I see a lot of people are still confused on this video, so maybe my explanation will help. 68% of the population is within 1 standard deviation of the mean. 95% of the population is within 2 standard deviations of the mean. 99.7% of the population is within 3 standard deviations of the mean. So, if I ask you what the 50th percentile is in a data set, then its the mew or mean(same thing), so its the very center(where the 0 is on the video). if I ask you what the 40th percentile is it would fall within -1(SD) and the mean. if I ask you what the 80th percentile is it would fall between the mean and +1(SD) away from the mean. Hope this helps a little bit. Happy studying and glhf!!
it’s not a bad tutorial, so don’t let it distract u from the fact this help is better than none lmaoooo. stats final tomorrow morning and i’m just now learning les go
Let me try to explain these percentages for the students that are struggling with it. The good news, is this: It is NOT within your ability to calculate these percentages on your own and you will not be expected to. This is a problem that can only be solved through advanced integral calculus, and it is problem that only a small handful of calculus enthusiasts have the ability to solve. BUT, you better be damn clear about what these numbers mean. Suppose this bell curve is a dance floor, and suppose there are exactly 10,000 people crowded asshole to elbow on this dance floor. Then, the middle two boxes will have exactly 3413 people, each. And, the outer two boxes will contain exactly 1359 people each. Add these totals and subtract them from 10000 and the difference will be split between the two outermost boxes. 10000-3413--3413-1359-1359 = 456. The best example of all is to think of this bell curve as a an upside down picture of Hoover Dam. Then, these numbers would represent the total weight of the hydrostatic pressure behind each section of its wall. The only real challenge you must face is being able to calculate the area of the independent sections by subtracting them from the cumulative sum of the distribution function. What you are calculating is the "area under a curve"; or how many yard of carpet it would take to cover this dance floor. Area, is most often and most easily calculated by the formula AREA = WIDTH x HEIGHT, but this assumes a RECTANGULAR shape. This formula does not work for a triangle until you realize that every rectangle is made of two equal triangles. Hence the modified equation AREA = 1/2 WIDTH x HEIGHT, which is still easy to calculate because the change in length of the sloped side is still a straight line. If we change the sloped side of this wall to a semi-circular, most math students can still calculate the area based on the area formula for a circle, but it is definitely getting more challenging. Next, if we changed the curved wall to a parabola (like x-squared) then the precise area can only be solved by advanced integral calculus. And the slope, although no longer static, can be calculated. BUT, 'e' none as euler's constant (2.7173...) is based on infinite layers of change that are difficult to pin down even with integral calculus. Finally, the equation for the bell curve e^(-x^2) requires the calculation of an integral that is almost impossible to calculate. THIS IS WHY YOUR STATISTIC BOOK HAS LOVINGLY DISPLAYED EVERY POSSIBLE VALUE OF THIS CURVE'S AREA IN ONE OF ITS APPENDICES. But, if you are hell bent on pulling these numbers out of your ass then this is the least challenging way to do it:::(1) SUB-Divide the chart into as many smaller boxes as you can, and calculate the area for each 'micro-box' the way you would for a rectangle. (2.) Add the area EACH of the micro-boxes, and it will be a very accurate approximation of the actual area under the curve. As the number of boxes in your calculation approaches an infinite number of infinitesimally small micro-boxes, your approximation will become more and more accurate. This dilemma should serve to make you aware of the magic of calculus, but it is not something you should be sweating over. Many of You are thinking of it backwards. 34.13% is the definition of what 1 standard deviation is. STANDARD DEVIATION is a method of describing how closely the data points adhere to the curve. From looking at the symmetrical shape of the bell curve, you can all tell that the average value (expected value) is smack dab in the center. But, we can stretch or squeeze this graph to infinite proportions without changing this central value. So, the next most important thing to calculate is the average distance each data point veers from dead center. The seemingly random fact that the average swerving distance of each data point from its center lane is + or - 34.13% is the feature which defines 1 standard deviation in this case scenario, and 1 standard deviation of + or - 34.13% is the key feature of the normal distribution curve.
It's not confusing. He explained it well and everything you need to know is here. No need to blame your stupidity on others. You just need to practice.
