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@DataNgineering10 ай бұрын
aaand Sold Out! JK :)
@isaacfurlani80153 жыл бұрын
Clearly explained for a novice. Thank you, Josh. I really appreciate the time you've put into creating these. They're very helpful.
@statquest3 жыл бұрын
Glad you like them!
@anaswahid85205 жыл бұрын
You are technically sound and logically consistent Since you explain in depth Therefore I love watching your videos
@statquest5 жыл бұрын
Thanks! :)
@jackignatev5 жыл бұрын
Dude, your intros are incomparable!
@AboutOliver3 жыл бұрын
I'm definitely in the minority, I know that. But I really hate them.
@tianleizhou39475 жыл бұрын
Hi dude, your last sentence saved the rest of my day! I was struggling for hours figuring out the results calculated by quantile() on a vector of only 10 entries!!!
@statquest5 жыл бұрын
Hooray! I'm glad the video helped you figure what was going on. :)
@AntonFedorov-o3nАй бұрын
I liked your pronunciation and the absolute clarity of the presentation of information.
@statquestАй бұрын
Thank you!
@simpuruit52894 жыл бұрын
Thanks for the hard work. I didn't expect that intro from a Statistician LOL
@statquest4 жыл бұрын
:)
@pellurumanoj5195 жыл бұрын
Wow!!!! no one can explain quantiles and percentiles better than this explanation, at least I feel this way.
@statquest5 жыл бұрын
I'm glad you like the video so much! :)
@JoshKonoff13 жыл бұрын
Wow...This is literally the best movie I've ever seen. Thank you!
@statquest3 жыл бұрын
bam! :)
@peshalgoel74144 жыл бұрын
Stat Quest is special.....Yes it is!!
@statquest4 жыл бұрын
:)
@자본주의쟁이2 жыл бұрын
hahaha great lecture and you got good sense of humour which makes the whole video more entertaining :)
@statquest2 жыл бұрын
Glad you enjoyed it!
@grantsmith36534 жыл бұрын
I liked the level at which you explained this. It was easy enough for me to understand, but explained fully so I feel like I totally get it. Thank you!
@statquest4 жыл бұрын
Thank you very much! :)
@stavalfi3 жыл бұрын
"Quantiles and percentiles are just a metter of finding out how many values are less than the value you are interested in". Interesting. Thanks!
@statquest3 жыл бұрын
:)
@nourajamal8166 Жыл бұрын
Thank you so much for this video. This was really clearly explained as promised in the video's title. I watched so many videos before I found yours. None of the previous videos was well explained as yours . You are totally right when u said that StatQuest is special , YES IT IS!
@statquest Жыл бұрын
Great to hear!
@bestest434 жыл бұрын
If you consider the first element as 0th quantile, then how do you get 100th as you get 14/15 for the last one?
@statquest4 жыл бұрын
It doesn't really make sense to call the first element the 0th quantile because that means 0% of the data is equal to or less than that quantile.
@itsmichaelaforeal3 жыл бұрын
I'm staying for the intros (and the content, of course!)
@statquest3 жыл бұрын
BAM! :)
@stonededge5 жыл бұрын
How do you have the first blue dot being a 0.25 quantile at 3:07 and then suddenly becoming a 0.20 quantile at 5:05? I am a little confused, if the technical definition is that of a quantile being the amount of points less than itself. Thanks!
@statquest5 жыл бұрын
The difference is that when we are explicitly trying to find quantiles - 4 ways to divide the data into equal sized bins - we have to round to either the 25th, 50th or 75th quantile.. So that's what is going on at 3:07. Later, we are calculating percentiles (but calling them quantiles because that is what is commonly done - and I mention this at 4:16 ) and we don't have to round, so we call the point the 20th quantile, because that is what it is without rounding.
@satyaprakash7843 жыл бұрын
@@statquest Thank you for clearing it. I also had the same doubt.
