An Introduction to Continuous Probability Distributions
Vložit
- čas přidán 22. 12. 2012
- An introduction to continuous random variables and continuous probability distributions. I briefly discuss the probability density function (pdf), the properties that all pdfs share, and the notion that for continuous random variables probabilities are areas under the curve.
I have understands more from your continuous probability distribution playlist than in 7 1-hour lectures at my college.
Just want to say that I really really appreciate your work and how you are saving my grades.
Thank you so much
im at a lost for words,when i think abt how much i appreciate ppl like u..thnks for making these videos.Your helping ppl acheive their goals...regardless of hw small a topic like this is. Thanks and Bless you. #from Jamaicawithlove
Samo David You are very welcome. I'm very glad that I can be of help. All the best.
This is Pure Gold
Same dan
I want you to know, that you are the reason I am passing Statistics.
+Reid Clark I'm glad I could help!
I just did too, I usually don’t understand in math classes, so when the exam times i am clueless what are even the material, but i just passed probability in good grade with only you’re videos and solving a previous, i am glad you exist👍
+1
You are very welcome! I'm glad to hear you got a good mark in your introduction to probability course! I have many videos on various topics in inference (and I'll be adding more) so you may very well find some that help you in your future courses. I'm very happy to do my little bit to help a few people around the world. Best wishes from Canada!
Man ive never found such a perfect maths lections channel in yt.
Fr the way everything is explained and how u lead on us to use logic more than memory is just how i learn and understand concepts in maths and tbh everything i have to study.
I just wish i'd found this earlier and not 2 days before my exam... Universities and schools need more teachers like u🙏
This is hands down the best explanation I've come across youtube on this topic!
This man is an Angel. Really need these type of people in my life. You make statistics look like a piece of cake for me.
I'm glad to be of help!
By far the the most understandable instructional videos on probabilities & statistics. Thank you!
Just came back to say that I passed my statistics/probability exam because of you. Thank you!
I've learned more from your videos in a few hours than I've learned from my professor in weeks...can't state enough how well you explain things in an easy to understand way, without diminishing the knowledge that is still expressed.
Thanks for the kind words! I try very hard to give you the real deal, just in an understandable way.
I have a final in two days that I would die to if I didn't have these videos. God bless
You're welcome! I'm glad you find them useful.
Your videos were a total lifesaver. Thank you. Excellent teaching abilities
Straight to the point, I love your "rulebook" format.
thank you, finally made it clear in my mind after weeks of studying!
You are a super saviour.. You save degrees, you build confidence in thousands, to know and grow. Tht's what is a teacher... I literally stay on leaves to finish your courses comfortably. Hats off!!
Thanks for the compliment! I'm glad to be of help.
jbstatistics, YOU ARE THE BEST THING ON CZcams!
This was extremely helpful and very clear in its explanation. Thank you.
Thank you a lot! This channel explains better than my professor.
I really do not have enough words to thank you. I just want to tell you that I got a high mark in introduction to probability and I owe you in lot for that :), of course I will study in next semester "Introduction to inference" and "Introduction to the sampling" and i will be waiting for your videos ..Thank you very much =)
your student from Oman
Wow, great series of videos. Very helpful, appreciate it!
+James Dwayne You're welcome!
Thanks! I'm glad to be of help.
I'm a nurse and in a beginning statistics class. It's killing me. We move very fast and understanding how to use all the formulas is tough for me. This video is helpful. I will try to track with you as I go through upcoming subjects.
I'm glad to be of help Stephanie!
Thank you so much, you helped me pass probability, those proffesors only come with shit, you made it all clear to me!
I'm glad to be of help!
Thank you very much for your videos! I will definetly spread your channel in my university :)
Thank you for the whole videos! Even if i'm french speaking and so i don't perfectly understand all, your videos stay much better than the others !
Je vous en prie!
Brief, clear and to the point. Thanks!!
You are very welcome!
I hope I have a teach like you in my real life!!!!! Thank you so much!!!
Even to this day, your videos help!
you can't imagine how much grateful i am for you
thanks a lot :D :)
You are very welcome.
Really easy to understand thanks!
thanks man you are an exam grade saver XD , Appreciate your help here
Wow! Great video and very easy to understand. Appreciate it! Can I get the pdf?
I study aerospace engineering at a pretty damn good university and you explain this material better than any professors or TA's around. Dank je wel :)
alstjeblieft :) I teach statistics at a pretty darn good university :)
Where do you teach?
Do you have a video on Gamma distribution?
Ahhh... You just save me :) Thank you very much
Thanks!
Great video...
Do you have a video about the sample distribution? I suggest make it
U always help me to further boost my concept@likesupplement professor. ##From Concordia University##
I'm glad to be of help!
jbstatistics If area under the curve represents - PROBABILITY, what does the y-value represent, It is very confusing please reply
GREAT VIDEO !
Hey, I was wondering if you would ever do online tutoring? I'm not a student at Guelph but I used to be! I wish I had you as a teacher then. I am studying econometrics now. Either way, thanks for the videos, I am using them as a stats review and I'm so grateful for how much work you've put into making this free content. -Megan
Or would you happen to know any other trustworthy higher-level stats youtube channels?