@@lance4377 Watch the video he linked in the description, he explains how there's an assumption you know some basics of it, this video does it explain it okish, it is a bit confusing, but having a bit of knowlledge about what it's about makes it a bit easier to understand :) I hope this helps
Itʻs not, Slim. It could nicely be broken down into simpler steps. A good technique is to bump into a friend whoʻll pace you or to look at more than one version of the explanation from different books and videos. For instance, algebra gets taught in smaller doses, because textbooks teach it at a younger age. But the simpler approach is good for everyone; a smarter, advanced kid can breeze through it faster and get the job done. The opposite is not as helpful: cramming so much info into so little space! If the author skips examples for any so-called obvious steps, he loses readers in a hurry! The problem is, the readers tend to blame themselves and feel dumb, when in reality ANYONE reading over their head in ANY topic could feel the same way! Who wants to learn to swim by dangerously jumping in over their head? No need! Statistics could benefit from the same "thin slicing" of the lesson material!
Great video. I have a question. Does your data have to be normally distributed to use these charts? I have data grouped into categories (0,1,2,3,4,5), almost 50% of the data points fall into category 0, so it is very skewed. I'm guessing this data won't be suitable for a control chart.
Stephen MacDonald Correct, the data have to be normally distributed to be able to rely upon the categories/percentages displayed in the figure. However, if your data are non-normally distributed, you can still create a histogram and report the percentiles that correspond to your data, if you want.
The mean is ALWAYS your reference point and set to 0. When you right the date on your papers, how do you know what date to right. Or, how do you know how old the pyramids of GIZA are? ANSWER: You set the most significant event in recorded history to zero and describe EVERY date relative to this reference date. HENCE, BC, AD
You should probably clarify a bit better that those percentiles of 34.13% correspond to a standard normal curve of a sample with a standard deviation = 1, and are based in reality, because a lot of people seem to feel like you're puling them out of thin air. I think calculus 2 would help a lot with this concept and those of later areas of general stats.
Great introduction to a very important probability distribution. However, growth of biological tissue (including here human height) actually fits a log-normal distribution, which means that the logarithm of height is a normal variable. A bit of a nitpick, but there you have it.
if you have a life example with a mean of 3 and SD of 1.5 how do you calculate probability when everything past the second negative variable is impossible.
You set the mean equal to 0. This is what is meant by 'Standard' normal distribution. Pay no attention to the real value of your mean, but to how far to the left or the right your data points swerve
People get lost at the point with the percentages. Let me see if I can explain. Take a look at the x axis and imagine you have a tape measure. You can draw a length between the 0 and the 1. Let’s pretend that’s one foot. You can also draw one foot between the 1 and the 2. Right? Now imagine you have a scale. You take the slice of bell between the 0 and the 1. It will weigh something. Let’s pretend that’s one pound. If you were to weigh the slice of bell between the 1 and the 2 that is going to weigh less than a pound. There’s less stuff there, right? Consider that if you were to weigh the entire bell, it will weigh 100%. Just think about these concepts and I bet you get it. Try not to get bogged down in the actual numbers. Just try and understand the concepts here. These seemingly random percentages are actual properties of the bell curve that has been figured out by statisticians. I personally feel the guy in the video described this shit rather clearly without getting lost in the weeds.
These percentages are the area under the curve. In Probability + Statistics this is used to determine the probability of an event. These percentages are obtained by transforming a certain value into a Z value in the Z domain, which is restricted between -3 and +3. Each Z value has corresponding percentage of the area under the curve. These percentages can be cumulative or discrete. The entire Z domain is tabulated in the Z-table. Google it to see it.
Most people talk about the standard normal distribution, and in this case, it is always 1. The properties of the normal distribution are function of a particular probability density function, so you don't find the standard deviation, per se, it finds you ;-)
Let us consider marks in statistics test of 100 students of a class. Where mean (mu) is 50, i.e. the average marks of the class is 50. And let us consider that standard deviation is 10. So now, 68 students out of 100 will get marks within the range 40 to 60. (68% within the range of +,- 1 standard deviation) similarly 95 students out of 100 will get marks within the range 30 to 70 (in generic term 95% will fall under +,-2 standard deviations) and 99.7 students out of 100 will get marks within the range 20 to 80 ( in generic terms it's 99.7% will fall under +,-3 standard deviation).
Thank you so much for posting this video I am now understanding normal distribution and it much easier to level thanks to your video. The section was the most difficult part to understand and learning this online is such a struggle right now during the pandemic and I’m eternally grateful for this video. Thank you! - (from the statistic student who does not understand math at all)
There is no meaning to the 34.13%. It's simply the percentage of observations that correspond to 1 SD from the mean (one side of the distribution). Stated another way, asking why 34.13%? is like asking why is planet earth's circumference at the equator is 24,874 miles (40,030 km)? It just is.
People getting confused the moment you jump to z-distribution while introducing normal distribution at the very basics like its curve that looks bell shaped. This is more of a giant leap of mankind to the moon for a child who is newly born and yet to see the moon. The improved version of this still misses the point, however, yes histograms run in the background of normal distributions.
