Support StatQuest by buying my books The StatQuest Illustrated Guide to Machine Learning, The StatQuest Illustrated Guide to Neural Networks and AI, or a Study Guide or Merch!!! statquest.org/statquest-store/
@@JohnYoga The p-value is related to the assumption that the null hypothesis is correct. If it is correct, then our data should have a relatively high probability, and thus, we get a relatively high p-value.
I'm astonished ... you explain the intuition behind this in 11 minutes while my teacher spent 3 hours trying to explain this ! Glad my sis recommended you ! ^^
@@statquest Hi Josh, great stuff, though I am still a bit confused. :) So that I can get the fact straight ... Question 1: "The threshold of 0.05 means if A and B are the same, there is only 5% of the tests will exhibit p-values that are less than 0.05". This statement is then equivalent to "If A and B are different, 95% of the tests will exhibit p-values that are great or equal than 0.05". If so, how can you come to a conclusion in the video at 8:48 that A and B are different just because they have ONE p-value which is less than 0.05? Question 2: When you say if some one wants to be very strict, he can set the threshold to be 0.0001. In this case, what will the corresponding p-value be, also 0.0001?
@@jtbauer3789 Let me put this in a different way. Suppose that you are the guy trying to develop this new drug A. To be 100% sure that your drug really works and that isn't just luck or placebo that are curing people you would need to test this new drug in every person in the world, or even in the universe. For obvious reasons, this is not possible. To still be able to prove that your drug is curing people you can run this statistical test with a portion of people. We can say that this portion of people is a sample of your universe of people. For this statistical test, you need to establish a hypothesis that nullifies what you are actually trying to prove (this is the tricky part). In this case, this null hypothesis could be that your drug A is no different from drug B that we previously know that doesn't work. The origin of this knowledge about drug B it's not relevant for this test, you can just assume this previous knowledge. You also need to choose a threshold. Now comes the practical part of the test as explained in the video. You create two groups of people from your sample of people and each group is treated with only one of the drugs. You count, for each group, how many people got cured and how many were not cured. With these values, you calculate the p-value. The calculation of p-value needs an apart explanation. You just need to know that the p-value is the probability that the null hypothesis is true. Then if you get a p-value under the chosen threshold, this means a very low probability, it's very unlikely that the values that you observed in this one experiment happened only by luck (placebo or whatever). In conclusion, you can deny the null hypothesis and you can be pretty confident that your drug A does work.
@@jtbauer3789 the equivalent statement should be that: if A and B are different, 95% of the the tests will exhibit p-values that are less than 0.05 since it will be more likely that the test will report significant differences thus producing smaller p-values most of the time. or if A and B are different, 5% of the tests will exhibit p-values that are greater or equal to 0.05(only 5% of the test should suggest that A and B are the same)
I'm watching this deep into the night and the consious part of my brain is half-foot in the dreamland, quarter-foot in the limbo and only about the rest in the real world. This kind of explanation managed to get me to get this faster than it lulled me into sleep, so have my like good sir
Cannot imagine a better and simpler explanation to p-values. Amazing! Loving all the contents of StatQuest. Feels like finding the key to the Real Treasure of stats concepts!! Hurray!!
I really appreciate the slowed down, enunciated explanation as though you were explaining to a 5 year old. As someone with ADD, it's super hard for me to keep track of information especially if its even a little bit faster paced than this, but you explained everything perfectly as though it was made for me. Thank you !
Omg. Thank you very much i read alot of articles talking about p value but i was confused but now after watching your video i mastered p value😊 i am abdy kany from somalia
I was struggling in my stats class lately but your videos SAVED me, thank you so much. I'll definitely be watching more of your videos. I wish my prof was as incredible as you!
Sweet. P-value is one of what students are confused about the most in the study of statistics. With normal distribution, p-value is both theoretical and practical. This would elaborate this point as well. Nicely done!
I finally got the concept of p-value and I’ve heard and read so many explanations, still left confused. Thank you so much, you’re making the world a better place❤️
@@EbonyPope It depends on what you are measuring. For example, if you are measuring the height between two groups of people, the effect size could be the difference in the average heights.
@@statquest Ok but what does the p value measure then? The likelihood of the null hypothesis being true? I understand that I reject it when it's equal or less my significance level. But apart from that? How do I interpret a very low or very high p-value? What does it tell me if for example p is 000000.1?
I wish I had a teacher like you in my college days. You are out of the world. Really really love your work. Have a doubt in stats don’t worry!! We have Sir Josh Starmer.