@skartikey Жыл бұрын
Easy to understand and to the point. Thanks!
@statquest Жыл бұрын
Thank you! :)
@XY-yg1ci6 ай бұрын
very clear explanation!!! tks!
@statquest6 ай бұрын
Thank you!
@phucthinh31575 жыл бұрын
Dear Josh, so the top dot is 14/15 = 93% quantile? And we never have the 100% quantile? Supposed we have 1000 dots, the top is 999/1000 = 99.9% quantile, could we round it to say it is the 100% quantile?
@statquest5 жыл бұрын
Remember, there are a lot of ways to define quantile and percentile. One way to define it, used in this video, is the percent of values below a specific value. However, it's also defined as the number of values equal to or less than. In this case you'd have 100%.
@phucthinh31575 жыл бұрын
@@statquest thank you so much for the detailed explanation
@oleersoy65474 жыл бұрын
AWESOME BEGINNING!!!
@statquest4 жыл бұрын
Thanks! :)
@kakusniper6 жыл бұрын
Its a joy watching your stats videos. Thanks a lot.
@venkatramanirajgopal73645 жыл бұрын
At 3:37 can be related to Box Plots.
@statquest5 жыл бұрын
Yes! :)
@LUSCIOUSDUNCAN Жыл бұрын
just saw someone post a Q-Q plot with regards to the price of an asset and was like, "what the hell is a Q-Q plot? and what the hell is a 'quantile'?" only to find out that quantiles were related to percentiles which were a mathematical concept that i had always struggled with. i love love love math but percentiles were one of those things i just couldn't fully grasp. bookmarking this to my lil "education" folder so i can come back to this when i need it. thanks!! :^)
@statquest Жыл бұрын
bam! :)
@niknoor40446 жыл бұрын
Hi Joshua. Once again, a very good video! Any plans on making videos about quantile regression?
@naf7540 Жыл бұрын
Hi Josh, as usual, a super video, taking into account all the subtleties of quantiles/percentiles, Thank you!!
@statquest Жыл бұрын
Thank you! :)
@harshmalik34707 ай бұрын
What would i even do without you Josh
@statquest7 ай бұрын
:)
@IngridKen5 жыл бұрын
I'll be honest 50% of this video is what i need.
@carlosherrero4990 Жыл бұрын
What a great and clear way to teach! congrats :)
@statquest Жыл бұрын
Thank you! 😃
@Im-Assmaa2 жыл бұрын
Thank you so much. Your explanation is Top notch👌
@statquest2 жыл бұрын
Thanks! :)
@charlottet7548 Жыл бұрын
This is incredibly clear and well explained! Thank you!
@statquest Жыл бұрын
Thank you!
@IngridKen5 жыл бұрын
I have so much trouble with our teacher, he just inserted quartile, percentile, deciles and teach us in one subject and now its exam and were having trouble because its included in the test and we barely gets anything 😣
@ashishmulchandani87685 жыл бұрын
That's why god created youtube! :)
@bikashchandragupta63335 жыл бұрын
For the 4th blue Dot, which you are addressing as 25th percentile, there are 3 Dots below that Dot, so the percentage becomes 3/15*100= 20%. If I count that Dot also than will have 4/15*100 = 26.67%. Then why are you calling that Dor the 25th percentage, can't figure it out as you are saying 25th percentile means 25% of the data is equal to or less than that value.
@statquest5 жыл бұрын
In this part of the example, I call this the 25th percentile or 25% quantile, because the lines have divided the data into 4 equal portions. This makes the lowest line the 25th percentile, the middle line the 50th percentile and the highest line the 75% percentile. Dividing the data into four equally sized groups is just one way to determine quantiles. When you do it this way, you have to do some rounding because, as you noticed, there is no specific point that is exactly above 25% of the data, however, since each group of points is equally sized, we still call it the 25th precentile. Later, when I show how each data point can be considered its own quantile, you can be much more precise in defining the quantiles for each point. Does that make sense? The important thing to remember is that you should really only trust quantiles when there is a lot of data. When you have a lot of data, the differences among ways of determining quantiles are insignificant.
