Challenge 23 - Generating Synthetic Population Attributes

Create a workflow to generate synthetic data for an imaginary population consisting of 1000 people. The data should include attributes such as age, height, and weight.<br /><br />Generate Unique random ID for 1000 people.<br /><br />Generate Age Distribution using a Gaussian distribution with a mean of 40 and a standard deviation of 10, generate ages for 1000 people, then bin the dataset into four age groups: 'Children', 'Young Adults', 'Adults', and 'Seniors'.<br /><br />For each age group, generate heights using a beta distribution. Tune the parameters of the distribution to reflect realistic height ranges for each age group.. Categorize heights into three groups: 'less than 160', 'more than 180', and 'rest'.<br /><br />Based on the binned height information, generate weights using a gamma distribution. Adjust the parameters of the distribution to accurately model weight distributions for each height group.<br /><br />Utilize a scatter plot matrix to visualize the relationships between age, height, and weight. Identify any patterns or correlations within the synthetic population.