1. Course wrap-up video
You've completed the course, what an amazing accomplishment!
2. Bias and sampling
You've learned how bias and sampling can creep into your analysis, and the havoc they can wreak if not properly managed. You've also learned how point estimates and confidence intervals differ in your ability to make inference based on your calculations.
3. Hypothesis testing
You then explored a wide range of hypothesis tests for all sorts of situations. This included parametric tests for normally distributed data, non-parametric tests for other distributions, tests for correlation, and tests for normality.
4. Effect sizes
You then learned how to take inference beyond p-values by measuring effect sizes. Effect sizes are key in understanding the degree to which a treatment works, and you mastered them!
5. Simulation, randomization and meta-analysis
Finally you learned extremely flexible tools like bootstrapping and permutation tests for working with any data, as well as how to combine research done by others using Fisher's method.
6. Going forward
All of these tools allow you to make sound data-driven decisions, and produce inference that you can back up. Consider checking out other DataCamp courses which use these skills in domain-specific applications.
7. Let's practice!
Congratulations, and go use your new-found tools to make a difference!