Probability Theory #1: Beta distribution

<p>The beta distribution is a continuous probability distribution for data with discrete outcomes. I&rsquo;ll use an example to help us understand it better. Let&rsquo;s say our store manager at the local supermarket did a stock count of the remaining green and red apples in the basket before closing the supermarket. Every day at 6 p.m. over the past month, the manager recorded the ratio of the green apples against all apples in the basket, and also the ratio of the red apples. If you lay out all the ratios on the x-axis and do a count of them as the y-axis, the numbers run continuously across the chart. If it runs continuously, we refer this distribution as a continuous probability distribution.</p> <p><a href="https://medium.com/datafrens-sg/probability-theory-1-beta-distribution-a-very-simple-explanation-1db5ff9600e2"><strong>Click Here</strong></a></p>