What are some of the assumptions that go into predictive analytics?   What would happen if these assumptions are violated?

explain briefly the Predictive system concept

What factors contribute to the erroneous nature of the data? Is there anything specific you'd want to learn about any of them?

Senior executives at an oil company are trying to decide whether to drill for oil in a particular field. It costs the company $750,000 to drill. The company estimates that if oil is found the estimated value will be $3,650,000. At present, the company believes that there is a 48% chance that the field actually contains oil.  Before drilling, the company can hire an expert at a cost of $75,000 to perform tests to make a prediction of whether oil is present. Based on a similar test, the probability that the test will predict oil on the field is 0.55. The probability of actually finding oil when oil was predicted is 0.85. The probability of actually finding oil when no oil was predicted is 0.2. What is the EMV if the company hires the expert?

List two examples each of variation, foreseen uncertainty, and unforeseen uncertainty that you have personally experienced in your studies

What are the advantages of predictive analytics?

What is the primary distinction between business intelligence and analytics?

How does data modeling support the development of effective Business Intelligence (BI) systems?

In your view, which of these two terms—business intelligence or analytics—best describes the primary distinction between the two?

Do you think that the use of Statistics is important for a Business Analysis?