Continuous Random Variables: Cumulative Distribution Functions

Показать описание

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

Рекомендации по теме

Комментарии

The way the material is being presented, beats KhanAcademy, which in my opinion was the superlative till now. Awesome. Thanks!

torwalk

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.

MrNichollTV

These are covered in later videos in the series. Have a look in the video description for the links. (YouTube doesn't allow me to paste them here.) Thank you for watching.

MrNichollTV

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.

MrNichollTV

Excellent description of the CDF, best I have seen sofar. Thanks a lot.

y

I feel that i should thank you again, in another comment. Thank you!

torwalk

I was hoping you would show the relationship between CDF and central tendencies like mean median mode etc.

racerx

Thanks Very much Mr Nicholl, really really good teaching. Chapter 3 used to be a nightmare :)

Virusj

very nice and easy to understand, thanks!

joshuac

Thank you, thank you, thank you. I finally see the big picture!

sitkin

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

Virusj

thank you ! it is very helpful and easily understandable

majdabdo

Thank you very very much! It is very helpful!

jhliang

The PDF link doesnt work. How can we watch that

mrsambhi

Mean & Variance: gPAxuMKZ-w8
Median: lmXDclWMLgM
Mode: AYxZYPcXctY

MrNichollTV

Continuous Random Variables: Cumulative Distribution Functions

Continuous Random Variables: Cumulative Distribution Functions

L08.7 Cumulative Distribution Functions

Cumulative Distribution Functions and Probability Density Functions

Cumulative Distribution Function of Continuous Random Variables

Calculating a Cumulative Distribution Function (CDF)

Continuous Probability Distributions - Basic Introduction

Continuous Random Variables: Probability Density Functions

Probability Distribution Functions (PMF, PDF, CDF)

Continuous Random Variable, the PDF and Cumulative Distribution Function

Find the Probability Density Function for Continuous Distribution of Random Variable

Understanding Continuous Random Variables and Probability Distributions

An Introduction to Continuous Probability Distributions

L08.2 Probability Density Functions

Finding Probabilities and Percentiles for a Continuous Probability Distribution

Probability Density Functions

How to find Cumulative Distribution Function from Probability Density Function PDF to CDF

Cumulative Distribution Function for Continuous Random Variables

Continuous probability distribution intro

How to find CDF from the PDF

Discrete Random Variable : How to find probability from a CDF.

Discrete and continuous random variables | Probability and Statistics | Khan Academy

Continuous Random Variables: Mean & Variance

Cumulative Distribution Function (1 of 3: Definition)

The mean, CDF and median from a continuous random variable