@@ajaymalik2835 calm down Karen. Nobody really cares what your bitch ass does for work. If you don't know when or how to use this then you really don't have a real job. Good day ma'am
@@CJJJCC I'm pretty sure u have a real full time job commenting on youtube btw who's comment did you copy, must be dissed pretty badly it seems, keep up the good work buddy.
How the hell did you get those percentages? The fact you didn't explain this made your whole video useless, thanks for wasting my time, on to the next.
Youre not expected to calculate them. It would be better to just understand what they mean. Those numbers define 1 and 2 standard deviations because they represent the average values in which the data points swerve to the left or the right
If I have two groups that I want to look into, one group is 677 with disability and the other is 17 265, with no disability can I say that this is not evenly distributed? I don't get it.
I would say the mean and standard deviation do not affect the normal distribution. Instead, they are simply descriptive properties of the normal distribution.
Those who use the normal distribution should always be aware that the independent values range from -infinity to +infinity. In reality, nothing has this range.
Good explanation about the ND intervals. Please explain the point of inflection, I heard it lies in 68.26. I want to know what the other points are called. i.e, 95.44% and 99.73%
How is it possible that The Mensa calculates wrongly that 2% of the people reach 148 IQ points.SD=24. So the right score is 149,32.The Mensa 148 IQ points 2,27% of the population.Also the chess metrics founder Jeff Sonas is totally wrong.The chess players average is 1400 SD=282,842 Jeff Sonas is using wrong SD=166,66.If you score 84,13% score in chess tournament you will get 282,842 points plus you opponents average
Remember, alpha and beta errors, confidence levels, as well as a minimum number of data points needed to reach 95% level. Its easy to forget that the ends of this curve are asymptotal and stretch out to infinity, and that the graph loses its ability to accurately represent data points at these extremes. For example, how would you evaluate the IQ of the smartest man who has ever lived? You might know that he's smarter, but would have no way to know how much smarter he is than number 2. His IQ would have no where to go because there aren't enough other people up there to compare him with. So, the question is how many more births will it take for him to be bested? If he turns out to be smarter than the next 10 billion people to be born, than his IQ will, or at least our assessment of it, will have doubled posthumously. The same problem exists for FIDE grandmasters. Magnus Carlson has what I believe is the highest rating in chess history, but is maxed out because there is no one else at the level left for him to win points from. The more distance he puts between himself and the pack, the fewer points he's award from each win.
I'm here because the last couple of meetings my teacher in stat didnt went in on our class and on last day before our test is when he just discussed this and is expecting us to learn it quickly in 1 hour for our test just 1 day after that like the f!
This is the bell curve!? Aaaahh! I've been hearing about it for so long and it was the statistics' course normal distribution! :o This is the thing used to show IQ differences between the sexes. Wow! So most people are within two standard deviations from the mean. Then, at the far right and far left you get people like Tesla and my boyfriend, respectively. :| I didn't picture myself saying this about anything related to statistics, but: Very cool!
HERE's an idea. If each of you cut out a picture of this curve and throw 100 darts at its center, the numbers he has provided are guaranteed to be almost the exact same number of holes made in each section.
it just mean 68% of the sample points falls within 1 standard deviation from the centre of the normal distribution curve, while 95% of the sample points falls within 2 standards deviation from the centre.
Sorry, your 68.26% and so on, are so OUT of scale. This exaggeratedly high curve promotes a misconception. Either the areas under the curve don't add up to 1, or you owe us a scale for the y values if you insist on using different ones than x. Why not use the correctly shaped (much flatter) curve, especially for struggling students? Since the 1stSD is correct in this case, the height of the curve at x =0 should be only ≈ .3989 -- do you realize how high you have it? [in your STAT 101 Tour of the ND it's even worse] It may not be your fault, (you were taught that way) but this would be a great place to fix it. PLEASE
You're just plain wrong here. If anything, the shape of the distribution used in the presentation is already too flat. It was the based shape I could find in powerpoint. Go ahead and simulate some normally distributed data (say, N = 5000) and check it out in a histogram. Ideally, you would have done that before making your comment, but that may not be your fault (you were taught that way).
clarklambert Here's what you get from N = 10,000: www.how2stats.net/2014/11/normaldistributionimage.html. It's possible that everyone else is wrong and you're right, but I don't see any evidence to suggest that's the case.
