FAQ: Hypothesis Testing with R - P-Values

This community-built FAQ covers the “P-Values” exercise from the lesson “Hypothesis Testing with R”.

Paths and Courses
This exercise can be found in the following Codecademy content:

Learn R

FAQs on the exercise P-Values

There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply (reply) below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply (reply) below!
You can also find further discussion and get answers to your questions over in #get-help.

Agree with a comment or answer? Like (like) to up-vote the contribution!

Need broader help or resources? Head to #get-help and #community:tips-and-resources. If you are wanting feedback or inspiration for a project, check out #project.

Looking for motivation to keep learning? Join our wider discussions in #community

Learn more about how to use this guide.

Found a bug? Report it online, or post in #community:Codecademy-Bug-Reporting

Have a question about your account or billing? Reach out to our customer support team!

None of the above? Find out where to ask other questions here!

In the section used to describe Type I and II errors, I would recommend modifying the language to discuss whether there is a statistically significant difference rather than a meaningful correlation, since correlations are a separate statistical topic (which R can also be used to ascertain, but it is not related to hypothesis testing within this lesson). I think this will aid in understanding for those who have had less exposure to statistical concepts. There are also a few typos within the lesson (volleball in section 7, for instance).

1 Like

All four options for this exercise’s multiple-choice question are false.

The correct interpretation is NOT “There is a 20% chance that the difference in average weight of green and red apples is due to random sampling.”

The correct interpretation is “There would be a 20% chance of observing a difference at least as big as the observed difference anyway, even if all differences are only due to random sampling.”

It is impossible in traditional hypothesis testing to say anything about the posterior probability, given an observed difference, that the null is true. That’s only possible in Bayesian statistics (where it depends also on the prior probability; “extraordinary claims require extraordinary evidence” and all that). But we aren’t doing Bayesian statistics here.

In conditional probability terms, p-values tell you p(observation|null), not p(null|observation). These are completely different.

2 Likes