Statistics 101: Type I and Type II Errors

Statistics 101: Type I and Type II Errors - Part 1.
If this video we begin to talk about what happens when our data analysis leads us to make a conclusion about a hypothesis that turns out to not align with the actual state of the world. These are called Type I and Type II Errors in statistics. There is no computation in this video as it is purely conceptual and aimed at basic understanding.
We start out by looking at two thorough non-statistical examples; the fire hypothesis and the andon hypothesis. These examples set the stage for understanding Type I and Type II Errors in statistics by providing situations you can reference easily. In Part 2 we will do the same thing but with proper statistical problems. Enjoy!
My playlist table of contents, Video Companion Guide PDF documents, and file downloads can be found on my website: www.bcfoltz.com

[@vulnerablerummy]

i'd like to think of type i and type ii error as "the error of acting" and "the error of not acting"

[@setred1970]

These videos are making statistics understandable for one returning to school after 20 years. A heartfelt Thank You!

[@amritasridhar2452]

Is it just me or are these videos making everyone see the world in a whole new way? I love the approach of the professor

[@huytquoc]

Love the approach learning math in relating it to real-world problems. Easy to understand and remember. Thank you!

[@BrandonFoltz]

Thank you!

[@maxpercer7119]

This once happened to me. I had to decide between making a type I error (called the fire dept and got embarassed that it was a small fire that i could easily put out with water) or ignore it and the small fire continue to burn and turn into a whole house on fire. The cost of the type 2 error was must greater than the cost (embarassment, inconvenience) of a type I error.

[@xjervoise]

Thanks for the clear and easy to understand series. Really helped me a lot in my course work. I'd just like to add that the table for Andon Hypothesis has a row stated "Accept H0", which should be "Fail to reject H0".

[@BrandonFoltz]

Oh thank you so much my friend! People like yourself are MY inspiration. I try to explain things to others as I explain them to myself in my own head. :) You are most welcome and THANK YOU! All the best, B.

[@Subboxx]

Your Intro was vey positive and encouraging. I appreciated that because this course is very overwhelming........ Thanks and Great Job!!!!!!

[@chu8595]

You are GOD sent; I fail Stats the first semester and now I understand better because your videos are excellent and easy the understand. Thanks you sooo much

[@BrandonFoltz]

chu8595 Thanks so much for watching! :) Kudos to you for picking yourself back up and making the effort to go out and try again. Perseverance wins out. Hang in there! Best, B.

[@wootsat]

Thank God nobody died in that hypothetical Type II fire! On a serious note, your videos are amazing!

[@vineetmehrotra2362]

Nicely explained first time ever i have been able to understand basics of Type 1 and 2 errors

[@laurisskraucis2247]

Thank you Brandon. You are literally having a positive impact on lives of many thousands of students. You are an awesome teacher, really wish you were teaching at my University.

[@BrandonFoltz]

Thanks Lauris! That means a lot to me. Can't wait to see the impact you and your classmates have on the world. And I do get to be your teacher! :)

[@MsSofia8]

PLEASE KEEP MAKING STATS VIDEOS! I LEAVE CLASS COMPLETELY CLUELESS AND THANKS TO YOU I AM DOING GOOD! THANKS!

[@veeranagoudayaligar]

Simple explanation about Type I and Type II error. Thank you soo much Brandon. You are my stats teacher!

[@cummind100]

I'm studying for the CAIA. This person has been hugely helpful !

[@bryanbocao4906]

Thanks for this concrete example! Hopefully, next time when I smell a smoke I will not just sit down and focus on thinking of whether I will make a type I or type II error or not, but instead, what I should do is to pull the alarm properly.

[@chhaviaggarwal8437]

Your videos are just awesome. The way you explain everything, the organisation, the speed , the length , the completeness of the material , everything is so good. Thank you sir!!

[@palak1997]

Thanks! It is such a smooth flow. I am taking your all Statistics courses. It is really working for me while I am doing my MS (Data Science) from Texas. I support your channel. Love from India.

[@BrandonFoltz]

Thank you so much 🙏

[@ubuntuhosting]

I'm just a few minutes into your video and the way you explain is simple but effective, making it so easy to understand. Can't wait to finish the rest. Thank you!!!!

[@markniks8821]

Brilliant, thanks. Key is - False alarms are TYPE I errors.

[@maartjeamelink8838]

Very helpful, thank you! The only thing I would like to add is that Type-I error can be quite bad as well, for example when someone is diagnosed as having cancer when in fact they don't. Again, thanks for your tutorials!

[@Another_Look]

Well, the opposite is much worse.

[@danicaliz7133]

Wow you explained it better than my statistics teacher. Kudos to you 👌

[@anilpanagoda8560]

I am following your videos for some time. It has given me a good insight about stats. Very helpful for my econometrics. Thanks

[@deniz7mel]

Best explanation of type I and II errors I have ever seen, thanks for the video

[@pv0315]

very well made . this has made all stressy math so easy to learn

[@hormatomran8724]

You are an amazing person Foltz. you are explaining complex stat issues in a very simple way. thank you very much.

