Accuracy and precision | Wikipedia audio article | Wikipedia audio article
Channel: Shishir Kumar Sahu
Date: 18/11/2018

This is an audio version of the Wikipedia Article:
Accuracy and precision | Wikipedia audio article

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.

You can find other Wikipedia audio articles too at:
https://www.youtube.com/channel/UCuKfABj2eGyjH3ntPxp4YeQ

You can upload your own Wikipedia articles through:
https://github.com/nodef/wikipedia-tts



"The only true wisdom is in knowing you know nothing."
- Socrates



SUMMARY
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Precision is a description of random errors, a measure of statistical variability.
Accuracy has two definitions:

More commonly, it is a description of systematic errors, a measure of statistical bias; as  these cause a difference between a result and a "true" value, ISO calls this trueness.
Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness.In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured.  In the first, more common definition above, the two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither.