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A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

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Write a function <code>get_ngrams</code> to take in a word (string) and return a dictionary of n-grams and their frequency in the given string.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>string = &#39;banana&#39; 
n=2
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = {&#39;ba&#39;:1, &#39;an&#39;:2, &#39;na&#39;:2} 
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>string = &#39;banana&#39; 
n=3 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = {&#39;ban&#39;:1, &#39;ana&#39;:2, &#39;nan&#39;:1}
</code></pre>

N-gram Dictionary

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 we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</code> table

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

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

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

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