# Judging smiles

## Question

It's often hypothesized (and backed in some studies) that smiling can increase leniency, or reduce the effects of wrongdoing among other benefits.

A 1995 study by Marianne LaFrance & Marvin Hecht produced a dataset containing 4 different types of smiles, as well as the judge's leniency against judging wrongdoing when seeing these smiles.

The dataset can be interpreted as follows:

Smile:

• 1 - false smile
• 2 - is felt smile
• 3 - is miserable smile
• 4 - is neutral control

Leniency: a measure of how lenient the judgments were, higher means the judges were more lenient

Given the above information:

• Plot the leniency by smile type in a parallel box plot
• Based on the box plot above, which smile condition resulted in the highest leniency?
• Is the median leniency for the false smile lower than the 75th percentile leniency score for the neutral expression?

Below is code to import the dataset into a Google Colab or Jupyter notebook to help get you started:

``````# Here is code to pull the dataset and relevant libraries
# into a Google Colab or Jupyter notebook to help get you started
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns