Understanding Survivorship Bias

What common misconception does the phrase 'they don't make them like they used to' illustrate?

• That only modern goods are durable

• That all past goods were of superior quality

• That past goods were cheaper

• That modern goods are always better

How does survivorship bias affect research conclusions?

• It eliminates the need for data analysis

• It causes incorrect conclusions by focusing on successful cases

• It leads to accurate results

• It ensures all data is considered

What did Abraham Wald's research on WWII planes reveal about survivorship bias?

• Reinforce areas with fewer bullet holes

• Reinforce all areas equally

• Ignore the least damaged areas

• Reinforce the most damaged areas

What percentage of billionaires have a full college education according to a 2017 analysis?

• 16%

• 50%

• 84%

• 100%

How does survivorship bias affect mutual fund performance analysis?

• It only considers successful funds

• It focuses on new funds

• It includes all funds

• It ignores successful funds

What is a consequence of ignoring survivorship bias?

• It ensures all voices are heard

• It clarifies causation

• It encourages overly optimistic thinking

• It leads to realistic expectations

Why is it important to distinguish between correlation and causation?

• Correlation always implies causation

• Causation is irrelevant in research

• Causation is the same as correlation

• Correlation does not imply causation

What should you consider when trying to avoid survivorship bias?

• Only successful data

• Missing data

• Data from a single source

• Ignoring outliers

Why is it important to choose accurate data sources?

• To focus on outdated data

• To ensure only positive results are included

• To omit negative results

• To ensure a complete and accurate analysis

What should you be cautious about when cleaning your data?

• Only keeping extreme values

• Understanding what outliers represent

• Ignoring extreme values

• Removing all outliers