False Positives vs. False Negatives in Science and Statistics (Type 1 and Type 2 Error)

thank you sir

you are the best

Type I error (falsely rejecting a null hypothesis) and type II error (falsely accepting a null hypothesis).

False positive is alpha in the hypothesis testing? Actually lawful but the jury finds him guilty.
False negative is Beta in the hypothesis testing?
Actually criminal but the jury finds him not guilty.

I take it that the null hypothesis is considered a negative and the alternate hypothesis is considered a positive.

Thank you

I really enjoyed the lesson. Thanks for enlightening me on the context because the type one error is known to be worse, but after watching your video, I have to understand the context and be wiser regarding the conclusion and required action.

Well it depends on the benefits that come from the results , i mean newton theory had a beneficial outcome although it is not totally true

Finally this topic makes sense. Thank you!

you are by far the best at explaining this stuff

It's a little difficult to make a claim about what is worst in science. False positives
a re far more commons than negative positives, given those conditions, it's easier to run into false positive than with negative positives, because we do care about the sample size and the spread or variability of the data instead of caring about the randomness and uncertainty around false positives more frequently. It's kind of bias or something like that with the uncertainty.

let us suupose there are 100 students in each school and we measure the height of all students and compare between two school, can we say we can get 100% errorless result?

The first example is bad. It helps with nothing. I've given it an hour with no clear understanding between them, nor perspective of what is true. You cannot ask this question and get a right answer 100% of the time.

Excellent explanation on these concepts especially to laymen. thank you so much

Great video. Many thanks.

Hey doctor Jeff, having a strong feeling that you will rise fast and become one of the youtibe heriage of education.

I believe that writing about a range of topics is a good way to improve one's understanding. I find your closing question insightful. Thank you for your lecture.

So out of 1000 student schools, how large would the sample sizes of each school have to be to minimize the possibility of a false positive/negative?

In information retrieval these are called recall and precision.