Biostatistics: Hypothesis Testing | USMLE Step 1 Crash Course (FA 2020)
ฝัง
- เผยแพร่เมื่อ 15 ต.ค. 2024
- The scientific process starts with a hypothesis, but what are the outcomes of hypothesis testing? Well, in this video, I'll be covering them!
Want to support me further? 👉 www.buymeacoff...
If you appreciate all the hard work that went into this video, please show it some love and drop me a like & comment! If you'd like to support me even that bit more, you can share this video with your friends and on social media! Also, subscribe and hit that notification 🔔 to never miss any of my future uploads!
📝 Notes/Errata:
1) None; please comment if you found an inconsistency and I'll be sure to add it here along with the time stamp!
Social Media:
🐦 Twitter: Khalemedic
📸 Instagram: Khalemedic
🙋🏻♂️ Who am I?
I'm Khaled, a final-year medical student, and I make videos on quite a few different topics within the scope of medicine such as reacting and breaking down medical shows, studying for exams, discussing important health issues, etc... I hope that my videos help you in any way, shape, or form and that you enjoy them regardless of your background.
Medicine is quite the challenging topic, but I don't see why we can't enjoy it together!
Disclaimer: The information and education material contained herein is meant to promote the general understanding of medical topics by healthcare professionals and related parties. Such information is not meant or intended to serve as a substitute for a healthcare professional's clinical training, experience, or judgment. For patient’s care or regarding your own health please consult your doctor or refer to the most recent evidence based practice.
Have been studying this for last 2 years but never understood it right. Thank you so much
Thanks so much for the clear content. you are a great teacher. My question is from the last example, it says that Null hypothesis is accepted when in reality, it is false - doesn't that make it an alpha error?
No, I believe you’re mixing it up. An alpha error is when you wrongly accept the alternate hypothesis. A beta error is when you wrongly accept the null hypothesis.
Here’s another way to look at it. If you accepted the null hypothesis, it is not possible to make an alpha error, since you MUST reject it in order for it to even be possible to make an alpha error.
I hope this clears it up.
I’m watching all your video but I really don’t understand this topic , specially the initial portion. Is there any way to understand it? N why are you connecting two graphs I really don’t understand?can you please explain it?TIA
Firstly, don't beat yourself up about it! It was a very difficult concept for me to wrap my head around the first time I ever learned it.
This usually takes me around an hour to fully explain to my peers when they first learn it. I doubt that text would help me here so I'll leave you a link to where I fully explain this (it is very long but extremely thorough): th-cam.com/video/JhQEyrp4Nuo/w-d-xo.html
@@Khalemedic thankyou for responding . I really appreciate it. 2nd video is too long still I will try to watch it. Thankyou
Same here. I didnt get why 2 graphs and what are we trying to deduce from there
@@sandhya797 I recommend you check the video linked in one of my comments. It's quite long but extremely thorough. I suggest you immediately skip to 1:00:00 for the explanation of the mind map. If it felt too rushed, then please go through the entire video.
@@Khalemedic Thanks Khaled. Appreciate it.💕💕 Will watch it
Thanks dr khaleed
You're most welcome!
Nice explanation Doc!
i still have some doubts on my side thanks to uworld😬. Why is it that when significance level is reduced we decrease type one error and increase confidence level? Yet when significance level is reduced the study will have less statistical power to detect a significant difference so > type two error? Sorry if my question is unclear:/
Hey Lana, first off I’m glad you found the explanation beneficial!
Note: Alpha = type 1 error // Beta = type 2 error
Now onto your question, when I draw this mindmap, there is one single point that once crossed will allow us to reject the null hypothesis. It is important that both alpha and beta errors touch that SPECIFIC point as it is simply impossible for it to be both an alpha AND a beta error.
Now if you draw this mindmap, as alpha becomes smaller, you have to push that cutoff where we reject the null hypothesis a bit to the right to follow alpha. But wait, that means we also have to widen beta a little bit since it also has to touch that point/cutoff. The result is a smaller alpha error and a bigger beta error.
Since power will always be the complement of beta, it would decrease in such a situation. I know it can get rather confusing especially when you’re just reading a body of text such as this. Feel free to dm me on twitter or instagram if you still feel a little confused about the concept. Either way, I hope you benefitted from this comment and that I answered your question!
@@Khalemedic thank you so much !
Your explanation put things in perspective 😇