@bikashchandragupta63335 жыл бұрын
@@statquest For the data : 5, 10, 15, 20, 25, 30, 35, 40, 45, 50. I have calculated the Q1= 13.75, Q2= 27.5, Q3= 41.25 from the Percentile Formula P=(N+1)/100 and Excel also gives the same results. But by observing the data, it is 15, 27.5, 40 that devides the data into 4 equal parts, so Q1= 15, Q2= 27.5, Q3= 40 and my CASIO fx-991 EX calculator gives the same results. So, can you tell why is this absurdity and which answer should I take?
@oleersoy65474 жыл бұрын
Explanations are brilliant too!! NICE WORK!!
@statquest4 жыл бұрын
Thanks!
@shinhyelee31695 жыл бұрын
awesome explanation! Thanks a lot
@statquest5 жыл бұрын
Thanks! :)
@rahmanhi6 жыл бұрын
I was struggling to find out what Quantile means & finally got it! thank you.
@serdomal87965 жыл бұрын
5:44 i have the feeling that this kinda explains the central limit theorem, am i wrong?
@statquest5 жыл бұрын
It's a little different. For example, if you only had 3 points (point A, B and C), then the gaps between datapoints will be large and there would be a relatively big difference between the quantiles if one method said the first quantile was A and another method said the first quantile is B. But when there is tons of data, then the gaps between datapoints will be small and difference between A and B will be much smaller, so if one method says the first quantile is A and the other says it is B, those two values will be close to each other. Does that make sense?
@serdomal87965 жыл бұрын
@@statquest yeah totally, thanks
@mengfu64614 жыл бұрын
Is the blue point the 25th(3:09) percentile or 20th (4:56)? Thanks for answering.
@statquest4 жыл бұрын
Both! Starting at 0:36 I talk about how quantile and percentile have multiple definitions and multiple ways to be calculated. The point is that with quantiles and percentiles, if you have a lot of data, details are not important, the bigger picture is important. If you don't have a lot of data, then be very cautious with your conclusions.
@mengfu64614 жыл бұрын
@@statquest Got it! thanks for helping out
@Dominus_Ryder4 жыл бұрын
@ 3:25, why is the 0.75 quantile 7.3, instead of 7.5? The 0.25 quantile was 2.5...
@statquest4 жыл бұрын
The 75% quantile crosses the y-axis at 7.3.
@fkhan45046 жыл бұрын
Love watchng ur videos
@statquest6 жыл бұрын
Thank you so much! I'm really glad to hear you like the videos :)
@abnp4346 жыл бұрын
Nicely explained !! crystal clear !
@jimhawkins3006 жыл бұрын
do we always need to arrange data to ascending order for ungrouped data?
@statquest6 жыл бұрын
In practice, you can just call a quantile function on your data without having the pre-sort it. The quantile function will sort it for you.
@Cowwy2 жыл бұрын
Thank you for the clear explanation. :D
@statquest2 жыл бұрын
You're welcome!
@DS-nr9zc6 жыл бұрын
Can you go over hidden markov models? Love your videos btw.
@shubhamsharma146 жыл бұрын
very nice explanation
@statquest6 жыл бұрын
Thank you! :)
@kimi7082 жыл бұрын
Love your videos
@statquest2 жыл бұрын
Thanks!
@kennetharguedas23163 жыл бұрын
Thank you! clear and to the point!
@statquest3 жыл бұрын
Thanks! :)
@parthmadan6712 жыл бұрын
Thanks a lot.
@statquest2 жыл бұрын
Most welcome!
@KPT_0012 жыл бұрын
Thank you
@statquest2 жыл бұрын
:)
@mosama222 жыл бұрын
Thank you for the beautiful video :-)
@statquest2 жыл бұрын
Glad you enjoyed it!