how2stats Switching from continuous to discrete just perpetuates the error. The point is the the y and x scales must match or you disturb both the area and the abscissa readings. Compare the exaggerated area to the left of a Z score of 1.5 on your curve, with the true standard normal (use a decent graphing app) and you'll see how yours overly flatters the subject because he thinks his score is better than (far too many) of the rest of the population. That's the point of graphing: to give an (accurate!) visual of relationships.
they are already tested and proven by mathematicians/statisticians before us. all we need to do is use those percentages we dont need to know how or where they come from unless you want to be a pinoneering mathematician yourself
If your class does shit on a test and you also do shit, for example class average is 22% and you get a 20% on a test, you get boosted up. If class does well and you do shit, you get dropped. the bell curve compares your grades against the others and thats how you get your grade. People take AP courses saying Il get boosted up even If i do shit thinking that they wont have to work as hard
I think you need to understand it much deeper before trying to explain it. It’s not the most difficult subject, however It sounds like you are just “copying and pasting” lecture notes which is not very effective.
I see a lot of people are still confused on this video, so maybe my explanation will help.
68% of the population is within 1 standard deviation of the mean.
95% of the population is within 2 standard deviations of the mean.
99.7% of the population is within 3 standard deviations of the mean.
So, if I ask you what the 50th percentile is in a data set, then its the mew or mean(same thing), so its the very center(where the 0 is on the video).
if I ask you what the 40th percentile is it would fall within -1(SD) and the mean.
if I ask you what the 80th percentile is it would fall between the mean and +1(SD) away from the mean.
Hope this helps a little bit. Happy studying and glhf!!
How to get these % ?
I literally didn't study at all so now I'm just watching videos to help me and my exam is tomorrow 🙃👌
so how did it go HAHAHA
I leaving this vid just as confused as when i first clicked it
So high school maths go over your head?
I thought it was me alone...DAMN
should i just skipped this vid then ?? hahah
it’s not a bad tutorial, so don’t let it distract u from the fact this help is better than none lmaoooo. stats final tomorrow morning and i’m just now learning les go
Final in t minus 3 hours, just learning :D
LOL same I'm so fucked tbh I got 1 and a half hours until my final
yo me too
@@brooktame3484 @Ayden Bergen
Update -
I passed with a 65.76 But I don't think it's passing, however, my stats grade is now a 67% so I'm good :)
Let me try to explain these percentages for the students that are struggling with it.
The good news, is this: It is NOT within your ability to calculate these percentages on your own and you will not be expected to. This is a problem that can only be solved through advanced integral calculus, and it is problem that only a small handful of calculus enthusiasts have the ability to solve. BUT, you better be damn clear about what these numbers mean. Suppose this bell curve is a dance floor, and suppose there are exactly 10,000 people crowded asshole to elbow on this dance floor. Then, the middle two boxes will have exactly 3413 people, each. And, the outer two boxes will contain exactly 1359 people each. Add these totals and subtract them from 10000 and the difference will be split between the two outermost boxes. 10000-3413--3413-1359-1359 = 456.
The best example of all is to think of this bell curve as a an upside down picture of Hoover Dam. Then, these numbers would represent the total weight of the hydrostatic pressure behind each section of its wall. The only real challenge you must face is being able to calculate the area of the independent sections by subtracting them from the cumulative sum of the distribution function.
What you are calculating is the "area under a curve"; or how many yard of carpet it would take to cover this dance floor. Area, is most often and most easily calculated by the formula AREA = WIDTH x HEIGHT, but this assumes a RECTANGULAR shape. This formula does not work for a triangle until you realize that every rectangle is made of two equal triangles. Hence the modified equation AREA = 1/2 WIDTH x HEIGHT, which is still easy to calculate because the change in length of the sloped side is still a straight line. If we change the sloped side of this wall to a semi-circular, most math students can still calculate the area based on the area formula for a circle, but it is definitely getting more challenging. Next, if we changed the curved wall to a parabola (like x-squared) then the precise area can only be solved by advanced integral calculus. And the slope, although no longer static, can be calculated. BUT, 'e' none as euler's constant (2.7173...) is based on infinite layers of change that are difficult to pin down even with integral calculus. Finally, the equation for the bell curve e^(-x^2) requires the calculation of an integral that is almost impossible to calculate. THIS IS WHY YOUR STATISTIC BOOK HAS LOVINGLY DISPLAYED EVERY POSSIBLE VALUE OF THIS CURVE'S AREA IN ONE OF ITS APPENDICES. But, if you are hell bent on pulling these numbers out of your ass then this is the least challenging way to do it:::(1) SUB-Divide the chart into as many smaller boxes as you can, and calculate the area for each 'micro-box' the way you would for a rectangle. (2.) Add the area EACH of the micro-boxes, and it will be a very accurate approximation of the actual area under the curve. As the number of boxes in your calculation approaches an infinite number of infinitesimally small micro-boxes, your approximation will become more and more accurate. This dilemma should serve to make you aware of the magic of calculus, but it is not something you should be sweating over.
