Week 8 | Using R to work with performance data

Question 1

What real life example of limitations are there on measuring performance employee efforts?

Answer 1

There are often external events that are outside an employee’s control. For example, when COVID-19 hit no matter how much work people were doing there was no way that employee performance could be measured from their efforts.
- restrictions
- people got fired (no way to prevent this)

Question 2

How does criteria of performance metrics relate to previous content?

Answer 2

This relates to week 4 and 5 where financial metrics were covered.
- suitability
- criteria
- limitations of it (noisy, backward looking, less precise)

Question 3

What are the empirical properties of performance measures?

Answer 3

Validity
Concise
Sensitive - changes with behaviour
Low cost to measure and verify

Question 4

What are the downsides of data?

Answer 4

• Costly to measure
• Tricky to clean and arrange
• Challenging to meaningfully analyse

Question 5

What purpose does R-studio

Answer 5

R as a tool for cleaning, arranging,
visualizing, and analyzing performance
data

Question 6

What is R-studio a de-facto programming language for data science?

Answer 6

Open-source programming language, widely used in academia and industry
* Well-supported and documented – large, online community