[@pradeepmanjegowda1148]

Very useful information explained with simple and easy examples.

[@nss490]

I have to say, this channel is great. Thank you!

[@cristinaquiambao1672]

It makes my teaching easier than i Think. Thank you and more power.. Keep on informing people.

[@AngeloYeo]

Your lectures are just amazing! It always made me confused whether it's type 1 or 2. Thank you so much for your lectures.

[@cheanna4543]

we students attend our statistics class to report in front and so all of us end up watching the internet to prepare for the class that is supposed to be discussed by the teachers.. :( so thank you for the videos! it helps a lot!

[@djjiang3718]

Thank you Mr. Brandon Foltz, you are such a great teacher ! You explained a very complex subject very clearly and vivid and very easy to understood !

[@eaweltmer]

My homework is already getting easier! Thank you so much!

[@milligangirl]

Thank you for explaining the Type 1 and Type 2 errors so thoroughly! Thank you!

[@whiteorchid1957]

Watched several videos so far. I'm making steady progress. Thank you.

[@shaz-z506]

Hi Brandon, Please create a series on Machine learning, and I know that your explanation over the concepts we'll be on top of the line.

[@melissacastro8265]

amazing, the real world examples helped me COMPLETELY understand!

[@sarammamathew7335]

Excellent explanation of type 1 and Type 2 Errors! thank you for making it simple for students to understand !

[@karaokeclicks]

Amazing simplicity. I wish there were more teachers like you!!!

[@craigneed9276]

Your teachings are very helpfull and easy to understand and remember. Thank you, for helping me get throug Statistics.

[@coolfrog6569]

no words to explain... simply awesome...

[@samarthtandale9121]

I'm watching this series and found the videos very helpful in fundamental concept building 💪 ... Great Work I must say 🔥 Shared the playlist with all of my classmates ! Keep up the great work ✨✨

[@BrandonFoltz]

Hi Joyce! You hang in there; I know you can do it. :) Experience is the best teacher. And you are welcome. Glad you are finding them helpful. - B

[@sarveshsundaram]

Dude, your explanation style is other worldly. Thanks!

[@jenniferarmstrong4055]

Thank you for your video! It makes much more sense to me than what I read in my textbook!

[@sahajshukla]

simplistic approach, pep talks, good thoughts and everything nice. I wish I could thank you enough both for the positivity u bring in and the way u help us learn. Thankyou so much sir.

[@Gehrber]

Your work is amazing: Videos are well structured, calmly narrated and your examples are always relatable!

[@LambaDaboos]

Thank you very much for the simple way you are using to explain ..... Best of luck always and keep doing more and more videos....Thanks.

[@justincordeiro5674]

Your teaching are thorough, unfortunately I found your video collection in the last 2 weeks of my Stats class. Maybe you should start teaching some of these online classes? When I have questions for my professor they respond with screenshots of the answers. I sit back in my chair and hesitate to promptly reply with an email. When you ask why something happens or to further explain the application of these processes my teacher simply replies that it is a fast pace class and to not worry about this process? First and last time I take an online class. Education system.... Thank you again Brandon Foltz your video gives some depth and application.

[@janellcruz3103]

Thank you so much! I had been working on the same problems for about four hours already!

[@rishabhmehta3364]

You are like a ray of certainty in the world of uncertainty of statistics. Thanks a lot for your wonderful videos, keep making many more. Would love it if you could make some videos about stochastic processes and Markov jump process. Thanks.

[@baymafay]

Thanks so much for your time. Your knowledge and simplicity in explaining these difficult concepts is exceptional. Please don't ever stop. You have been my saving grace through my statistics courses.

[@Azureandfabricmastery]

Hi Brandon, Thank you for your help. Beautifully explained with real world problems. Learning can never be this easier. God bless for your efforts.

[@janewhite3330]

I really appreciate your videos; your approach and your thoroughness are very helpful. I also think it would be worthwhile to add the choice of speeds so that students can listen at 1.5X or even 2X speed. This would be very beneficial if I am doing a review of material that I have already viewed, or if I have a shorter time to listen--like when getting ready for work or when out on a power walk and my time is truly limited. Thank You!!

[@Parvathyvarmas]

Great Video! Making it simple for the students. Good job!

[@william254mwangi4]

thanks, it really gave me an intuition of how to see nil and the alternative hypothesis👌👍

[@beatspongebob9643]

These videos are so helpful Thankyou Mr.Foltz!

[@agarciasanz]

Thanks! I will take a look now. Very useful videos!

[@kstudy6187]

Thanks a lot sir....really good content and understandable one . Thanks for providing this valuable video.

