JKISeason3-23_​sryu

<p><strong>Generating Synthetic Population Attributes</strong></p><p><strong>Challenge 23</strong></p><p><br><strong>Level: </strong>Easy to Medium<br><br><strong>Description: </strong>You are a social scientist who needs to create some synthetic data for an imaginary population consisting of 1000 people, including attributes <em>age</em>, <em>height</em>, and <em>weight</em>. Start by generating a Gaussian age distribution using a mean of 40 and a standard deviation of 10, then bin people into four age groups: 'Children', 'Young Adults', 'Adults', and 'Seniors’. For each group, generate heights using a beta distribution with realistic parameters. Categorize heights into three groups: ‘&lt; 160cm', ‘&gt; 180', and 'rest’. Based on the binned height information, generate weights using a gamma distribution that accurately models weight distributions per age group. Visualize the relationships and identify patterns and correlations within this synthetic population.</p>