Multiple comparisons | Wikipedia audio article
Channel: wikipedia tts
Date: 13/01/2019

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Multiple_comparisons_problem


00:00:49 1 History
00:01:36 2 Definition
00:04:56 2.1 Classification of multiple hypothesis tests
00:07:13 3 Controlling procedures
00:15:49 4 Large-scale multiple testing
00:18:55 4.1 Assessing whether any alternative hypotheses are true
00:19:50 5 See also
00:21:35 6 References



Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago.

Learning by listening is a great way to:
- increases imagination and understanding
- improves your listening skills
- improves your own spoken accent
- learn while on the move
- reduce eye strain

Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone.

Listen on Google Assistant through Extra Audio:
https://assistant.google.com/services/invoke/uid/0000001a130b3f91
Other Wikipedia audio articles at:
https://www.youtube.com/results?search_query=wikipedia+tts
Upload your own Wikipedia articles through:
https://github.com/nodef/wikipedia-tts
Speaking Rate: 0.8886236599618428
Voice name: en-US-Wavenet-C


"I cannot teach anybody anything, I can only make them think."
- Socrates


SUMMARY
=======
In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. In certain fields it is known as the look-elsewhere effect.
The more inferences are made, the more likely erroneous inferences are to occur.  Several statistical techniques have been developed to prevent this from happening, allowing significance levels for single and multiple comparisons to be directly compared.  These techniques generally require a stricter significance threshold for individual comparisons, so as to compensate for the number of inferences being made.