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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

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?

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

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