Poisson processes -- Example 1

[@sudiptasaha738]

First 3 are good and the last one is the best, interesting and entertaining. Cleared all doubts. Thank you sir.

[@phuongnguyen-kc8hi]

Part d is really interesting. Thank you so much professor.

[@prateeksharma9505]

thanks a lot sir.. you are a good teacher..

[@Mr.AsKaRo0o]

Can you help me with this question Professor? You are waiting for a bus to take you home. There are two buses you can take to get home: red buses arrive at an average rate of 4 per hour, and blue buses arrive at a rate of 5 per hour. You always take whichever bus comes first.determine [a] what is the average time you wait before catching a bus

[@dayjavu18]

Clear and helfpul explanation! Thank you!

[@khinayemyint2148]

Thank you for explain this.

[@kaiwen123]

thank you so much professor for the clear explanation

[@gdragon1268]

thanks so much :) was totally lost before watching this

[@diogoprudente6041]

The R statement is the code for Rstudio Rscript???

[@Ppooh002]

the answer to the last question needs a table or does one have to calculate from 26 down to 0? of course that cant be done but is that the general rule for answering such a question?

[@LawrenceLeemis]

One does need to calculate each of the probabilities from 0 to 26. This is where a language like R can be helpful. The ppois function calculates this quantity.

[@deadleaf1194]

Can't you use the definition of conditional probability to solve part d)? if so, how would you do it? Ty

[@johnnewman3221]

peru laye yelara vechrukkan

[@sudiptasaha738]

Yes, the nice memoryless property is playing the trick here.

[@sudiptasaha738]

I feel using conditional probability may be done, but not at all required due to the memory loss property of Poisson distribution.

[@sadhana2619]

thanks sir