical/modeling techniques
3. Routinize the procedure
• Documentation
• Next similar question can be solved quickly
• Build a system (macros, codes, programs)
Question:
7. 4 squares of data collection
Answer:
cleaning communication analyses
Question:
8. Primary data
Answer:
• Surveys
• Interviews (marketing firm's telephone interviews)
• Used a lot in marketing research
Question:
9. Secondary data
Answer:
-- Beautifulsoup
• Stock/capital markets data (Compustat, CRSP, etc.)
• Accounting disclosure data (Form 10K, 10Q)
• Firm's proprietary databases
• Internet data (crawlers)
-- https://scrapy.org/
Question:
10. Simulated data
Answer:
• Data based on assumptions and simulations
• Used a lot in scheduling, routing, queuing
Question:
11. Survey Examples Examples of quantitative research that use
CORRECT ANSWERS
Question:
1. Heuristics
Answer:
• Experience
• Intuition
• Rules of thumb
• Think fast
Question:
2. Analytics
Answer:
the process of developing actionable decisions or recommendations for actions based on insights generated
from historical data
• Observe what has worked
• Experimentation
• Collect data and analyze data
• Find patterns
• Boundary and Generalizability
• Think slow
Question:
3. A Scientific Perspective to Problem Solving
Answer:
- Heuristics vs Analytics
Question:
4. Decision Making Biases
Answer:
- Understand situations where biases arise
- Based on a situation, you should be able to identify what kind of cognitive bias
that is
- Differentiate the major kinds of biases discussed
Question:
5. Analytics Process - Identify a problem
Answer:
- Interpret Results
- Find dataset (Data collection)
- Prepare data (ETL)
- Analyze data with a data model (Descriptive, Explanatory, Predictive, and Prescriptive)
, Question:
6. problem finding
Answer:
1. Tell an interesting and complete story
• The problem you address should be meaningful
• Solution could be reused for related problems
• Assumptions, boundaries
2. Find an appropriate solution framework
• Break down the problem into pieces
• Iterative process (agile vs. waterfall)
• Identify appropriate analytical/modeling techniques
3. Routinize the procedure
• Documentation
• Next similar question can be solved quickly
• Build a system (macros, codes, programs)
Question:
7. 4 squares of data collection
Answer:
cleaning communication analyses
Question:
8. Primary data
Answer:
• Surveys
• Interviews (marketing firm's telephone interviews)
• Used a lot in marketing research
Question:
9. Secondary data
Answer:
-- Beautifulsoup
• Stock/capital markets data (Compustat, CRSP, etc.)
• Accounting disclosure data (Form 10K, 10Q)
• Firm's proprietary databases
• Internet data (crawlers)
-- https://scrapy.org/
Question:
10. Simulated data
Answer:
• Data based on assumptions and simulations
• Used a lot in scheduling, routing, queuing
Question:
11. Survey Examples Examples of quantitative research that use