@giovanavieira77085 жыл бұрын
loved this! thanks from Belém do Pará, in Brazil!
@statquest5 жыл бұрын
Muito obrigado! :)
@reytns16 жыл бұрын
Always clearly explaining!
@daringcalf Жыл бұрын
I never know the meaning of quantile until today.
@statquest Жыл бұрын
bam!
@troyliddell73735 жыл бұрын
Super dude. Keep them coming!!!!
@statquest5 жыл бұрын
Thank you! :)
@singrevolution6 жыл бұрын
Thanks for the video! Can you make one quantile regression, please
@statquest6 жыл бұрын
That's on the to-do list, but it might be a while before I get to it.
@omarabdelrahman44543 жыл бұрын
@@statquest "Waah, waah, waah". :(
@josevaldes74932 жыл бұрын
Thanks
@statquest2 жыл бұрын
:)
@rossxie98092 жыл бұрын
you said " quantiles are just the liens that divide data into equally sized groups". What equally-sized groups does the 25% quantile split the data into ?
@statquest2 жыл бұрын
When we look at all of the quantiles that we are going to use, so, in your case, you might look at the 25% 50% and 75%, you'll create 4 equally sized groups.
@agiledev5773 Жыл бұрын
Hi Josh, I don't understand the graph. Since the y-axis is gene expression, what is the x-axis? Also, what do you mean by gene expression on the y-axis? Are these types of gene expression?
@statquest Жыл бұрын
The data come from gene expression measurements made from mouse cells. So the y-axis is gene expression (how much each gene is transcribed) and the x-axis represents the specific mouse. If we had 2 mice, we'd have 2 columns of dots.
@subjord5 жыл бұрын
Thanks for the explanation. By the way, there is no difference between 0.5 and 50% since 50%=0.5. It's mathematically exactly the same, so both notations can always be used.
@statquest5 жыл бұрын
That's exactly right! :)
@roxyzhang62933 жыл бұрын
this intro is bomb
@statquest3 жыл бұрын
bam! :)
@witnessa7x3 жыл бұрын
I feel like I understood the video, but I feel like I'm missing a logical jump. We said that in a sample with fifteen data points the 50% quantile would have seven points below it, and seven points above it. Fair enough. 15/2=7.5, and perhaps that 0.5 comes from the line going through the median point itself. But this doesn't really seem to generalize well in the scheme you present at the beginning of this video. Perhaps its best shown by saying at 2:56 you highlight a purple point as being the 25% quantile because you've bisected twice. However, at 4:52 you refer to that same point as the 20% quantile, because three of the fifteen points are below it. Both approaches make some intuitive sense to me, but they give notably different results for quantile measurement.
@statquest3 жыл бұрын
Unfortunately, one of the annoying things about quantiles is that there are a ton of ways to calculate quantiles ( as I mentioned at 0:44 ) Depending on the number of values in your dataset, you end up with situations where it's not possible to groups that are exactly equal, so we have a lot of different formulas to deal with this, and that means we get small differences in the results. However, that said, when the dataset is large enough, the differences don't matter any more.
@tanjimrafi62114 жыл бұрын
Love your videos!!
@swarnabandi76704 жыл бұрын
Superb
@statquest4 жыл бұрын
Thans! :)
@KPT_0012 жыл бұрын
You save me thanks
@statquest2 жыл бұрын
Thanks!
@SunSan1989 Жыл бұрын
Dear Josh, Why do I get residual plots in some software after fitting line,where the X-axis is labeled 'Regular Residual' and the Y-axis is labeled 'percentile'? Is this a Q-Q plot of residuals?
@statquest Жыл бұрын
I don't know. I've never seen one before.
@jenevavergara41255 жыл бұрын
Hi thanks for the great video, do u have R tutorial on hoe to get the quantile from a fitted distribution?