Many of You are thinking of it backwards. 34.13% is the definition of what 1 standard deviation is. STANDARD DEVIATION is a method of describing how closely the data points adhere to the curve. From looking at the symmetrical shape of the bell curve, you can all tell that the average value (expected value) is smack dab in the center. But, we can stretch or squeeze this graph to infinite proportions without changing this central value. So, the next most important thing to calculate is the average distance each data point veers from dead center. The seemingly random fact that the average swerving distance of each data point from its center lane is + or - 34.13% is the feature which defines 1 standard deviation in this case scenario, and 1 standard deviation of + or - 34.13% is the key feature of the normal distribution curve.
Thank you!
this should be top comment; awesome explanation
Ok got it...
Thank you. that really helped.
In short, you are just calculating a selected area under the curve.
Ugh .... just going to fail my test
thats the spirit
Can we get an update
Honestly same
Yup its tomorrow and I just don't understand
I most definitely failed
So what you basically said is that I'm gonna fail?
did you fail ?
@@salma-hh1sf I actually passed 😂
@@Chloe-dt2vw wow congrats 😁👏👏
Lmaoo
the most confusing tutorial i came across. Good Job mate. :)
It's not confusing. He explained it well and everything you need to know is here. No need to blame your stupidity on others. You just need to practice.
@@navjotsingh2251 Bullshit. This is a shit video.
@@lance4377 Watch the video he linked in the description, he explains how there's an assumption you know some basics of it, this video does it explain it okish, it is a bit confusing, but having a bit of knowlledge about what it's about makes it a bit easier to understand :) I hope this helps
Your ability to teach, enlighten, and simplify is > 2.58 sigma which now I know puts you in the 1%. THANK YOU!
Thanks. The best compliments are expressed statistically : )
No mylidlponee. how2stats
Great video but how did you figure out the percentages? What if we numbered the bell curve with different numbers, would the percentages be the same?
I wouldn't call this a simple explanation at all.
Itʻs not, Slim. It could nicely be broken down into simpler steps. A good technique is to bump into a friend whoʻll pace you or to look at more than one version of the explanation from different books and videos. For instance, algebra gets taught in smaller doses, because textbooks teach it at a younger age. But the simpler approach is good for everyone; a smarter, advanced kid can breeze through it faster and get the job done. The opposite is not as helpful: cramming so much info into so little space! If the author skips examples for any so-called obvious steps, he loses readers in a hurry! The problem is, the readers tend to blame themselves and feel dumb, when in reality ANYONE reading over their head in ANY topic could feel the same way! Who wants to learn to swim by dangerously jumping in over their head? No need! Statistics could benefit from the same "thin slicing" of the lesson material!
I’m in year nine and I just want to know what normal distribution, even distribution and un even distribution is for my homework *help me* 😪
What does the x axis and the y axis of the graph represent?
Simple my behind! I understood a lil before this now I’m lost thank you!
There's a better version of this video here: ua-cam.com/video/tDLcBrLzBos/v-deo.html
Great video.
I have a question. Does your data have to be normally distributed to use these charts?
I have data grouped into categories (0,1,2,3,4,5), almost 50% of the data points fall into category 0, so it is very skewed. I'm guessing this data won't be suitable for a control chart.
Stephen MacDonald Correct, the data have to be normally distributed to be able to rely upon the categories/percentages displayed in the figure. However, if your data are non-normally distributed, you can still create a histogram and report the percentiles that correspond to your data, if you want.
in order to test for normality the sample size must be minimum 30 and probability sampling must be adopted for more ask Dr.rao ;hklrao@gmail.com
Are the numbers an integral of some complicated function? Because the %s are essentially area under the curve.
I know the mean for data and the median for the data. How can I plot it on Bell curve?
Nitin Saini A histogram
The mean is ALWAYS your reference point and set to 0.
When you right the date on your papers, how do you know what date to right. Or, how do you know how old the pyramids of GIZA are?
ANSWER: You set the most significant event in recorded history to zero and describe EVERY date relative to this reference date. HENCE, BC, AD
Step 1: You need either sample size(n) or directly standard deviation(SD)
If sample size given,
1. For n≥30, SD=√Σ(x-mean)²/n
2. For n
You didn't explain how the 34.13 came about. Is that the area under the curve which would be determined by integral calculus?
Yes, it is in a fairly established table called the Z-table where it corresponds standard deviations to percentages.