@@michipichu mitocw, >200 vids, go ahead
How many attempts does it take to complete one of your videos? Do you record all in one go? Nicely done!
I recorded my very early videos in one take, with a retake if required. But I upped the quality as I went along, and now break it up a bit. I record slide by slide, and I might have 20 or 30 minutes of record time for a 5 minute video like this one. Prepping beforehand and editing afterwards are the real time sinks.
me: straggling to understand continues variables.
jbstatistics: don't worry I got u
thanks a lot!!!
Thank you so much!
Thanks man, that helped.
Sir your videos are great...
If you are reading this please reply ok??
Let's say X is a continious random variable that takes the masses if animals in zoo.And those masses will be from 100 kg to 10000kg lets say.And when we model that how can we get the area under the curve to be 1????I have been confused on that since long.Please help
*applause*
Harshita Gupta Thanks!
Can a probability density function be discontinuous? Like, could the chances of a random variable assuming a certain value be greater or smaller by a significant amount than the values immediately next to it?
Sure. Even something as simple as the continuous uniform has discontinuities at the endpoints (where f(x) drops to 0). We could also have discontinuities "in the middle" (at non-endpoints of the support of the random variable). For a continuous pdf, the cumulative distribution function F(x) = P(X
Wow really useful
please make a video on beta distribution
NORMAL DISTRIBUTION CURVE ranges from 0 to infinity .?? or... + ,- infinity. anyone?
You are awesome
Great video. But what I don't get is why the area under the curve stands for the probability between two elements of the random variable
The function f(x) is defined to be the function such that the area between a and b is P(a
Now I get it. The PDF is the derivative of the Cumulative Distribution Function, so the area between two boundaries (a,b) is the probability that the random variable takes any value between a and b. Thanks!
Yes, that too :)
thanks teacher.
This video is really helpful ...cool stuff..
Great! I'm glad to hear you found this video helpful! All the best.
Wonderful videos!
Thanks!
thank you sir
Please make videos of bivariate distribution
thank you
well done. love it.
Heng zheng Heng fucking Zheng!
Thank youuu sooo much ^^
You are very welcome!
Now with just real world observations, how do you actually know f(x) to even draw the curve first. Only once you know f(x) you can get area under the curve. Now the real world observations may or may not fall into a normal distribution.
In the real world, we often use known probability distributions to approximate an (unknown) underlying reality. In practice, nothing actually has a perfectly normal distribution, but many variables have distributions that are approximately normal. This video is a brief introduction to the notion of continuous probability distributions, and yes, the given situations are simplified in the sense that we're assuming the distribution is known. But knowing the basics of these distributions is important, and later on we use these distributions to help us answer questions about an underlying reality.
What is the range of pdf?
Million likes for all of your videos
Thanks!
5 minuets Better than the 3 hours lecture ...
thank you so much!
You are very welcome!
👍
thank you for your video
You are very welcome Toyosi.
The video is great! but I still have something that is not clear for me you might can help me. Let's say that I have a continuos cumulative F(X), suppose F(0)=O, F(0)>0 and F(0)
I don't understand what you're asking me. F(x) = P(X
sorry is only F(0)=0 and F(0)>0
I don't completely understand why the area under a graph represents probability of something happening. Extending from discrete variables, their probability was not the area under the graph but rather just the corresponding value on the y-axis, why should it be any different here? I can intuitively see why any 1 value would have the probability of 0, but even then, where does the area under the graph come in?
Because the variable is continuous over the range under the curve.
you are awesome :D
I'm glad I could help!
Thanks, though I don't understand why the normal distribution is a continuous probability distribution. Isn't the height of Canadian dudes also a normal distribution even though those values are discrete?
I'm not sure what you are asking, and I don't know what you mean by "those values." Height in its nature is continuous. You've lived through every possible height from your height as a toddler to what you are now. There's a continuum of possible values. Sure, there are restrictions imposed by our measuring devices, but height is continuous by nature. Time is continuous by nature, but there can be situations where it's treated as discrete (week 1, week 2, etc.).
@@jbstatistics Oh OK. I guess I was thinking height is not continuous because each individual has a discrete height, but I guess that's wrong.
2:50 P(X=a)=0 makes sense mathematically (because a specific value is a line and has no area) BUT intuitively and practically it doesn't make sense. E.g. thinking about the heights as cont probability distribution, if one asks "what's the probability someone is 175cm?" that seems like a totally reasonable question but according to P(X=175cm)=0 the question shouldn't make sense. So where is the discrepancy here? Is this some inherent limit of this mathematical tool that somehow doesn't map onto our intuition of a perfectly reasonable question (at least seemingly) or is the question actually not reasonable to begin with? Thanks so much.
I wonder why maths is taught better on u tube than at university
I wish you my professor instead lol.
I'm gonna cry, I still don't understand
00:21 at 1.5x and you have a cattle auctioneer
I like your voice 😂
Thanks!
2:06 He's talking like many people made this mistake haha
Really easy to understand thanks!