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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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<p>You’re analyzing a user’s purchases for a retail business.</p>

<p>Each product belongs to a category. Your task is to identify which purchases represent the first time the user has bought a product from its own category and which purchases represent repeat purchases within the product category.</p>

<p>The <code>id</code> in the <code>purchases</code> table represents the purchase order (rows with a lower <code>id</code> are earlier purchases).</p>

<p>Your code should output a table that includes every purchase the user has made. Additionally, the table should include a boolean column with a value of <code>1</code> if the user has previously purchased a product from its category and <code>0</code> if it’s their first time buying a product from that category.</p>

<p><em>Note: Sort the results by the time purchased, in ascending order.</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>purchases</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>product_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>product_category</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>product_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>category_previously_purchased</code></td>
<td>BOOLEAN</td>
</tr>
</tbody>
</table>
<p>Display results in the following way:</p>

<table>
<thead>
<tr>
<th>product_name</th>
<th>category_previously_purchased</th>
</tr>
</thead>

<tbody>
<tr>
<td>toy car</td>
<td>0</td>
</tr>

<tr>
<td>toy plane</td>
<td>1</td>
</tr>

<tr>
<td>basketball</td>
<td>0</td>
</tr>

<tr>
<td>football</td>
<td>1</td>
</tr>

<tr>
<td>baseball</td>
<td>1</td>
</tr>
</tbody>
</table>


Identify which purchases were users' first purchases within a product category.

Repeated Category Purchase

<p>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.</p>

<p>What factors could have biased this result, and what would you look into?</p>


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

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?

<p>You are testing hundreds of hypotheses with many <em>t</em>-tests. What considerations should be made?</p>


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

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
Repeated Category Purchase	SQL	Easy	Very High
Boarding Times Bias	Statistics	Medium	Medium
Hundreds of Hypotheses	Statistics	Medium	Low

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