My brain has been so enlightened, thus I feel so much better about p-values as well :D How many times did I read about this trying to understand it?! But this video concisely elucidated the concept so well, I'll return here if I need a refresh. Thank you Josh and Statquest! Double Bam!!
This is the reason I have started my channel here to help others understand mathematics like you. This is very good approach in this field ,DAVIKA Academy which is my channel am working on both pure, applied and statistical mathematics. Once more keep it up let us transform the educational sector .
I spent like 2 days read about NULL HYPOTHESIS and when I came here you just said that to prove whether the drugs are the same or not.... Sir you are intelligent indeed!
Josh, this is really good! It covers that main points and helps us all focus on them. As a calibration person, I always find it interesting when I find situations in which we assume the perfection of the accuracy of our input data. This is not at all a criticism of your excellent effort, because if you tried to cover all considerations, you would never publish anything. This is what sank Charles Babbage. I appreciate how you pointed out the assumptions that are sometimes hidden in "hypothesis test". This is why juries find some people "not guilty" instead of "innocent". There is an important sense in which those two things are not equivalent to each other. Thank you again!
Josh, I am not sure if I am going to pass my exam or not. But if I do, it is thanks to you. You are a king among kings when it comes to clear, meaningful instructions about statistics. Thank you so, so much for the time and effort you put into these videos. It makes studying bearable. Thank you, thank you, thank you.
If all the teachers were this fun and cleared concept with such lucid explanation, there would be many bright students who would be interested in the subject rather than cramming up definitions!
Loved it... was struggling to understand how the p value actually determine the differences in effect. This video explained it all. Thanks a lot StatQuest
You are absolutely awesome!! I watched a bunch of videos but yours was the only one where i got to understand the actual concept..Thanxxx a lot! You’re such a saviour.🤩
In simple terms. I would say that “p values has the ability to identify rare events”. But before that you have to decide what a rare event would be. However. Explanation provided by Sir is awesome.
Thanks a lot for this amazing video, I knew what p values meant but you gave me a whole knew way to think about it. A lot of statisticians are against using p values. I have tried to understand the reasons, but haven't made much progress. If possible please make a video of it or write it up on a blog.
The problem with p values is that they are easy to manipulate and you need more information about an experiment than just the p value to assess if the results show anything. Let's say I have 100 drugs, test if they cure a diseases and say they are a good drug if the respective test resulted in a p value smaller than 0.01. Now even if no drug has any value we expect one p value smaller than 0.01, because we did so many tests. This happens a lot and instead a much smaller threshold should be used (e.g. by Bonferroni correction). What I read in a medical paper lately was that they tested I two groups of size 3 were different and got "p
A week from today I'll release a StatQuest on something called "p-hacking" that explains how p-values are abused. Then I'll release a video on power calculations that shows how to fix the problem.
@@nmertsch8725 So here chances of getting p less than .01 is because we are comparing Large (100) no treatments. If we would be comparing just 2 treatments one control and new one than using p values would be fine?? Apologies for such a late reply.
Thanks for great intuition video. Hope you do more mathematically rigorous videos also ❤️ 9:00 interpretation of large or tiny p value. A small p value doesn’t necessarily mean that there’s a big difference between the drugs, but it means that there is a statistically significant difference (even if that difference is small)
@@statquest Thanks for all your videos! I got one question, how is it possible that drug A and B are different if they have 35% and 34% cured people respectively?
@@nestorrabanal4451 The larger the sample size, the more power we have to detect small differences between groups (or drugs, in this case). For more information about "power", see: th-cam.com/video/Rsc5znwR5FA/w-d-xo.html
Thanks, for such creative interpretation of p value. Sometimes it appears to me that i have to cram a lot of formula in stats and that is quite irking for me.But your video is simple, adorable and short in which you have used set induction and then illustrated through various distinct examples. Lovely!
Thank you so much! I'm a bit confused about why the closer a p-value is to 0, the more confidence we have that Drug A and B are different as if the threshold is 0.05 which means if A and B are same and if we did this exact same experiment a bunch of times, then only 5% of those experiments would result in the wrong decision. Then if the p-value is 0.03. It means only 3% of those experiments would result in the wrong decision. Why it doesn't mean it is more likely that A and B are same?
The p-value tells us how different the observed data are from what we would expect if the data were the result of random chance. The smaller the p-value, the less likely that the data were the result of random chance.
@OKUBO SELESTINE OPIYO It's not exactly "the the p-value, meaning there was less random chance influencing the results", it is more that "if it were random chance, then the event we saw would be very rare".
