Text: Recap + Next Steps

QUIZ QUESTION::

Review Quiz

Match the statements below to the most appropriate term to recap the big ideas of this lesson.

ANSWER CHOICES:

Statement	Term
Sampling with replacement.
Confidence intervals provide a range of values that are possible for a _.
The distribution of a statistic (any statistic).
By simulating the distribution of our statistic(s) of interest using bootstrapping, we can remove the bottom 1.5% and top 1.5% of the sampling distribution to build a __.

SOLUTION:

Statement	Term
Sampling with replacement.
By simulating the distribution of our statistic(s) of interest using bootstrapping, we can remove the bottom 1.5% and top 1.5% of the sampling distribution to build a __.
The distribution of a statistic (any statistic).
Confidence intervals provide a range of values that are possible for a _.

Recap

In this lesson, you learned:

How to use your knowledge of bootstrapping and sampling distributions to create a confidence interval for any population parameter.
You learned how to build confidence intervals for the population mean and difference in means, but really the same process can be done for any parameter you are interested in.
You also learned about how to use Python built-in functions to build confidence intervals, but that these rely on assumptions like the Central Limit Theorem.
You learned about the difference between statistical significance and practical significance.
Finally, you learned about other language associated with confidence intervals like margin of error and confidence interval width, and how to correctly interpret your confidence intervals. Remember, confidence intervals are about parameters in a population, and not about individual observations.

What's Next

The topics of confidence intervals and hypothesis testing essentially do the same thing, but depending on who you talk to or what source you are reading from, it is important to understand both.

In the next lesson, you will be learning about hypothesis testing!