@statquest5 жыл бұрын
I don't, but that's a great idea. :)
@jenevavergara41255 жыл бұрын
@@statquest would love to watch it from your channel soon
@ashishtiwari19124 жыл бұрын
I would like to see videos on time series- ARIMA Model,ACF and PACF plots
@tanyasingh27812 жыл бұрын
Considering the point where you mentioned "the terms quantile and percentile are used when we divide each datapoint in it's own group" , what happens when we have lets say 200 datapoints .... do we have 200 pecentiles ? If yes, do we plot all these 200 pecentiles in Q-Q plot ? I am really stuck at this ....
@statquest2 жыл бұрын
Usually we just use 100 percentiles.
@tohabin50646 жыл бұрын
tnx
@SirGeforce Жыл бұрын
I have a auestion. How can the blue point (4th from the bottom) be the 20th and 25th percentile at the same time?
@statquest Жыл бұрын
Rounding. With more data points, we'd end up with finer, more precise quantiles and percentiles.
@pratapseshachalam28595 жыл бұрын
awesome video. It's made my day :)
@statquest5 жыл бұрын
Thank you! :)
@alexiasantos55263 жыл бұрын
Hi Josh. There is a rule to decide the quantity of quantiles to separate the data? Or Can I just pick a random number independent of characteristic of data?
@statquest3 жыл бұрын
Generally speaking, the most commonly used are quartiles (dividing the data into 4 equally sized pieces) or percentiles.
@piotrszocik77754 жыл бұрын
Great explanation, have a nice day :)
@sepideh11112 жыл бұрын
Great explanation, just how 7% quantile is equal with 7 percentile! It make sense if they are different. Can you please explain? thanks
@statquest2 жыл бұрын
I'm not sure I understand the question. This video talks about how there is a strict definition of quantile, which is one thing, and then there is how the term is used in practice, which is different. In practice, the terms quantile and percentile are interchangeable.
@alexlee3511 Жыл бұрын
say if today i have 1000 samples, can i refer the third data point (2/1000) as 0.2% quantile or 0.2th percentile
@statquest Жыл бұрын
If you wanted to.
@RebeliousSapien3 жыл бұрын
i'm confused. if a quantile is dividing the data into groups of equal numbers of points how is, for example a .95 quantile achieving this? i get that at the .95 point it means %95 of my data points are below that "line" but where does the definition lie here ? how are the datapoints divided into equal points? because below that "line" you have %95 of you data and above it %5 ... the datapoints are not equally divided.
@statquest3 жыл бұрын
Depending on the number of values in your dataset, you end up with situations where it's not possible to groups that are exactly equal. In order to deal with this problem, there are a ton of ways to calculate quantiles ( As I mentioned at 0:44 ). However, that said, when the dataset is large enough, the differences don't matter any more.
@RebeliousSapien3 жыл бұрын
@@statquest thank you for replying. I think it's more clear now what quantiles are all about. thanks for the help
@wanhope36606 жыл бұрын
Awesome!
@jaysonklau36834 жыл бұрын
Thanks you ^^
@uiru29003 жыл бұрын
So the median has 7/15ths of the observations below it. How is it then the .5 quantile?
@statquest3 жыл бұрын
Because 7/15ths of the observations are below it and 7/15ths are above it, the median is right in the middle, and thus, the 0.5 quantile.
@uiru29003 жыл бұрын
@@statquest The first observation marks the 0% quantile, as there are 0 observations below it. The second observation marks the 7% quantile, because 1/15th (.666...) of the observations are below it. Following this logic... The eighth has 7/15 of the observations below it, and would be the 46%. I obviously understand that it is "in the middle" but I thought you were defining quantiles by what percentage of the observations are below them.
@statquest3 жыл бұрын
@@uiru2900 Unfortunately there are a ton of ways to define "quantile", however, one common way is
@milkywayandbeyond4 жыл бұрын
Is it possible for someone to score in the 100th percentile of a standardized test?
