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You’re given a dataframe of students named <code>students_df</code>:

<code>students_df</code> table

<table>
<thead>
<tr>
<th>name</th>
<th>age</th>
<th>favorite_color</th>
<th>grade</th>
</tr>
</thead>

<tbody>
<tr>
<td>Tim Voss</td>
<td>19</td>
<td>red</td>
<td>91</td>
</tr>

<tr>
<td>Nicole Johnson</td>
<td>20</td>
<td>yellow</td>
<td>95</td>
</tr>

<tr>
<td>Elsa Williams</td>
<td>21</td>
<td>green</td>
<td>82</td>
</tr>

<tr>
<td>John James</td>
<td>20</td>
<td>blue</td>
<td>75</td>
</tr>

<tr>
<td>Catherine Jones</td>
<td>23</td>
<td>green</td>
<td>93</td>
</tr>
</tbody>
</table>
Write a function named <code>grades_colors</code> to select only the rows where the student’s favorite color is green or red and their grade is above 90.

Example:

Input:

<pre tabindex="0" class="chroma"><code>import pandas as pd

students = {&#34;name&#34; : [&#34;Tim Voss&#34;, &#34;Nicole Johnson&#34;, &#34;Elsa Williams&#34;, &#34;John James&#34;, &#34;Catherine Jones&#34;], &#34;age&#34; : [19, 20, 21, 20, 23], &#34;favorite_color&#34; : [&#34;red&#34;, &#34;yellow&#34;, &#34;green&#34;, &#34;blue&#34;, &#34;green&#34;], &#34;grade&#34; : [91, 95, 82, 75, 93]}

students_df = pd.DataFrame(students)
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def grades_colors(students_df) -&gt;
</code></pre>

<table>
<thead>
<tr>
<th>name</th>
<th>age</th>
<th>favorite_color</th>
<th>grade</th>
</tr>
</thead>

<tbody>
<tr>
<td>Tim Voss</td>
<td>19</td>
<td>red</td>
<td>91</td>
</tr>

<tr>
<td>Catherine Jones</td>
<td>23</td>
<td>green</td>
<td>93</td>
</tr>
</tbody>
</table>

Write a function to select only the rows where the student's favorite color is green or red and their grade is above 90.

Good Grades and Favorite Colors

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

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?

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