Suppose all you had was a history of user requests to the service desk. Would you be able to determine how many of those requests were honest?
I am looking at distribution of a certain data set (left). It has two peaks (this is called ‘bimodal’) therefore I suspect that those are two overimposed populations. How do I split the data, to rediscover the original two populations
We would all love to spot business problems early on, to react before they become painful. You can learn a lot by looking at past problems. Hence, understanding the nature of anomalies in data can bring substantial operational benefits and