Probability Distribution Functions - PMF, PDF and CDF (Clearly Explained!)
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- Опубліковано 22 чер 2020
- This tutorial of statistics provides with the intuition of Probability Distribution Functions - PMF, PDF and CDF. What are Random Variables? What are the Discrete Random Variables? What are Continuous Random Variables? Difference Between PMF (Probability Mass Function), PDF (Probability Density Function). What are CDF (Cumulative Distribution Function)?
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I have watched almost 5 videos of same topic from different channels but I didn't get, finally after 2 days UA-cam recommend me this video I don't know how to thankyou ❤️ just keep making videos
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Your channel is soo underrated. I was really having a tough time understanding these concepts but after watching your video I can say I have a concrete idea about these things. Thanks to you. Keep your good work.
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Best video I’ve ever watched that explains anything on UA-cam
You have saved me hundreds of hours.
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Just wow!!! This is the first time I truly understand probability density function. you nailed it man you have teardown the fabric to reveal the thread. Hats off, can't explain my satisfaction in words 💐💐
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Perfectly explained sir 😌 all the students definitely pray for the professor like u sir🙏
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Really clear explanation! Helped me understand the concepts much better. Thank you!
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i have seen around 20 videos , but your explanation is very precise and clear. thanks
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This video is so clear I even learned how to integrate from this
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understood, thank you
thank you so much. this video is very helpful in term of pmf, cdf and pdf.
Excellent, very clear 10/10
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Same here
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Best video on this topic. Thank you!
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Awesome! Very helpful, thanks
Thank you. These concepts are explained so well..
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Perfectly explained ☺️❤
Would be glad if u could do more sums !
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@Kody Baker Yea, I've been using flixzone for months myself :D
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Very well explained
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Life saver
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I wish I had this in college
for continuous random variable is pdf and cdf will be same ...confused in that .Kindly reply sir ..
The integration limit is very small for pdf (dx) whereas for cdf, the integration limit is from lower limit to upper limit.
@@confidencematrix couldn't able to get u sir ... can you explain it clearly ..if u r free now ...
what exactly is dx in CDF of continous random variable?
For continuous random variable unlike discrete, we have to integrate because the points of addition are infinite and cannot be added hence dx there represents the distance between 2 points and is infinitely small. :-)
👍❤️
Why u did not make much vidoes
try to use bright colors while writing please.
Thanks for the feedback! We will definitely incorporate your feedback.
CDF and pdf are same??
No. CDF is cumulative and PDF is a density function at a point (for a continuous variable a very small invlterval delta).
Brilliant explaination but I can't see anything
😂😂
i still don't understand yow cdf is different from pdf
I think sir has already mentioned that we can't find pdf for single point, where as we can find cdf of point( since cumulative of all lies in left side!!
L.ub.
?;?
)-0 c.
.
Awesome