You should probably clarify a bit better that those percentiles of 34.13% correspond to a standard normal curve of a sample with a standard deviation = 1, and are based in reality, because a lot of people seem to feel like you're puling them out of thin air. I think calculus 2 would help a lot with this concept and those of later areas of general stats.
They should change the curve slightly so the percentages are rounded. I don't understand why they made that the standard shape.
Your clearly lost my friend.
Thank you very much for this video, it was very explanatory. I finally get what I was calculating all this time in math class.
I like how it says 'explained simply' in first few frames.
Great introduction to a very important probability distribution. However, growth of biological tissue (including here human height) actually fits a log-normal distribution, which means that the logarithm of height is a normal variable. A bit of a nitpick, but there you have it.
if you have a life example with a mean of 3 and SD of 1.5 how do you calculate probability when everything past the second negative variable is impossible.
You set the mean equal to 0. This is what is meant by 'Standard' normal distribution. Pay no attention to the real value of your mean, but to how far to the left or the right your data points swerve
People get lost at the point with the percentages. Let me see if I can explain. Take a look at the x axis and imagine you have a tape measure. You can draw a length between the 0 and the 1. Let’s pretend that’s one foot. You can also draw one foot between the 1 and the 2. Right? Now imagine you have a scale. You take the slice of bell between the 0 and the 1. It will weigh something. Let’s pretend that’s one pound. If you were to weigh the slice of bell between the 1 and the 2 that is going to weigh less than a pound. There’s less stuff there, right? Consider that if you were to weigh the entire bell, it will weigh 100%. Just think about these concepts and I bet you get it.
Try not to get bogged down in the actual numbers. Just try and understand the concepts here. These seemingly random percentages are actual properties of the bell curve that has been figured out by statisticians. I personally feel the guy in the video described this shit rather clearly without getting lost in the weeds.
I’ll just.... hold the L
What links the # of SDs to those percentages (i.e. what does 1s correspond to 68%)?
+Chad Sweeney There's nothing that links them intuitively. They are just facts.
These percentages are the area under the curve. In Probability + Statistics this is used to determine the probability of an event. These percentages are obtained by transforming a certain value into a Z value in the Z domain, which is restricted between -3 and +3. Each Z value has corresponding percentage of the area under the curve. These percentages can be cumulative or discrete. The entire Z domain is tabulated in the Z-table. Google it to see it.
How do you even find out the standard deviation of the normal distribution curve?
Most people talk about the standard normal distribution, and in this case, it is always 1. The properties of the normal distribution are function of a particular probability density function, so you don't find the standard deviation, per se, it finds you ;-)
how2stats oh ok. thank you :)
Let us consider marks in statistics test of 100 students of a class. Where mean (mu) is 50, i.e. the average marks of the class is 50. And let us consider that standard deviation is 10.
So now, 68 students out of 100 will get marks within the range 40 to 60. (68% within the range of +,- 1 standard deviation) similarly 95 students out of 100 will get marks within the range 30 to 70 (in generic term 95% will fall under +,-2 standard deviations) and 99.7 students out of 100 will get marks within the range 20 to 80 ( in generic terms it's 99.7% will fall under +,-3 standard deviation).
Why normal distribution curve bell shape?
Thank you so much for posting this video I am now understanding normal distribution and it much easier to level thanks to your video. The section was the most difficult part to understand and learning this online is such a struggle right now during the pandemic and I’m eternally grateful for this video. Thank you! - (from the statistic student who does not understand math at all)
There's an improved (more background information and better audio) version of this video here: ua-cam.com/video/tDLcBrLzBos/v-deo.html
yep, still confusing the fuck out of me. WHERE DOES THE RANDOM 34.13% COME FROM?!?!?! god i hate math, everything about is unclear and unnecessary
There is no meaning to the 34.13%. It's simply the percentage of observations that correspond to 1 SD from the mean (one side of the distribution). Stated another way, asking why 34.13%? is like asking why is planet earth's circumference at the equator is 24,874 miles (40,030 km)? It just is.
haha...
Slytherin Snowflake that value comes from the Normal distribution table
Slytherin Snowflake that's very simple...
VAUGHN CASTLE no
My assignment values start in at 40-120 . Every example I see never shows this
even on the internet, maths is confusing. and boring. and annoying. great
Generic Rarity i know right 😳
I was looking for these exact words when thinking about this
This is a shit video; go to other channels like organic chemistry tutor for good videos. Yeah I replied to a 4 yr old comment
@@lance4377 No, but that's totally needed here. This video is utter trash. Poor folks in the comments :(
Perfectly explained, thank you!
