Lillian L's Enrolled Lessons

10 minStatistics lesson6 CQ
Statistics is the science of analyzing data, and in this lesson, you'll learn the basics! Discuss statistical modeling and parameterizing models, too.
with Mark HuberStatistics is the science of analyzing data, and in this lesson, you'll learn the basics! Discuss statistical modeling and parameterizing models, too.

13 minStatistics lesson7 CQ
In this lesson, discover the building blocks of probability, including random variables, set notation, and two important rules for calculating probabilities.
with Mark HuberIn this lesson, discover the building blocks of probability, including random variables, set notation, and two important rules for calculating probabilities.

12 minStatistics lesson7 CQ
There are two main types of random variables: discrete and continuous. In this lesson on foundational concepts in statistics and probability, see how they work!
with Mark HuberThere are two main types of random variables: discrete and continuous. In this lesson on foundational concepts in statistics and probability, see how they work!

11 minStatistics lesson6 CQ
Discover the Strong Law of Large Numbers, discrete random variables, and learn how to calculate variance in this lesson on statistics and probability.
with Mark HuberDiscover the Strong Law of Large Numbers, discrete random variables, and learn how to calculate variance in this lesson on statistics and probability.

14 minStatistics lesson8 CQ
Conditional probabilities add extra information to random variables. They're calculated using the conditional probability formula and Bayes' Rule, covered here.
with Mark HuberConditional probabilities add extra information to random variables. They're calculated using the conditional probability formula and Bayes' Rule, covered here.

11 minStatistics lesson6 CQ
The Central Limit Theorem says that the sum of random variables tends to look like a normal distribution. Use this to approximate probabilities in this lesson!
with Mark HuberThe Central Limit Theorem says that the sum of random variables tends to look like a normal distribution. Use this to approximate probabilities in this lesson!

13 minStatistics lesson7 CQ
This statistics lesson covers the two most important point estimators: the sample average for the mean, and the population variance for the variance.
with Mark HuberThis statistics lesson covers the two most important point estimators: the sample average for the mean, and the population variance for the variance.

14 minStatistics lesson8 CQ
This lesson covers the idea of the pvalue, which is a numerical way of characterizing the evidence against a particular hypothesis with a test statistic.
with Mark HuberThis lesson covers the idea of the pvalue, which is a numerical way of characterizing the evidence against a particular hypothesis with a test statistic.

8 minStatistics lesson5 CQ
Confidence intervals contain all numbers between a and b, and can be calculated with the Central Limit Theorem, which is covered in this statistics lesson!
with Mark HuberConfidence intervals contain all numbers between a and b, and can be calculated with the Central Limit Theorem, which is covered in this statistics lesson!

13 minStatistics lesson7 CQ
Bayesian statistics treats the parameters as if they are random variables. In this stats lesson, use Bayes' Rule to update the distribution of the parameters.
with Mark HuberBayesian statistics treats the parameters as if they are random variables. In this stats lesson, use Bayes' Rule to update the distribution of the parameters.