Support StatQuest by buying my books The StatQuest Illustrated Guide to Machine Learning, The StatQuest Illustrated Guide to Neural Networks and AI, or a Study Guide or Merch!!! statquest.org/statquest-store/
After watching this video, I bought the book! Thanks!!
@@dezj9427 Hooray! Thank you for your support!
In an ideal world, all teachers should be this clear, intuitive, and fun!
Thank you! :)
I would say in an unreal word.
It,s null hypotesis
in malaysia we dun understand what bam means... lol
I really like the vedio produced by Statquest. Much clearer explanationation than my lecturer
You can't imagine how much *EASY you are making* these confusing things or other people who are making this stuffs confusing !!! Love you man...
Thank you!
If my Null Hypothesis is I will understand the concepts explained for you, then I get a p-value of 1 every single time.
Best teacher ever, period!
BAM!!!
@@JohnYoga The p-value is related to the assumption that the null hypothesis is correct. If it is correct, then our data should have a relatively high probability, and thus, we get a relatively high p-value.
I'm astonished ... you explain the intuition behind this in 11 minutes while my teacher spent 3 hours trying to explain this !
Glad my sis recommended you ! ^^
Glad it was helpful!
my professors spent hours and multiple slides trying to explain P-values and still did like 20% as good of a job as statquest.
I'm sorry, but, for some of us, that the ice-cream truck arrives on time is extremely important.
You made me laugh! :)
@@statquest BAM!!!
@@statquest Hi Josh, great stuff, though I am still a bit confused. :) So that I can get the fact straight ... Question 1: "The threshold of 0.05 means if A and B are the same, there is only 5% of the tests will exhibit p-values that are less than 0.05". This statement is then equivalent to "If A and B are different, 95% of the tests will exhibit p-values that are great or equal than 0.05". If so, how can you come to a conclusion in the video at 8:48 that A and B are different just because they have ONE p-value which is less than 0.05? Question 2: When you say if some one wants to be very strict, he can set the threshold to be 0.0001. In this case, what will the corresponding p-value be, also 0.0001?
@@jtbauer3789 Let me put this in a different way. Suppose that you are the guy trying to develop this new drug A. To be 100% sure that your drug really works and that isn't just luck or placebo that are curing people you would need to test this new drug in every person in the world, or even in the universe. For obvious reasons, this is not possible. To still be able to prove that your drug is curing people you can run this statistical test with a portion of people. We can say that this portion of people is a sample of your universe of people. For this statistical test, you need to establish a hypothesis that nullifies what you are actually trying to prove (this is the tricky part). In this case, this null hypothesis could be that your drug A is no different from drug B that we previously know that doesn't work. The origin of this knowledge about drug B it's not relevant for this test, you can just assume this previous knowledge. You also need to choose a threshold. Now comes the practical part of the test as explained in the video. You create two groups of people from your sample of people and each group is treated with only one of the drugs. You count, for each group, how many people got cured and how many were not cured. With these values, you calculate the p-value. The calculation of p-value needs an apart explanation. You just need to know that the p-value is the probability that the null hypothesis is true. Then if you get a p-value under the chosen threshold, this means a very low probability, it's very unlikely that the values that you observed in this one experiment happened only by luck (placebo or whatever). In conclusion, you can deny the null hypothesis and you can be pretty confident that your drug A does work.
@@jtbauer3789 the equivalent statement should be that: if A and B are different, 95% of the the tests will exhibit p-values that are less than 0.05 since it will be more likely that the test will report significant differences thus producing smaller p-values most of the time. or if A and B are different, 5% of the tests will exhibit p-values that are greater or equal to 0.05(only 5% of the test should suggest that A and B are the same)
Finally I don't dread this question in an interview. Godspeed to you!
BAM! :)
You explain things so clearly, these videos are a gift to us all, especially to those like me studying for a statistics exam! Many thanks from Canada
Good luck! Let me know how the exam goes.
@@statquest If the p-value doesn't decide effect size what does it then? And what does determine effect size?
I'm watching this deep into the night and the consious part of my brain is half-foot in the dreamland, quarter-foot in the limbo and only about the rest in the real world. This kind of explanation managed to get me to get this faster than it lulled me into sleep, so have my like good sir
Thanks!
It’s 12:25 am and finally understood what is p-value. BAM!!!
Bam! :)
I believe there isn't any other simple and clear explanation of the P value that is out there. hands down!
Thank you!