Still don't get it
what is zed test
Hi, I want to use your nice video for educational purpose. Thank you.
Well, I have a statistics test tomorrow 😢 hope this was able to sink in.. wish me luck
How did you do? You don't look like an actual moron btw.
Dustin Hinze well you asked about 3 years late so I wouldn’t count on that answer..
what about the t9-83
34% ? really? The things i knew i forgot because of u . The f was that , thanks alot i have a quiz right now
this was a pretty simple explanation what are these guys on about?
Sneak peek: 3:24
People getting confused the moment you jump to z-distribution while introducing normal distribution at the very basics like its curve that looks bell shaped. This is more of a giant leap of mankind to the moon for a child who is newly born and yet to see the moon. The improved version of this still misses the point, however, yes histograms run in the background of normal distributions.
That's a compliment. Seinfeld was one of my favourite sitcoms.
Is normal distribution applied to all observations?
Well explain Thank you for taking the time to share your knowledge.
and where we are gonna use this in our life?
If you had a real job you'd know
@@CJJJCC bitch I'm a technical head of a full stack developers team.
@@ajaymalik2835 calm down Karen. Nobody really cares what your bitch ass does for work. If you don't know when or how to use this then you really don't have a real job. Good day ma'am
@@CJJJCC I'm pretty sure u have a real full time job commenting on youtube btw who's comment did you copy, must be dissed pretty badly it seems, keep up the good work buddy.
Very well explained!!!
How the hell did you get those percentages? The fact you didn't explain this made your whole video useless, thanks for wasting my time, on to the next.
Exactly wtf im sayin. Might as well not have uploaded this bs
Youre not expected to calculate them. It would be better to just understand what they mean. Those numbers define 1 and 2 standard deviations because they represent the average values in which the data points swerve to the left or the right
Don't worry about how. Memorize them as part of the definition of the normal curve.
I appreciate it bud but I graduated 2 years ago and never need this crap again.
TheBirdMan so why watch the video? Quite contradictory 😑🤔
If I have two groups that I want to look into, one group is 677 with disability and the other is 17 265, with no disability can I say that this is not evenly distributed? I don't get it.
Do you mean the disability group has 677 people in it?
how2stats Yes, the group with disability has 677 people in it. And the other group is with no disability and has 17265 people.
it would be a good idea to add subtitles
If there were an easy way to get them, I would!
how does the value of the mean and standard deviation affect the normal curve??
I would say the mean and standard deviation do not affect the normal distribution. Instead, they are simply descriptive properties of the normal distribution.
Those who use the normal distribution should always be aware that the independent values range from -infinity to +infinity. In reality, nothing has this range.
he looks confused more than me
Good explanation about the ND intervals. Please explain the point of inflection, I heard it lies in 68.26. I want to know what the other points are called. i.e, 95.44% and 99.73%
How is it possible that The Mensa calculates wrongly that 2% of the people reach 148 IQ points.SD=24. So the right score is 149,32.The Mensa 148 IQ points 2,27% of the population.Also the chess metrics founder Jeff Sonas is totally wrong.The chess players average is 1400 SD=282,842 Jeff Sonas is using wrong SD=166,66.If you score 84,13% score in chess tournament you will get 282,842 points plus you opponents average
Remember, alpha and beta errors, confidence levels, as well as a minimum number of data points needed to reach 95% level.
Its easy to forget that the ends of this curve are asymptotal and stretch out to infinity, and that the graph loses its ability to accurately represent data points at these extremes. For example, how would you evaluate the IQ of the smartest man who has ever lived? You might know that he's smarter, but would have no way to know how much smarter he is than number 2. His IQ would have no where to go because there aren't enough other people up there to compare him with. So, the question is how many more births will it take for him to be bested? If he turns out to be smarter than the next 10 billion people to be born, than his IQ will, or at least our assessment of it, will have doubled posthumously.
The same problem exists for FIDE grandmasters. Magnus Carlson has what I believe is the highest rating in chess history, but is maxed out because there is no one else at the level left for him to win points from. The more distance he puts between himself and the pack, the fewer points he's award from each win.
Label axes. Point out inflection points, and comment on area under curve as a quantity of ....
im bout to fail my test tmr
where did he get all those percentages from?!?!?!?!
im so confuised
He got them because all the percentages In a bell curve equal too 100% and each side is normally distributed
thanks a lot. I came here with zero understanding but I'm leaving here with something.
negative understanding?
