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AntoineSoetewey / statsandr

A blog on statistics and R aiming at helping academics and professionals working with data to grasp important concepts in statistics and to apply them in R. See www.statsandr.com
http://statsandr.com/
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blog/hypothesis-test-by-hand/ #48

Closed utterances-bot closed 3 years ago

utterances-bot commented 3 years ago

Hypothesis test by hand - Stats and R

Learn the structure of a hypothesis test by hand, illustrated by 4 easy steps using the critical value, p-value and confidence interval methods

https://statsandr.com/blog/hypothesis-test-by-hand/

drfurtado commented 3 years ago

Excellent write up; I am always learning something new from your posts. God bless you!

AntoineSoetewey commented 3 years ago

Excellent write up; I am always learning something new from your posts. God bless you!

Thanks for your kind words!

vonjd commented 3 years ago

For a gentle introduction and some intuition see also: https://blog.ephorie.de/from-coin-tosses-to-p-hacking-make-statistics-significant-again

AntoineSoetewey commented 3 years ago

For a gentle introduction and some intuition see also: https://blog.ephorie.de/from-coin-tosses-to-p-hacking-make-statistics-significant-again

Thanks for your input!

abuabara commented 3 years ago

Incredible post, amazing. I use R for research but I teach introductory statistics mostly using Excel. Your posts are very cool and thought-provoking. Thanks a lot for sharing! ;)

AntoineSoetewey commented 3 years ago

Incredible post, amazing. I use R for research but I teach introductory statistics mostly using Excel. Your posts are very cool and thought-provoking. Thanks a lot for sharing! ;)

Thank you for your feedback! Glad you find them useful.

sicabi commented 3 years ago

Thank you very much for this explanation. Several textbooks and teachers never get to convey these difficult concepts and procedures as clearly as this article.

AntoineSoetewey commented 3 years ago

Thank you very much for this explanation. Several textbooks and teachers never get to convey these difficult concepts and procedures as clearly as this article.

Thanks for your feedback!

zhou8p commented 3 years ago

Great article! I am a data science student from springboard.com, my mentor pointed me to this article, which I found truly helpful.
One question is on the method 2, step3, "1. The critical value is -2.189", do you mean the t-stat computed at step2?

Also, could I summary these 3 methods in a way as below? Method 1, is to compare the t-stat with the critical value, which is the line drawn on the distribution graph used to reject the null hypothesis. Method 2, is to compare the significance level alpha with the p-value, which is a probability represented by the sum of the area under the curve. Method 3, is to compare the target parameters with the confidence interval, which is a range of number. And to better memorize them against on the distribution graph, I consider the 3 method as line - area - interval.

AntoineSoetewey commented 3 years ago

Great article! I am a data science student from springboard.com, my mentor pointed me to this article, which I found truly helpful.

Thanks for your feedback!

One question is on the method 2, step3, "1. The critical value is -2.189", do you mean the t-stat computed at step2?

Yes, indeed it is the t-stat and not the critical value. I corrected the typo in the article. Thanks!

Also, could I summary these 3 methods in a way as below? Method 1, is to compare the t-stat with the critical value, which is the line drawn on the distribution graph used to reject the null hypothesis. Method 2, is to compare the significance level alpha with the p-value, which is a probability represented by the sum of the area under the curve. Method 3, is to compare the target parameters with the confidence interval, which is a range of number. And to better memorize them against on the distribution graph, I consider the 3 method as line - area - interval.

Yes, exactly, that's a very good (and concise) summary!