Cannot imagine a better and simpler explanation to p-values. Amazing! Loving all the contents of StatQuest. Feels like finding the key to the Real Treasure of stats concepts!! Hurray!!
Thank you very much!
this channel saved me from joining the marine corps
bam! :)
I really appreciate the slowed down, enunciated explanation as though you were explaining to a 5 year old. As someone with ADD, it's super hard for me to keep track of information especially if its even a little bit faster paced than this, but you explained everything perfectly as though it was made for me. Thank you !
Glad it was helpful!
These videos are concise & easier to grasp than the 2hr Stats lectures at college. Thanks, Josh & Stats Quest Team!!
Thanks!
omg I love how calm your voice is, I can actually feel relaxed trying to learn stats - thank you!
Thanks!
I really needed the, "if johnny has 3 apples" level of explanation
bam! :)
Omg. Thank you very much i read alot of articles talking about p value but i was confused but now after watching your video i mastered p value😊 i am abdy kany from somalia
Awesome! And good luck with your studies! :)
I was struggling in my stats class lately but your videos SAVED me, thank you so much. I'll definitely be watching more of your videos. I wish my prof was as incredible as you!
Wow! Thank you! :)
You have the best videos about statistics of the entire internet
Thank you!
Sweet. P-value is one of what students are confused about the most in the study of statistics. With normal distribution, p-value is both theoretical and practical. This would elaborate this point as well. Nicely done!
Thanks! :)
Thank god, you saved me. It was explained so perfect! May my gratitudes reach you wherever you are
Thank you very much! :)
The StatQuest must go on! Thanks a lot, Josh. Stay strong and safe!
Yes!!! I hope you stay strong and safe as well. :)
This is the 4th video about p values I've watched and you finally make it make sense, thank you
Thanks!
I finally got the concept of p-value and I’ve heard and read so many explanations, still left confused.
Thank you so much, you’re making the world a better place❤️
Glad it was helpful!
If the p-value doesn't decide effect size what does it then? And what does determine effect size?
If the p-value doesn't decide effect size what does it then? And what does determine effect size?@@statquest
@@EbonyPope It depends on what you are measuring. For example, if you are measuring the height between two groups of people, the effect size could be the difference in the average heights.
@@statquest Ok but what does the p value measure then? The likelihood of the null hypothesis being true? I understand that I reject it when it's equal or less my significance level. But apart from that? How do I interpret a very low or very high p-value? What does it tell me if for example p is 000000.1?
His "hello" is like waking me up from a deep sleep....that's awesome!!💌
Bam! :)
I wish I had a teacher like you in my college days. You are out of the world. Really really love your work. Have a doubt in stats don’t worry!! We have Sir Josh Starmer.
I'm really glad you like my videos! :)
My brain has been so enlightened, thus I feel so much better about p-values as well :D How many times did I read about this trying to understand it?! But this video concisely elucidated the concept so well, I'll return here if I need a refresh. Thank you Josh and Statquest! Double Bam!!
Thank you!
among all the videos I watched regarding pvalues, I'd say this is the most easy to understand. good job!
Awesome, thank you!
These series of lectures are a gift to humanity.
Thank you!
This is the reason I have started my channel here to help others understand mathematics like you. This is very good approach in this field ,DAVIKA Academy which is my channel am working on both pure, applied and statistical mathematics. Once more keep it up let us transform the educational sector .
Noted
I spent like 2 days read about NULL HYPOTHESIS and when I came here you just said that to prove whether the drugs are the same or not.... Sir you are intelligent indeed!
Thank you! :) I also have another video that is all about the null hypothesis: th-cam.com/video/0oc49DyA3hU/w-d-xo.html
Man, I love your nonchalant exclamations lol. As an engineering undergrad, you make statistics less insufferable. 😂
Thank you! :)
Josh, this is really good! It covers that main points and helps us all focus on them. As a calibration person, I always find it interesting when I find situations in which we assume the perfection of the accuracy of our input data. This is not at all a criticism of your excellent effort, because if you tried to cover all considerations, you would never publish anything. This is what sank Charles Babbage. I appreciate how you pointed out the assumptions that are sometimes hidden in "hypothesis test". This is why juries find some people "not guilty" instead of "innocent". There is an important sense in which those two things are not equivalent to each other. Thank you again!
Thanks! :)
I really like this sentence, "This is why juries find some people "not guilty" instead of "innocent".
