The ANOVA DAY,ANOVA Model and how to deal with intersectional groups. Discussed are the following: Factorial ANOVA, F Test, Sums of Squares Between Groups, ETA Squared, Interaction Plot, Main Effects.

From the framework of the General Linear Model, the ANOVA--Analysis of Variance is discussed. Also explained are the following: R.A. Fisher's Potato Study, Sums of Squares, Sums of Squares for Error, Omnibus Test.

Moderator discusses P-Hacking or data gone wrong, using the framework of Null Hypothesis Significance Testing. Family Wise Error Rate and Bonferroni Corrections are also explained.

The moderator analyzes categorical variables by using Chi Square Tests: Goodness of Fit, Tests of Independence, and Test of Homogeneity.

Discusses how Big Data is collected and used.

Unsupervised Machine Learning have not true categories to compare in order to predict a future outcome. Therefore, two types of clustering are applied: K-Means and Hierarchical clustering. Centroid, Silhouette Score, Agglomerative...

Supervised Machine Learning predicts future outcomes by applying the following models: Logistic Regression, Confusion Matrix, and K-Nearest Neighbor. Also explained are Linear Discriminant Analysis and Bayes Rule.

Explains the downside of Big Data and offers solutions to everyday problems. Bias is discussed as related to data.

Understanding an insurance company's sense of my chances of dying.

A video reviewing over on p-values and Null Hypothesis Significance Testing (or NHST). Learn how to use the NHST and p-value to tell you if something is statistically significant, but as you'll see that doesn't necessarily mean the...

Do you know how close your predictions were to the actual value? This video will review over examples of both t-tests and z-tests to explain how critical values and p values are different ways of telling the same statistical information....

A video looking at how the p value can be misinterpreted. Review over examples in this video. [12:15]

A video over viewing how p-values can be misinterpreted and how the logic of p-values can be misunderstood. [12:14]

A video [48 mins, 48 sec] explaining 21 different math concepts to help students prepare for the ACT including; circumference; averages; probability; multiplication counting principle; functions; circles; percentages; factoring; rules of...

Sal solves a conditional probability example where he thinks about probabilities like P(A | B) where the events are about lunch and breakfast.

Sal explains the difference between a subset, a strict subset, and a superset. He also explains the notation behind these ideas.

Sal moves onto more challenging set ideas and notation like the universal set and absolute complement.

Sal shows examples of intersection and union of sets and introduces some set notation.

Sal summarizes the set operations that he has discussed in the previous videos.

Probability of compound events. The Addition Rule.

In this Wireless Philosophy video, Nina Emery (Mount Holyoke College) explores the nature of chance and probability. [7:27]

This video serves as an introduction to Markov Chains. [7:15]

This lesson demonstrates how to draw a conclusion based on the results of a probability experiment. It is 5 of 8 in the series titled "Drawing Conclusions."

This lesson demonstrates how to draw a conclusion based on the results of a probability experiment. It is 8 of 8 in the series titled "Drawing Conclusions."