@statquest4 жыл бұрын
It depends on how, exactly, you define percentiles. In this video I demonstrate one of many methods. When there is a lot of data, all of the methods are going to give you very similar results, so it's no big deal. However, if you only have a small amount of data, it's worth trying different approaches.
@milkywayandbeyond4 жыл бұрын
@@statquest Thanks! So when someone says they scored in the 100th percentile of a large standardized test, did they actually score in a percentile labelled "the 100th percentile" or did they really score in the 99.6th and have it rounded up to 100?
@salma-hh1sf3 жыл бұрын
OMG so easy THANK YOU SO MUCH 😃😃❤️❤️❤️❤️❤️😍😍😍😍😍
@statquest3 жыл бұрын
You're welcome 😊
@python4beginners1643 жыл бұрын
Sir I have a question? How to find interquartile range when full dataset not given. Instead Q1,Q3, min and max values are given. Plz reply...
@statquest3 жыл бұрын
The interquartile range is the middle 50%, so the values between Q1 and Q3
@manaspeshwe82973 жыл бұрын
"Quantiles" when the data is considered to be 1. So, the Median is 0.5th quantile. "Percentiles" when the data is considered 100. the Median is the 50th percentile. "Deciles" when the data is considered 10. the Median is 5th Decile. right?
@statquest3 жыл бұрын
That's correct. But it is very common for people to use the terms interchangeably, so try to be flexible.
@canernm4 жыл бұрын
Hey and thanks a lot for your amazing videos, they've helped me a lot. One question regarding this one: "quantiles are just the lines that divide data into equally sized groups". Isn't that true only for the median? For example, the 75% quantile in your video splits the data into 2 groups, one with 3 observations larger than the 75% quantile and 11 observations smaller than it.
@statquest4 жыл бұрын
You are correct in that individual quantiles do not all separate the data into equally sized groups - however, all of the quantiles, taken together, divide the data into equally sized groups. So if someone said, "I divided the data with 4 quantiles" you would know that there were 5 equally sized groups.
@canernm4 жыл бұрын
@@statquest I see, thank you for the clarification! Have a great day.
@xoda3452 жыл бұрын
@@statquest Hi Josh, lets say that we divide the data in 4 quantiles, i,e 25 percentile,50 percentile, 75 percentile and 100 percentile. How can there be 5 regions? Should not there be 4 regions?
@statquest2 жыл бұрын
@@xoda345 I guess you could debate whether or not the 100 percentile is actually a quartile or not.
@GauravPadawe5 жыл бұрын
First we need to sort the data in this case.
@statquest5 жыл бұрын
My intention was that sorting would be implied by the way the data is put on the graph. However, you are correct, I probably should have stated it explicitly.
@GauravPadawe5 жыл бұрын
@@statquest No worries Sir. Very well explained tho.
@osamahassan70292 жыл бұрын
Hey, can you please recommend book for practicing your taught concepts?
@statquest2 жыл бұрын
Not yet. I'm writing one right now, though, and it should be out in early 2022.
@BeginnerVille Жыл бұрын
So, thers's no 100% percentile in the example, for the top only have 14 lower than it as 14/15 right?
@statquest Жыл бұрын
What time point in the video, minutes and seconds, are you asking about?
@BeginnerVille Жыл бұрын
@@statquest Thanks for notifying! At 5:03.
@statquest Жыл бұрын
@@BeginnerVille It's a toss up as to whether or not we have 0% percentile or a 100% percentile. We can have either one, but not both. So you can include the point in the calculation (1/15 = 0.07% or 15/15 = 100%) or not (0/15 = 0% or 14/15 = 93%). In this example, we don't include the point. Note: We can do it either way because usually these sort of divisions are only done with a lot of data, and one point doesn't make a big difference.
