Probability and Statistic applications

[shilongo83]

application of probability

I am studying for the degree in Electronics Engineering, and in Maths I am being tought complex analysis and Probability & Statistics. On complex side I can familiarise it with its application such as Harmornic and and motors and all that but I fail to understand the application of Probability & Statistics in my field of study. my cousin asked me that question one day and I failed t provide a proper answer up until nw??

Can somebody please help. or wil I get to undersand it later as my studies continue?

 

[halls]

application of statistic

Imagine you work developing electronic devices, and you need to verify how many of the devices developed are working ok, and how many of them are malfunctioning. We are talking about 5000 devices, let's say. Are you going to test all of them one by one?

Here comes the statistics, where you take samples of let's say 100 devices and test them. Then you can set the parameters that define the devices as working. And then you can ESTIMATE (magic word related to statistics) how many of those 5000 will be working properly.

This is just one example.

I studied Electronics Engineering, specializing on Telecommunications. Estimating the traffic usage in a network needs statistics, because you cannot know for sure the traffic coming from each user, but you can estimate an overall.

Also on telephone networks, it is a MUST to know about statistics (talk about Poisson, Erlang, etc...)

So, maybe if you don't see many reasons now, you will be seeing them along these coming years

 

[shilongo83]

application of statistic

Thanx Halls.
Now that you mentioned poison, I didnt continous poison in Probability and Earlang in electronic communications, hopefully by the end of the course I will get better understanding.

Thanks again.

 

[harsha_jois]

application of probability in electronics

hi Shilongo83,
Poisson distribution is a probability distribution density function. over any given time period.
It is usually defined over cumulative densities.
The best example of a cumulative function is the number of packets. you may have seen the number on your connection balloon. Even if the connection is stagnant, the number of packets never decreases. it remains either constant or increases. the analysis of such entities needs cumulative density functions. we have a lot of such functions. I think you'll get to understand this when you begin wondering how many times you shoot the target of n trials or how many times you get a heads up on a toss. even betting has statistics.