[@venkatnaresh548]

awesome teaching sir..I Am really impressed with your style of teaching

[@ME-fp6hk]

Brandon, you are a legend.

[@mahbubulalam2067]

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[@trobsh84]

Amazing! Thank you very much! You make the concepts very easy to understand by providing real-life examples.

[@MegaMarshalld]

Absolutely brilliant - Thank you

[@palkarchinmayr]

millions of thank you, would love to learn and solve more, excellent video series very helpful

[@janetnapawl4180]

Thank you for the great video! I can so relate to type 1 error!

[@emilieeverly5102]

Your videos have been really useful for me. Thanks for making them!

[@akashbaruah8147]

Nice videos! Could we also get references to some of the materials (Books) that you read in order to prepare the videos? It would be very helpful with​ greater clarity on the subject. Thanks and Regards!

[@lyndamccroskey1884]

good sample/examples! I have reviewed many of these lectures, but would like to see a final section that provides the viewer the answer to what they likely are asking...how do you know if you committed a Type I or Type II error? Can you know? Students do not get this!

[@yxmordarbert]

thx for your videos, one of the most informative and well explained videos on youtube!

[@romanvasiura6705]

Thank you for this great lesson!

[@enatp6448]

Great vids Brandon. You are helping me make sense of a master's level research course. many thanks!

[@sansaonhantumbo6143]

Fenomenal explanation. Thanks.

[@nicolasadas307]

Truly excellent and effective .. thank you

[@msreeram1]

Excellent explanation. Thank you !!

[@somaksengupta9491]

Thank you so much ! Such a great explanation. Clears the concepts so well.

[@anamunoz730]

Awesome work. Thank you helping us understand the concepts and applying to real life example.

[@sudharshanr4997]

Andon cord example was excellent😊

[@sundars5278]

Hey Bradon this is Sundar 😍...@17.09 in andon hypothesis if the andoncord is pulled the worker is rejecting the assumption, actually the process is not error free...but you wrote as error free....can you please check it sir....😇😇😇.......Your concepts are awesome.I am learning statistics from your channel feeling blesses. Love you so much brandon💗💗💗💗💗💗

[@prvenkateswaran9435]

exceptionally good all your videos are a great learning asset for studdents i wish you will bring out videos on SEM also

[@abirmohamed161]

. Amazing lecture, and very clear explanation. Thank you so much

[@CheylGood]

Make more videos pleasee. I love your chanel! It helped me a lot going through my statistic class

[@danielstillit748]

Great work Brandon. Thanks

[@engchunheng3683]

Good vidoes, understands the basics.

[@kierrajones8510]

Wow! Thank you for such a great explanation, I might actually ace this stats test!

[@Coollllbboyy]

You are amazing! I have been struggling to understand this since my undergraduate studies!! and it is that easy???

[@sukarnabarua7979]

these are really great video. Learned a lot.

[@jaffsoran]

Thank you Sir. I do really appreciate this tremendous effort. Hope you continue

[@chinedueleh3045]

Hmmm....I think Boeing is in dire need of the Andon hypothesis! Great videos, thanks. I think comparison of the worse between null and alternative hypotheses is relative and depends hugely on the problem.

[@storytimereadaloud805]

Very good and useful.

[@ramanadeepsingh]

Is the False Positive and False Negative in ML problems same as Type I and Type II error in Hypothesis Testing? Or are they different? Does the decision matrix directly relate to the confusion matrix in ML Classification problems?

[@pragun1993]

The answer to which error should be minimized type 1 or type 2 / or which error is worse - is really unclear in the statisticians community. I guess it depends on the situation. Consider the example of deciding a person guilty or non guilty. Null hypothesis states that he is innocent. Alternate states that it has enough evidence to prove he is guilty. Now, when you commit a Type 1 error here - which is declaring a person guilty(rejecting Null) when he was really innocent(Null comes out to be true), it is more dangerous in a democracy than committing a type 2 error where you would have not rejected Null and called him innocent and set him free.

[@aadityachhitarka1938]

I like how is says no one is injured instead of saying they are dead cause of you

[@sarveshsawant5455]

Best video so far..Great work

[@mariamsaied6156]

you are awesome !.. for the first time I understand statistics :)

[@samasahara8043]

Great explanation ,thanks for you efforts...Keep going.

[@shionab8749]

A great way of teaching. Thank you so much. I have a doubt regarding the seriousness of Type 1 and Type 2 errors. I read that it actually depends on the situation. Can you please clarify it. Thank You!

[@punktart9956]

Brandon Foltz you hero

[@girijeshjha]

Status Quo was maintained and you falsely reported a change - Type 1 Status Quo changed and you failed to report it - Type 2 And it is not not hard to see why Type 2 is more problematic/dangerous. I am rejecting Null of my level of understanding and I am confident I am doing so without Type 1. Thanks!

[@prabh357]

hi, can you please explain how do we set null (H0) & Alternative (Ha) in case of a claim please.