@BeginnerVille Жыл бұрын
@@statquest I like you referring back to the example showed in the video, it becomes much clearer! Thank you so much! (I felt like I heard a 'Bam!)
@statquest Жыл бұрын
@@BeginnerVille bam!
@abdulqaadir6510 Жыл бұрын
At 4:14 you said that point is the 25th percentile. At 4:58 you pointed at the same point and called it the 20th percentile? I don't get it
@statquest Жыл бұрын
It's just rounding. When we divide the data into just 4 quartiles, each one contains approximately 25% of the data, and we do the best we can. However, when we divide the data into smaller quantiles, we can be more precise. Does that make sense?
@abdulqaadir6510 Жыл бұрын
@@statquest Oh yes I get it!
@rodeooswald69403 жыл бұрын
lov it
@statquest3 жыл бұрын
Thanks!
@govamurali23094 жыл бұрын
At 2:05, how is the gene expression calculated as 4.5 and how is the scale for the axis choosen?
@statquest4 жыл бұрын
The scale is arbitrary. However, we pick 4.5 as the median because 50% of the measurements are below that value.
@govamurali23094 жыл бұрын
@@statquest thanks for your response, so we can pick 5 as the median as well and we can change the scale to 10 instead of how you chose the scale as 9 and the median as 4.5, am I correct?
@statquest4 жыл бұрын
@@govamurali2309 In this example, 5 is not a good value for the median because there are more observations with values < 5 than there are observations values > 5. In contrast, 4.5 is a good value for the median because there are an equal number of observations with values < 5 and observations with values > 5. If you changed the scale, then you would change the median value. However, we still want a value that splits the data such that there is an equal number of observations with values > median and observations with values < median.
@govamurali23094 жыл бұрын
@@statquest Thanks got it now :)
@statquest4 жыл бұрын
@@govamurali2309 Hooray! :)
@derrickjator92824 жыл бұрын
how are you getting the values of 2.5 & 7.3?
@statquest4 жыл бұрын
Those are just the y-axis values that correspond the the values at the different quantiles.
@rikoimade70423 жыл бұрын
this is the first video without "BAM!!"
@statquest3 жыл бұрын
It's an old one, pre-bam.
@adhiyamaanpon41684 жыл бұрын
hey josh..one doubt!! if someone says 1st quantile is 0.07..what should i interpret from that..does that mean below that value only 1 data point falls or something else?
@statquest4 жыл бұрын
It depends...however, usually that means 1% of the data are less than that point (0.07).
@adhiyamaanpon41684 жыл бұрын
@@statquest thanks man!!
@xiangyuanli18492 жыл бұрын
can I ask why 75% quantile is 7.3 instead of 7.5 ?
@statquest2 жыл бұрын
Because the value of the point, such that 75% of the data is below it, is 7.3.
@userjieranli5 жыл бұрын
cannot be more clear
@BrazilianDaftPunkFan2 жыл бұрын
Quantile Dingle
@statquest2 жыл бұрын
:)
@namelessunnamed65445 ай бұрын
😮
@kmishy Жыл бұрын
So quantile and percentile are same
@statquest Жыл бұрын
In theory they are different, but practically speaking, they are the same.
@kennguyen10665 жыл бұрын
12 thumb downs = 12 dudes couldn't tell the difference between quantile and percentile. 12-BAMS!!
@statquest5 жыл бұрын
Dang! :)
@lilyha24704 жыл бұрын
Hi Josh, do you have videos on Rstudio?
@statquest4 жыл бұрын
I don't, but maybe one day I will.
@danzinde2 жыл бұрын
How is percentage different from percentile?
@statquest2 жыл бұрын
A percentile implies that a percentage of data has smaller values. For example, the 6th percentile implies that 6% of the data has lower values. In contrast, 6% simply means 6% of the data share some feature. In other words, percentile has a narrower definition, and is a specific case of a percentage.