I'm here because the last couple of meetings my teacher in stat didnt went in on our class and on last day before our test is when he just discussed this and is expecting us to learn it quickly in 1 hour for our test just 1 day after that like the f!
that was clear...and i hardy use a used a signal standard neuron. grazie
This is the bell curve!? Aaaahh! I've been hearing about it for so long and it was the statistics' course normal distribution! :o
This is the thing used to show IQ differences between the sexes. Wow! So most people are within two standard deviations from the mean. Then, at the far right and far left you get people like Tesla and my boyfriend, respectively. :|
I didn't picture myself saying this about anything related to statistics, but: Very cool!
Nyah Senai Lol 😂😂 Great explanation👌
very explanatory. thank you, i can now do my stats hw
The problem with some intelligent people is they ASSume everyone is as smart as them.
There's an improved version of this video with more background information for people who need it: ua-cam.com/video/tDLcBrLzBos/v-deo.html
Thank you for the video 😊
strangely enough, in my econometrics class my professor claimed the difference of -2 to 2 is 94%
HERE's an idea.
If each of you cut out a picture of this curve and throw 100 darts at its center, the numbers he has provided are guaranteed to be almost the exact same number of holes made in each section.
Such a good explanation - Thanks :)
why have somepeople will said ,68%95%99.7%???
it just mean 68% of the sample points falls within 1 standard deviation from the centre of the normal distribution curve, while 95% of the sample points falls within 2 standards deviation from the centre.
I come back to this vid from time to time to look at the comments 💀💀💀
The problem we all face is that math guys cant explain things simply or effectively....
sorry, i don't get it
Nice !
Sorry, your 68.26% and so on, are so OUT of scale. This exaggeratedly high curve promotes a misconception. Either the areas under the curve don't add up to 1, or you owe us a scale for the y values if you insist on using different ones than x. Why not use the correctly shaped (much flatter) curve, especially for struggling students? Since the 1stSD is correct in this case, the height of the curve at x =0 should be only ≈ .3989 -- do you realize how high you have it? [in your STAT 101 Tour of the ND it's even worse] It may not be your fault, (you were taught that way) but this would be a great place to fix it. PLEASE
You're just plain wrong here. If anything, the shape of the distribution used in the presentation is already too flat. It was the based shape I could find in powerpoint. Go ahead and simulate some normally distributed data (say, N = 5000) and check it out in a histogram. Ideally, you would have done that before making your comment, but that may not be your fault (you were taught that way).
how2stats Call up a graphing app and plug in the SND formula.
clarklambert Here's what you get from N = 10,000: www.how2stats.net/2014/11/normaldistributionimage.html. It's possible that everyone else is wrong and you're right, but I don't see any evidence to suggest that's the case.
how2stats Switching from continuous to discrete just perpetuates the error. The point is the the y and x scales must match or you disturb both the area and the abscissa readings. Compare the exaggerated area to the left of a Z score of 1.5 on your curve, with the true standard normal (use a decent graphing app) and you'll see how yours overly flatters the subject because he thinks his score is better than (far too many) of the rest of the population. That's the point of graphing: to give an (accurate!) visual of relationships.
clarklambert Still no evidence....
Is it only me who has no idea how those percent values came?
they are already tested and proven by mathematicians/statisticians before us. all we need to do is use those percentages we dont need to know how or where they come from unless you want to be a pinoneering mathematician yourself
Left me more confused t
whats with that seductive voice....
this is the funniest comment i've read in a while hahahaha
I followed you up until your video stopped abruptly. Half-way simple.
i dont get it bye
thanks so much!
woah dude, that was simple -.-
Miguel Potestades i
why u making it complicated...!! -_-
this videos from 2 years ago im sure he doesnt do it anymore
the number of times you said "uh" though...stop!
3:24
If your class does shit on a test and you also do shit, for example class average is 22% and you get a 20% on a test, you get boosted up. If class does well and you do shit, you get dropped. the bell curve compares your grades against the others and thats how you get your grade. People take AP courses saying Il get boosted up even If i do shit thinking that they wont have to work as hard
the swallowing is no annoying
I think you need to understand it much deeper before trying to explain it. It’s not the most difficult subject, however It sounds like you are just “copying and pasting” lecture notes which is not very effective.
merci!
Good
tanx
Yes
this doesnt focus on explaining why. it just tells what is. haha just some constructive criticism
Okay you don’t get it, you don’t have to hate on the man. Geez.
Lol, these comments 😳 atleast I am not alone. My head hurts, over statistics!
Why click your toungue all the time???? This is the most annoying speech feature I could imagine.
This is not “normal” at all
👍👍👍👍👍👍👍
When you start explaining Normal Distribution showing the Bell Curve .... you are not making it easy on anyone.