Continuous Random Variables: Cumulative Distribution Functions
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- Опубліковано 25 лис 2012
- Watch more tutorials in my Edexcel S2 playlist: goo.gl/gt1up
This is the second in a sequence of tutorials about continuous random variables. I explain how to calculate and use cumulative distribution functions (CDFs).
Tutorials on continuous random variables
Probability density functions (PDFs): • Continuous Random Vari...
Cumulative distribution functions (CDFs): • Continuous Random Vari...
Mean & Variance: • Continuous Random Vari...
Median: • Continuous Random Vari...
Mode: • Continuous Random Vari...
Past Paper Questions: • Continuous Random Vari...
Watch more tutorials in my Edexcel S2 playlist: goo.gl/gt1up
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The way the material is being presented, beats KhanAcademy, which in my opinion was the superlative till now. Awesome. Thanks!
I am glad you found it helpful!
By the way, you can also find out D by using the fact that F(4) = 1. You can substitute x = 4 into the formula for F when x is between 2 and 4 and the answer should be 1. So this gives you another equation you can solve for D.
Let me know if you would like any further explanation.
Excellent description of the CDF, best I have seen sofar. Thanks a lot.
very nice and easy to understand,thanks!
thank you ! it is very helpful and easily understandable
Ty this is perfect !
Thank you very very much! It is very helpful!
I feel that i should thank you again, in another comment. Thank you!
Putting x = 2 into the formula for F when x is between 0 and 2 should give the same answer as putting x = 2 into the formula for F when x is between 2 and 4. Both give the probability of the random variable being 2 or less and this probability cannot suddenly change when you switch from one formula to the other. So as the two things should give the same answer, you can equate them to find out D.
If you look at the final answer, you'll see that you get F(2) = 1/3 using either formula.
Thank you, thank you, thank you. I finally see the big picture!
I was hoping you would show the relationship between CDF and central tendencies like mean median mode etc.
Thanks Very much Mr Nicholl, really really good teaching. Chapter 3 used to be a nightmare :)
These are covered in later videos in the series. Have a look in the video description for the links. (UA-cam doesn't allow me to paste them here.) Thank you for watching.
thank-u so much
ty so much
I don't quite understand the part at 17:07 where you have equated the integrated function to F(2) in order to find D. I would have thought that in order to find D you equate what you integrated (plus your substituted value of 2 for x) to 0. ?
Thanks MrNicholl
The PDF link doesnt work. How can we watch that
M Singh Sorry. I think this is fixed now.
Mean & Variance: gPAxuMKZ-w8
Median: lmXDclWMLgM
Mode: AYxZYPcXctY