Hypothesis Testing: USEFUL Info + Concepts! Part 1 of 2

This video serves as an introduction to hypothesis testing in statistics. I discuss the the null hypothesis, the alternative hypothesis, type 1 error, type 2 error, discuss a real life example and work through the implications of our decisions. This video introduces terminology and concepts however I do not perform an actual hypothesis test using data and computations in this video.

[patrickjmt]

More statistics videos? Videos on R? Any thoughts?

[michaelbacay]

Been watching your videos way back in college up until now. Thank you for making these videos 💙

[dendopopo]

Watched your videos few years back when i was still studying. Your videos helped me a lot when i was a student. Hopefully you dont stop making videos and help other students who are noob in maths like me 😂 thank you

[tonywang]

Thank you; you are one of those teachers having an unexplainable calming effect on me.

[onlyonecjb]

Thank you for taking the time to make and share these helpful videos.

[vernardoortega]

Thanks, Patric I remember watching your videos a few years back when I was taking calculus.

[thrownmeteor]

Whoa! What program are you using to make this?! It looks so clean!

[sgiri]

Sir, one doubt i got is we are proposing two hypotheses. Namely, null and alternative ones. We should check whether null hypothesis is true or not. For that, we evaluate test statistic(Z or t statistic). If the test statistic falls in the critical region with respect to either 5% significance levels or 1% significance level. My intuition says that if it falls in the critical region, it is normal to observe deviations and occured by some random chance. There is no such evidence to reject the null hypothesis and therefore we should accept it. But in the books, they go other way round. Why is that the case ?