As much as we like to think that statistics is an exact science, in fact, there is a lot of room for uncertainty when you perform an analysis. In this video, explore some of the limits of hypothesis testing to give you some cautions about your data and yo
- [Instructor] As much as data analysts like to think that statistics is an exact science, in fact there is a lot of room for uncertainty. In this movie, I want to go over some of the limits of hypothesis testing and give you some cautions about your data and your analysis. The first caution is that even if your analysis meets the 95% certainty gold standard that most analysts use, you will still be wrong one out of 20 times, and if you've ever performed any analysis or even flipped a coin and gotten four tails in a row, or four heads, then you know how likely it is that events can happen one out of 16, one out of 20, or even one out of 100 times.
And next, I'm sure you're tired of hearing this, but correlation is not causation. Just because two things happen to occur at the same time does not mean that they are related. However, it does tell you where you can start looking. If two things tend to happen together, and based on your knowledge of your business and of the world, you think that they might be related, then that's where you can start looking. So the next time someone argues that your data shows correlation and doesn't mean causation, you can explain the real world mechanism by which the two events could be linked and your argument will be that much stronger.
- Distinguish between the mean, median, and mode.
- Describe the relationship between variance and standard deviation.
- Identify a nondirectional hypothesis.
- Point out the difference between COVARIANCE.P and COVARIANCE.S.
- Explain correlation.
- Analyze Bayes’ rule.