Thank youuu! You deserve a Nobel prize for providing such useful content for free. This helped me a lot. Now you have one more subscriber ❤
Thank you very much! :)
yooo wtf u look like alexandra botez
@@caclso4909 oh, I wish! She's gorgeous
Im so glad I pay all this money for a "teacher" to send me to your free videos to learn. What a world and ty
:)
now I understand the P value, don't know its just hyped terminology! Thanks man , the video is great.
Happy to help!
Hey Mr Josh
I can't Imagine the statistical World without you!
THANK YOU ❤️
Thank you!
Josh, I am not sure if I am going to pass my exam or not. But if I do, it is thanks to you. You are a king among kings when it comes to clear, meaningful instructions about statistics. Thank you so, so much for the time and effort you put into these videos. It makes studying bearable. Thank you, thank you, thank you.
Good luck with your exam! :)
@@statquest Thank you! I just finished. I'll let you know how it went (:
If all the teachers were this fun and cleared concept with such lucid explanation, there would be many bright students who would be interested in the subject rather than cramming up definitions!
:)
Best thing I've ever watched! Thanks for being so clear and giving examples.
Thank you! :)
bam bam bam aaannnd bam. This literally has revived my life. I was gonna be dead by imagining how difficult p-values were
bam!
Amazing explanation Josh Sir, I have been watching the stats playlist during this quarantine. Thanks for the amazing content. Stay Safe
Thank you very much! :)
Y
I love the jingles. They are short and delightfully lacking in enthusiasm. Thanks for the great videos!
:)
thank you so much for making this A1 content to help us students out, we are so indebted and grateful to you.. :"(
Thank you! :)
Loved it... was struggling to understand how the p value actually determine the differences in effect. This video explained it all. Thanks a lot StatQuest
Glad it was helpful!
Josh Starmer's Stat Quest is excellent.
Thank you very much! :)
Great way of teaching with full of humour thank you so much statquest ❤
Thank you!
Daddy, what are p-values?
Sit down son, and let me tell you the story about drugs
:)
You are absolutely awesome!! I watched a bunch of videos but yours was the only one where i got to understand the actual concept..Thanxxx a lot! You’re such a saviour.🤩
I'm glad the videos are helpful! :)
I would give this video 10/10 p values
Thanks!
In simple terms. I would say that “p values has the ability to identify rare events”. But before that you have to decide what a rare event would be. However. Explanation provided by Sir is awesome.
emphasis on the "deciding before" part, as this is often overlooked in understanding p-values. 👍🏾
repository.upenn.edu/statistics_papers/540/
Thanks! :)
I reject the null hypothesis that "there is a statquest video that don't start with a awesome song" :)
BAM!!! :)
The last point about p values and the difference between the two samples is seriously 🤯 BAM! 👍🏽👍🏽
Thank you! :)
Thanks a lot for this amazing video, I knew what p values meant but you gave me a whole knew way to think about it.
A lot of statisticians are against using p values. I have tried to understand the reasons, but haven't made much progress. If possible please make a video of it or write it up on a blog.
The problem with p values is that they are easy to manipulate and you need more information about an experiment than just the p value to assess if the results show anything.
Let's say I have 100 drugs, test if they cure a diseases and say they are a good drug if the respective test resulted in a p value smaller than 0.01.
Now even if no drug has any value we expect one p value smaller than 0.01, because we did so many tests.
This happens a lot and instead a much smaller threshold should be used (e.g. by Bonferroni correction).
What I read in a medical paper lately was that they tested I two groups of size 3 were different and got "p
A week from today I'll release a StatQuest on something called "p-hacking" that explains how p-values are abused. Then I'll release a video on power calculations that shows how to fix the problem.
@@nmertsch8725 So here chances of getting p less than .01 is because we are comparing Large (100) no treatments. If we would be comparing just 2 treatments one control and new one than using p values would be fine??
Apologies for such a late reply.
One of the best explanations of p values!
Glad you think so!
Though I am not a biology guy, but by watching your videos, I guess I can learn statistics and biology at same time.
Thanks a lot Josh.
Thanks! :)
Your "Horrayyy!" Makes me smile while learning from your videos.😆
I'm so glad!
You are a legend! Thank you for your clear explanation with some fun along the way.
Awesome! :)
The best explaining video i ever watched.
Thank you!
Thanks for great intuition video. Hope you do more mathematically rigorous videos also ❤️
9:00 interpretation of large or tiny p value.
A small p value doesn’t necessarily mean that there’s a big difference between the drugs, but it means that there is a statistically significant difference (even if that difference is small)
Thanks!
