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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?

Experiment Validity

Given a list of <code>stock_prices</code> in ascending order by <code>datetime</code>, and their respective dates in list <code>dts</code>, write a function <code>max_profit</code> that outputs the max profit by buying and selling at a specific interval and start and end dates to buy and sell for max profit.

Example:

Input:

<pre tabindex="0" class="chroma"><code>stock_prices = [10,5,20,32,25,12]
dts = [
 &#39;2019-01-01&#39;, 
 &#39;2019-01-02&#39;,
 &#39;2019-01-03&#39;,
 &#39;2019-01-04&#39;,
 &#39;2019-01-05&#39;,
 &#39;2019-01-06&#39;,
]

def max_profit(stock_prices,dts) -&gt; 27
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def max_profit(stock_prices, dts) -&gt; 
(27, &#39;2019-01-02&#39;, &#39;2019-01-04&#39;)
</code></pre>

Write a function to find the best days to buy and sell a stock and the profit you generate from the sale.

Buy or Sell

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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