The best part of this series is the clear English used without any accents. As an international person this helps me a lot in understanding the content. I look forward to watching all 365 Data Science videos. Also thank you very much for no advertisement breaks.
@@TawhidShahrior subjective to only you and a small minority. too strong of any accent is hard to understand and is far away from the normal phonetics. think about the way english sounds in typical pop music. Even singers from the U.K or other parts of the world drop their accents and speak "clearly." Yes, "clearly" as in easiest to understand.
At 5:54, you said Chi squared distribution is skewed to the left. But this distribution is typically skewed to the right. The shape of this distribution depends solely upon degrees of freedom. As degree of freedom approaches 90, the chi squared distribution resembles the Normal Distribution.
Way of Explaining and Summarizing concepts and its application of Distributiom is funnay and interesting to the learners watching other vedios. Thanks for contribution
Me: Ok, time to stop playing dota and get serious this semester, probability is no easy subject 365 data science: For example, take a competitive esport, like dota 2 Thanks 365, this really helps my addiction
I like how in this video it briefly touches on all the distributions, thanks a lot! But one thing, you didn't really explain normal distri except saying that many real life examples use it..
Thank you for sharing this informative video. I’m curious about the distribution pattern in the forex market. Assuming it’s represented graphically, what type of distribution does it exhibit?
Nice video... made things so easy to understand. At around 6 mins in the video, you mention that the Chi-squared distribution graph is skewed towards left. Should it not be skewed to the right? Please confirm. Thanks
If I have the race time/speed of runners, what sort of distribution would fit such data? Chi squared distribution skewed to the left and non negative. What is the distribution for data skew to the right?
The simulated distribution array (list of values) itself might not be sorted, but when you histogram it, it of course would have an order: y axis the count, x the measure binned
Oh my god!! The asymmetric Chi-squared distribution does not mirror real life events 🤦♂️🤦♂️🤦♂️🤦♂️🤦♂️ 5:59 😮😮😮😮it is what really matter. It should be the only thing to focus on in real life!!! 5:59
That's not correct. In nature what matters is the outliers. The normal distribution is ok for the weight of the bears. Do not say in nature. Say the weight of the bears can be normally distributed 4:09
Thanks for your interesting video. In the video below I buckle up a spring sheet of material. The shape looks like a flat bell shape or sine wave curve. It is bounded on the ends. I stress or compress it from the vertical axis. Is there any analogy in statistics that this models? I also do it in a V-shaped pattern. People say I am just plucked guitar strings. I said you can not make structures with vibrating guitar strings or harmonic oscillators. ua-cam.com/video/wrBsqiE0vG4/v-deo.htmlsi=waT8lY2iX-wJdjO3 In the model, “U” shape waves are produced as the loading increases and just before the wave-like function shifts to the next higher energy level. Over-lapping all the waves frequencies together using Fournier Transforms, I understand makes a “U” shape or square wave form. If this model has merit, seeing the sawtooth load verse deflection graph produced could give some real insight in what happened during the quantum jumps. You can reproduce my results using a sheet of Mylar* ( the clear plastic found in school folders.
how would you do this Say you started a UA-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation. Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
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The best part of this series is the clear English used without any accents. As an international person this helps me a lot in understanding the content. I look forward to watching all 365 Data Science videos. Also thank you very much for no advertisement breaks.
Its a very subjective statement. Whats wrong with having accents? I dont ususally face problems understanding videos where speakers have accents lol
@@TawhidShahrior subjective to only you and a small minority.
too strong of any accent is hard to understand and is far away from the normal phonetics.
think about the way english sounds in typical pop music. Even singers from the U.K or other parts of the world drop their accents and speak "clearly."
Yes, "clearly" as in easiest to understand.
No such thing as no accent
Even if you speak native English, you still have an accent-the accent of the native speaker.
Everyone has an accent. Why does your comment feel backhanded
This video is pure gold. Thank you so much for sharing this! I'm a Mathematics major, presently undertaking Statistics courses and enjoying them.
At 5:54, you said Chi squared distribution is skewed to the left. But this distribution is typically skewed to the right. The shape of this distribution depends solely upon degrees of freedom. As degree of freedom approaches 90, the chi squared distribution resembles the Normal Distribution.
This video did a better job explaining random variable distributions than my prof could do in 10 hours of Lecture.
Very well done!
Thanks! I finally understand the concepts behind the formulas that my lecturer has been teaching. what a relief!!
This video really made the lightbulb light!!! Thank you.
Very Talented and skilled one 😮❤ A great teaching 😊 Thank you sir🙏
Your presentation was great. It will be helpful if you guide how you make them.
absolutely great video! I have been trying to figure out what my lecturer has been talking about for the past few days and you guys have saved me!
As a Statistics major student, this is life saver 😭💯
Way of Explaining and Summarizing concepts and its application of Distributiom is funnay and interesting to the learners watching other vedios.
Thanks for contribution
Pretty sure the chi-square distribution is typically right-skewed not left-skewed. 6:00
The explanation is simple to understand...Thanks, @365 Data Science Department...Keep Going
This channel is so underrated
Outstanding didactics!! Congrats
Me: Ok, time to stop playing dota and get serious this semester, probability is no easy subject
365 data science: For example, take a competitive esport, like dota 2
Thanks 365, this really helps my addiction
plot twist, playing Dota helps with learning probability
install Cold Turkey program in your computer.
Thank you so much. It was amazingly easy to understand. Good work.
Thanks for the content.
