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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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You have store credit of \(N\) dollars. However, you don’t want to walk a long distance with heavy books, but you want to spend all of your store credit.

Let’s say we have a list of books in the format of tuples where the first value is the price and the second value is the weight of the book -&gt; (price,weight).

Write a function <code>optimal_books</code> to retrieve the combination that allows you to spend all of your store credit while getting at least two books at the lowest weight.

Note: You should spend all your credit and getting at least 2 books, If no such condition is satisfied just return <code>empty list</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>N = 18
books = [(17,8), (9,4), (18,5), (11,9), (1,2), (13,7), (7,5), (3,6), (10,8)]

def optimal_books(N, books) -&gt; [(17,8),(1,2)]
</code></pre>

Write a function to retrieve the combination that allows you to spend all of your store credit while getting at least two books at the lowest weight.

Book Combinations

Data Structures & Algorithms

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
Book Combinations	Data Structures & Algorithms	Medium	Very High
Boarding Times Bias	Statistics	Medium	High
Hundreds of Hypotheses	Statistics	Medium	Medium

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