How do I understand type I error and type II error when talking about hypothesis?
If “one picture is worth a thousand words” then this should help you understand what are type one and type two errors in statistics.
If I would explain otherwise a type I error is the incorrect rejection of a true null hypothesis or a "false positive". The doctor on the left just made an incorrect rejection of his null hypothesis “The man is not pregnant”.
A type II error instead is an incorrect retaining of a false null hypothesis or a "false negative". In fact the doctor on the right just made on incorrect retaining of her null hypothesis “The woman is not pregnant”.
Nice
@alketcecaj got you a $1.89 (1.0%) @minnowbooster upgoat, nice! (Image: pixabay.com)
Want a boost? Click here to read more about @minnowbooster!
The @OriginalWorks bot has determined this post by @alketcecaj to be original material and upvoted it!
To call @OriginalWorks, simply reply to any post with @originalworks or !originalworks in your message!
To enter this post into the daily RESTEEM contest, upvote this comment! The user with the most upvotes on their @OriginalWorks comment will win!
For more information, Click Here! || Click here to participate in the @OriginalWorks writing contest!
Special thanks to @reggaemuffin for being a supporter! Vote him as a witness to help make Steemit a better place!
@OriginalWorks check here my original work
@OriginalWorks bot has found some similar content online. Please reply to this message if you believe this to be wrong.
That is my original post on Quora @OriginalWorks