Cheers from Bolivia
How is the chi-square you are saying skewed to the left? In your picture it clearly looks right skewed
What a good channel!!! 5 Stars.
so helpful, thank you
clear and great explanation
Really good content... Great work
Great value for time
I like how in this video it briefly touches on all the distributions, thanks a lot! But one thing, you didn't really explain normal distri except saying that many real life examples use it..
thanks a lot for great explanation !
Uniform Distribution, Bernoulli, BInomial, Poisson.
Normal, T-Distribution, Chi-Square, Exponential, Logistics.
Thank you for sharing this informative video. I’m curious about the distribution pattern in the forex market. Assuming it’s represented graphically, what type of distribution does it exhibit?
Thankoy
Can you make these videos more descriptive
And how statistics is used in industry!
+100 yess please sir
Simply outstanding
Nice video... made things so easy to understand. At around 6 mins in the video, you mention that the Chi-squared distribution graph is skewed towards left. Should it not be skewed to the right? Please confirm. Thanks
I had also the same question. I checked again and as you said that it should be mentioned right-skewed.
Very good topic, Thank you very much!
absolutely great video!!
Tq so much ♥️
Great video 👍🏻
thank your for this clear and informatives vedios, one question please, what about gaussian distributian,where can we classified it ?
Thankyou sir.
Thank you so much
You look so good 😍 what a voice amazing skills ❤️
Thanks this video helped a lot
HELPFUL THANKS
When you work on stats for hours and found that video where he starts making an example with Lebron James, thank you man. + 1 like and + 1 follow
spectacular!
very informative! Can you please tell me which distribution is used in formula equations to find let's say coefficient of friction
Superb
5:59 Isn't this graph right-skewed?
Yes
thank you
thanks guys
Very helpful...thank you
perfect♥️
I can assure you that my teammates in dota doesn't give a fck about the win probability because they are fckn around during the first 10 mins 😂
Awesome ...
If I have the race time/speed of runners, what sort of distribution would fit such data? Chi squared distribution skewed to the left and non negative. What is the distribution for data skew to the right?
U r so kind😜
2:12
consider flipping a coin. both heads and tails are equally likely. why are not they then falling in the category of discrete distributions?
is this full course available on udemy?
Which Distribution should we use to predict General Assembly Elections of a country? For winning a single candidate or which party will gain majority?
While calculating probability do we care about order of distribution?
The simulated distribution array (list of values) itself might not be sorted, but when you histogram it, it of course would have an order: y axis the count, x the measure binned
@@oberlinio tx for clearance
Great Video ,
now how do i boost my mmr?
Great
The chi-square distribution is right-skewed. Not left skewed.
Which distribution should we use if we have to select exactly 2 out of 4 sample having certain probability?
Is chi square skewed to left or skewed to right?
He says in the video it is skewed to the left, where as I think it is skewed to the right ???
@@johandegroot7791 yeah. I checked. It is skewed to the right.
I just now completed my school.I am planning of studying Data Science.
Informative. See u around.
Isn't chi-squared right skewed?
Yep
Super
Is flipping a coin an example of uniform, or binomial distribution?
If more than once then binomial
Oh my god!! The asymmetric Chi-squared distribution does not mirror real life events 🤦♂️🤦♂️🤦♂️🤦♂️🤦♂️ 5:59 😮😮😮😮it is what really matter. It should be the only thing to focus on in real life!!! 5:59
Thaaaaaanks
Wow 🤩 Ure so cute
Great stuff, although you left out a lot of continuous distributions!
Typically skewed to the right?*
Geometric distribution ??
That's not correct. In nature what matters is the outliers. The normal distribution is ok for the weight of the bears. Do not say in nature. Say the weight of the bears can be normally distributed 4:09
I always forget about probability
Introduction to Probability Language
ua-cam.com/video/eqxozuUebaM/v-deo.html
You have explained everything instead of showing actual distributions!
ua-cam.com/video/M6014opxMo0/v-deo.html
Great work! But why is the probability of an international student becoming a captain is false? Why such pretexts?
Thanks for your interesting video.
In the video below I buckle up a spring sheet of material. The shape looks like a flat bell shape or sine wave curve. It is bounded on the ends. I stress or compress it from the vertical axis.
Is there any analogy in statistics that this models?
I also do it in a V-shaped pattern.
People say I am just plucked guitar strings. I said you can not make structures with vibrating guitar strings or harmonic oscillators.
ua-cam.com/video/wrBsqiE0vG4/v-deo.htmlsi=waT8lY2iX-wJdjO3
In the model, “U” shape waves are produced as the loading increases and just before the wave-like function shifts to the next higher energy level.
Over-lapping all the waves frequencies together using Fournier Transforms, I understand makes a “U” shape or square wave form.
If this model has merit, seeing the sawtooth load verse deflection graph produced could give some real insight in what happened during the quantum jumps.
You can reproduce my results using a sheet of Mylar* ( the clear plastic found in school folders.
how would you do this
Say you started a UA-cam channel about a year ago. You’ve done quite well so far and have collected some data. You want to know the probability of at least x visitors to your channel given some time period. The obvious choice in distributions is the Poisson distribution which depends only on one parameter, λ, which is the average number of occurrences per interval. We want to estimate this parameter using Maximum Likelihood Estimation.
Simulate 100 visits to your youtube channel, assuming that they will a Poisson distribution with a mean of 10 visits per minute. Plot the arrival time vs visitor index.
I think you just told us how
Lol yall didn't have to do Lebron's hairline like that tho
i love u
I didn't get head in any of the chances(in life)😒😪😔
URV gang
I still don't understand what us meant to "distribute" a price...I can't advance until I can fully explain what us meant by distribute
pls use common examples not games as not everyone knows every game
puwasungh
hi handsome you are awesome
I was 23 year old when I knew Poisson is pronounced as plason🤥
Thank You