Statistics and Probability Teacher Resources
What are the chances you can make it through one day without using or seeing statistics? It's highly unlikely, and that's why you can find resouces that cover tables, graphs, statistical models, and more, right here.
Showing 1,335 resources
Soft Schools
Soft Schools: Probability and Statistics Quiz
Students are asked to find the mean, median, mode, and range of a data set. Also, they must be able to interpret graphs and tables, and graphically represent data. The quiz is multiple choice and consists of nine questions, and a summary...
Crash Course
Crash Course Statistics #23: P Values: Playing With Power
A video looking at how the p value can be misinterpreted. Review over examples in this video. [12:15]
Crash Course
Crash Course Statistics #32: Regression
Using the framework of the General Linear Model, the Regression Model is explained. Points discussed include the following: Regression Line, Residual Plot, F Test.
Crash Course
Crash Course Statistics #34: Anova: Dealing With Intersectional Groups
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.
Crash Course
Crash Course Statistics #33: Anova
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.
Crash Course
Crash Course Statistics #30: P Hacking
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.
Crash Course
Crash Course Statistics #29: Chi Square Tests
The moderator analyzes categorical variables by using Chi Square Tests: Goodness of Fit, Tests of Independence, and Test of Homogeneity.
Crash Course
Crash Course Statistics #38: Intro to Big Data
Discusses how Big Data is collected and used.
Crash Course
Crash Course Statistics #37: Unsupervised Machine Learning
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...
Crash Course
Crash Course Statistics #36: Supervised Machine Learning
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.
Crash Course
Crash Course Statistics #39: Big Data Problems and Solutions
Explains the downside of Big Data and offers solutions to everyday problems. Bias is discussed as related to data.
Crash Course
Crash Course Statistics #22: P Values Problems
A video over viewing how p-values can be misinterpreted and how the logic of p-values can be misunderstood. [12:14]
Science Buddies
Science Buddies: Dice Probabilities
You're playing Monopoly with a friend, and you've already got Park Place and you really, really want to get Boardwalk. If you're on Pacific Avenue, what are the chances you'll reach your goal? Here's an easy project that will show you...
Virtual Nerd
Virtual Nerd: What Are Compound Events?
What if we want to find the probability of more than one event occurring? This would be a compound event. Watch this video for an explanation and example. [3:29]
Khan Academy
Khan Academy: Statistics: Sampling Distribution Example Problem
Video example of using a sample distribution to solve a problem determining the probability that a sample mean is below a certain number. Includes example of finding a z-score and looking it up in a table to determine the probability....
Khan Academy
Khan Academy: Statistics: Normal Distribution: Standard Normal & Empirical
Video example of giving the mean and standard deviation of the standard normal distribution and finding probabilities using the empirical rule. [8:16]