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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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Let’s say we’re supporting an internal application that interacts with a company database, but we don’t have access to the app’s source code. We need to figure out which database tables are being used when the app fetches data for a user with ID 12.

How would you go about identifying which tables are involved in retrieving this user’s data?

How would you determine which database tables an application uses for a specific record without access to its source code?

Application Table Usage

Query Optimization

Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

Question	Topic	Difficulty	Ask Chance
Application Table Usage	Query Optimization	Medium	Very High
Boarding Times Bias	Statistics	Medium	Low
Hundreds of Hypotheses	Statistics	Medium	Low

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