When examining data, it is common to encounter bimodal distributions. This means that the observations are displayed as having two distinct peaks. This is often seen in financial data, where there may be two distinct groups or trends within the data set. It is important to identify and understand these bimodal distributions in order to accurately interpret and analyze financial data. This can be achieved through thorough data exploration and visualization techniques. By doing so, we can gain valuable insights into the underlying patterns and trends within the data, ultimately aiding in informed decision making.
