1. Closing comments
Congratulations! You have used statistical thinking to study issues both fascinating and controversial.
2. Fractional improvment in finals
You showed that no, as a whole swimmers don't really swim faster in finals.
3. Quantifying the Current Controversy
You found a current in a pool that no longer exists.
4. Inter-earthquake times of the Parkfield sequence
You showed that it is not implausible that the Parkfield sequence comes from a Poisson process.
5. Oklahoma earthquakes
And you showed that once fracking started, Oklahoma got a lot more earthquakes, and that the magnitudes of them did not change much.
6. Active bout lengths
And you shouldn't forget that you found that melatonin production is key for little zebrafish to sleep.
Each of these studies offers different challenges, and each requires some domain-specific knowledge.
7. Each dataset offers unique challenges
In swimming, knowledge about the manufacture of the pools and how they operate is necessary to do something to mitigate current effects.
8. Each dataset offers unique challenges
In earthquake studies, we have not taken into account slip/strain history or other geophysics, which would help understanding magnitudes and timing of quakes. Nonetheless, just by using your hacker stats skills on datasets, you have learned from the data, even in complex scenarios. Thus, your ability to learn from data can be very valuable when you work in collaborative settings.
9. My goals for you
One of my goals for this case studies course was to demonstrate to you the great opportunity you have as a data scientist to learn and contribute to different areas of study.
10. My goals for you
Naturally, I also wanted you to sharpen your hacker stats skills, including computing bootstrap confidence intervals and permutation and bootstrap hypothesis tests. Along the way, you learned some new concepts, like the Kolmogorov-Smirnov test, location parameters, and log-linear regression.
11. My goals for you
I wanted to emphasize the pipeline for statistical inference, in order of importance, from EDA to parameter estimation with confidence intervals to hypothesis tests.
12. My goals for you
Finally, as important as any of the others goals, I wanted to use the case studies to help you learn to frame precise questions to ask of your data.
13. Go forth and data!
Having completed this course, you have accomplished all of those goals. I hope that as a result you feel more confident, and also intrigued, as you head into your next data project. Data science is a big, beautiful field. Enjoy it!