Question

2. Give three examples for random variables in maritime sector. Consider examples of random walk in maritime sector and explain by a scenario.

Answer 1

one of the interesting things is that the origin of insurance was in maritime sector. As you know that insurance is used to cover any contingency so yes definitely maritime sector can offer many examples of random variables.

First

As you know the behaviour of ocean depends on weather and geography. And forecasting weather is nothing but modelling random events precisely to the extent we can. So yes the very nature of maritime activity allows a great deal of randomness.

Second

Risks due to man made factors(engineering failures). We know that nothing is 100% fail proof. Yes definitey with good engineering we can minimize the probability of failure of equipments but we cannot eliminate it. A boiler can go in overpressurised state due to failure of equipments that are responsible for managing pressure. So here we can introduce random variables as reliability variables which can model the failure rate of these equipments.

Third

Maritime industry also includes people working on ports. So there are lot of activities at ports. Continuous loading and unloading of heavy containers. Building and launching of ships/cruises etc. and various other activities involving heavy machinery which is operated by humans. The jobs are so stressful that any mistake would cost life and huge property damage.

So we can use probability models to study the effect of psychology or mental conditions of the crew working. So let's say there is a random variable 'X' which is experience in years of a crane operator. Now the more the expereince probability of failure reduces. There can be other variables as well ...how many hours a shift lasts mental and financial conditions of people working on ports. So these can be modelled to see the impact on the industry.

Random walk example would be-

weather state ( good or bad)

let's say its bad

now all protocols to operate in rough weather were followed(yes or no)

if yes( then was there any equipment failure?)

if no( what was the error ? was it responsible for accident?)

so these kind of scenarios can be modelled where we can assign probabilities to all these events.

I hope I am able to help you

Thanks