Excel 2013 Statistical Analysis #30: Bayes’ Theorem to Calculate Posterior Probabilities

Topics in this video:
1. (00:11) Define and give example of Bayes’ Theorem with handwritten notes
2. (05:17) Discussion about how Bayes’ Formula is like of earlier Conditional Probability Formulas: (And/Joint Probability)/(Marginal Probability)
3. (08:45) Excel Example 1 with Tree Diagram (Probability Tree) and Table Format for calculating Bayes’ Theorem. CPA Score Example.
4. (12:52) Excel Example 2: Table Format for calculating Bayes’ Theorem. Police Data Example.
5. (14:41) Single Cell Formula for Bayes’ Theorem using SUMPRODUCT function.

[adnansafat]

I love the series and the teacher, and I wish all educational institutes had enthusiastic, interested teachers like him. Bravo! Thank you, Mike. We are very much thankful to you :)

[rodrigocustodio]

The most talented teacher I have ever seen, Mike is extremely intelligent yet a very humble person, thank you, Mike, for replying to my comments, I genuinely wish you have been my teacher at uni. You present any material in such a level of excellence that anything becomes easy to understand.

[excelisfun]

Excel 2013 Statistical Analysis #30: Bayes’ Theorem to Calculate Posterior Probabilities
Topics in this video:
1. (00:11) Define and give example of Bayes’ Theorem with handwritten notes
2. (05:17) Discussion about how Bayes’ Formula is like of earlier Conditional Probability Formulas: (And/Joint Probability)/(Marginal Probability)
3. (08:45) Excel Example 1 with Tree Diagram (Probability Tree) and Table Format for calculating Bayes’ Theorem. CPA Score Example.
4. (12:52) Excel Example 2: Table Format for calculating Bayes’ Theorem. Police Data Example.
5. (14:41) Single Cell Formula for Bayes’ Theorem using SUMPRODUCT function.

[zhouyinwei]

Watched twice of the PDF explanation part before fully understand how the result comes, I hate statistical which is become more and more complicated while my brain is just not enough to catch on, but I love the course which explains much more clear than the book and really helps a lot, thanks Mike again for bringing the great course!

[begaimkarynbaeva]

love this series of videos. easy to learn hard stuff!

[JoshuaDHarvey]

Never mind, I found your video 2010 statistics 43 which explains exactly this way. For anyone struggling to understand check out that video and/or 2010 #42 video is exactly like this video just filmed a while ago

[JoshuaDHarvey]

Great video, but I wish at the end of each practice we would have put the numbers in a cross tab table to help tie the context of what we had been learning in previous videos together with this harder to understand topic of tree diagrams. Otherwise we are just trying to rote memorize which is a bad way of learning as far as recall goes

[OzduSoleilDATA]

Excellent. I like the set-up and introduction with the handwritten notes.

[burinyakis]

thanks for this. i have no stats background. but you present it in a way that looks easy enough to understand. in the example the initial probability 0.25, and also those additional information are already assumed and given.

how about if I need to start from scratch?
say i have these measurement data using an instrument 29, 100, 180, 300, 470, 520, 490, 420, 340, 220 and 50meters while the actual or reference equipment read a few micrometers higher than those, using least square adjustment computation how can i calculate the a priori and a posteriori error?

thnx

[deedubdolphinsdialogue]

Does anyone have a video on how to use decision trees and the utility function?

[ikark]

Hi Mike, It's really cool series of videos, I love to crunch it then all the daily magic tricks is already watched :)
Could you please explain little more about garage examle. What does it mean in two words that result of formula 0.44 & 0.55? Is this an estimation of reason of already heppened event of theft? Am I right?