@@statquest Thanks for all your videos! I got one question, how is it possible that drug A and B are different if they have 35% and 34% cured people respectively?
@@nestorrabanal4451 The larger the sample size, the more power we have to detect small differences between groups (or drugs, in this case). For more information about "power", see: th-cam.com/video/Rsc5znwR5FA/w-d-xo.html
@@statquest Thanks for your answer Josh!
Best video on p-value by far
Thank you!
BAMMMMM i got it now! thank you so much!
Hooray! :)
I AM SO GRATEFUL I FOUND THIS!!!
Hooray! :)
It's been over a year and there are still comments being hearted and getting replies lol, I love the commitment.
BAM! :)
I graduated with your videos. I can say that the best and most clear explanation about my interested topics :)
BAM! Thank you!
Hi Josh,I really appreciate your efforts in making these videos
Thank you! :)
Way better than my university tutor explained, thanks you! Big help! Subscribed!
Wow, thanks!
So intuitive and well explained!! Great job!
Thank you!
want lo learn about data science and so many people suggest me to start from here, and finally i know why, absolutely great video
Thank you!!!
Thanks, for such creative interpretation of p value. Sometimes it appears to me that i have to cram a lot of formula in stats and that is quite irking for me.But your video is simple, adorable and short in which you have used set induction and then illustrated through various distinct examples. Lovely!
Glad it was helpful!
Bhai mujhe bhi samjha do. Mere kuch palle nhi pada
Amazing explanation! The excitement your explanation generates, blurs the difference between an entertainment video and an education one!! :)
Thanks! :)
I love the songs you sing at the beginning of the lectures each time.
Thank you very much! :)
Dude, you're getting me through STATS right now! Thank you! 🥰
Happy to help!
this helped, good explanation!.
Thanks! :)
Thanks!
HOORAY!!! Thank you very much!!! I really appreciate your support!
Sir, I will do a case study on your teaching methodology
BAM! :)
The Chef John of Stats, love the videos
Thank you!
Thank you so much! I'm a bit confused about why the closer a p-value is to 0, the more confidence we have that Drug A and B are different as if the threshold is 0.05 which means if A and B are same and if we did this exact same experiment a bunch of times, then only 5% of those experiments would result in the wrong decision. Then if the p-value is 0.03. It means only 3% of those experiments would result in the wrong decision. Why it doesn't mean it is more likely that A and B are same?
The p-value tells us how different the observed data are from what we would expect if the data were the result of random chance. The smaller the p-value, the less likely that the data were the result of random chance.
@OKUBO SELESTINE OPIYO It's not exactly "the the p-value, meaning there was less random chance influencing the results", it is more that "if it were random chance, then the event we saw would be very rare".
Excellent explanation, simple, summarized and clear
Glad you liked it!
Is it just me who laughs every time he says "small p"-value?
:)
StatQuest with Josh Starmer as I’m
In
I should be studying for my upcoming statistics exam...but instead I'm up late at night watching another episode of StatQuest ! 😬😬🤔🤔😎😎😎
bam!
Bam!!! Thanks! This video is going to help me in a presentation at work!
Good luck! :)
Amazing explanation and great voice! It is a pleasure to listen to You and all examples are funny. Live the pictures and examples. Thank you!
Thank you very much!
You made me sign on the first "hooray and bummer", but at the end of the video I realized u made a good material and worth the following, nice job XD
Thanks!
This is so much fun and clear!
Thank you! :)
josh is the best teacher
Thanks!
Thanks
TRIPLE BAM!!! Thank you for supporting StatQuest!!! :)
Wow I heard exactly what I needed to know! Thank you man !! Horraaaay
bam! :)
This is literally the BEST statistics channel I have ever seen , keep up the good work!
Thank you! :)
Amazing Video, solved a lot of confusion for me! Thank you very much.
Glad it helped!
I will forward this course for my stat instructors.
I hope they like it! :)
after attending your lecture BAMMMMMMMMM!!!!!!!
bam! :)
Hooray!!! I made it to the end! And now I get the idea behind p-values.
BAM! :)
thank you very much Josh, I was very confused with this topic
Glad it was helpful!
Beautifully and clearly explained. :)
Thanks a lot!
it is the best explanation I`ve ever seen. Thanks a lot!
Glad you think so!
Very clear cut and nice way u explained it 😍😍
Thank you sir 🙏🙏
Thank you! :)
You're teaching is very unique and easy to understand. Keep up the good work.
Thank you very much! :)
Excellent content! Meaty theory presented in an engaging way.
Thanks!