Crash Course
Confidence Intervals: Crash Course Statistics #20
Be confident about your ability to understand statistics. The 20th installment of the Crash Course Statistics playlist, the informative YouTube video describes the meaning of confidence intervals and how they relate to normal...
Crash Course
Playing with Power: P-Values Pt. 3: Crash Course Statistics #23
What went wrong?! The 23rd video in the Crash Course Statistics playlist focuses on errors that occur in hypothesis testing when using p-values. It describes Type I and Type II errors and explains how one type of error might be...
Crash Course
P-Value Problems: Crash Course Statistics #22
Ponder the problems of p-values. After reviewing p-values from the last video, the narrator explains some drawbacks of using p-values for hypothesis testing in the 22nd installment of the Crash Course Statistics series. The video...
Crash Course
The Normal Distribution: Crash Course Statistics #19
It's normal to want to learn about normal distribution. The 19th installment of the Crash Course Statistics series focuses on how means of sample distributions show a normal distribution. It looks at the Central Limit Theorem and also...
Crash Course
Bayes in Science and Everyday Life: Crash Course Statistics #25
You can bet on Bayes. Continuing from the previous video, scholars learn about Bayesian statistics and hypothesis testing. The 25th installment of the Crash Course Statistics series applies these concepts to continuous data and to...
Crash Course
Test Statistics: Crash Course Statistics #26
From t to z, learn about the basics of test statistics. An engaging YouTube video discusses t-tests and z-tests to determine whether observed differences are statistically significant. The video also looks at how p-values play a role in...
Crash Course
T-Tests: A Matched Pair Made in Heaven: Crash Course Statistics #27
Pair a video with your lesson on t-tests. Viewers of an informative YouTube video, the 27th part of the Crash Course Statistics series, study two sample t-tests and paired t-tests. They see which test would be appropriate for a situation...
Crash Course
Degrees of Freedom and Effect Sizes: Crash Course Statistics #28
Give learners the freedom to learn about hypothesis testing. The 28th installment of the Crash Course Statistics series focuses on degrees of freedom and effect size. It looks at how these concepts relate to t-tests and t-distributions.
Crash Course
Chi-Square Tests: Crash Course Statistics #29
Chime in and learn about chi-square tests. An informative video describes when chi-square tests would be appropriate and how to perform chi-square tests. It looks at three different types: the goodness of fit test, the test of...
Crash Course
P-Hacking: Crash Course Statistics #30
Spot the fake research. The 30th installment of the Crash Course Statistics series explains p-hacking and the family wise error rate, which occurs when researchers attempt to weed out a statistically significant result even when one is...
Crash Course
The Replication Crisis: Crash Course Statistics #31
There is growing evidence that suggests the results of many studies are not reproducible. The 31st lesson of the Crash Course Statistics playlist discusses possible causes of the problem and identifies solutions since producibility is...
Crash Course
ANOVA: Crash Course Statistics #33
How do you account for multiple variables when analyzing data? Following a lesson on regression, the 33rd lesson in the Crash Course Statistics series examines the ANOVA, analysis of variances, method of determining differences between...
Crash Course
ANOVA Part 2: Dealing with Intersectional Groups: Crash Course Statistics #34
A statistic of interest is often affected by multiple variables. Continuing from the previous lesson in the Crash Course Statistics playlist, the instructor explains how to apply the ANOVA calculations to multiple variables that have an...
Crash Course
Fitting Models Is like Tetris: Crash Course Statistics #35
Different statistical models tell people unique information about data. The 35th lesson in the Crash Course Statistics series describes two different statistic models: ANOVA and Repeated Measures ANOVA. The narrator of a short video...
Crash Course
Supervised Machine Learning: Crash Course Statistics #36
Use math to help predict the future. Viewers of the 36th Crash Course video covering statistics hear about machine learning. They see how logistic regression, linear discriminant analysis, and K nearest neighbors are all models that help...
Crash Course
Unsupervised Machine Learning: Crash Course Statistics #37
Let the machines do what they do best. The 37th installment of the Crash Course Statistics series focuses on unsupervised machine learning. It describes two methods, k-means and hierarchical clustering, and provides examples for each.
Crash Course
Big Data Problems: Crash Course Statistics #39
The big, the bad, and the ugly of data. The resource picks up from the description of big data and discusses the possible problems. Using examples, the 39th video in the series of Crash Course statistics explains how some use big data...
Crash Course
Neural Networks: Crash Course Statistics #41
Combine multiple inputs to get one output. An engaging video discusses neural networks and how they work on a basic level, that of taking several inputs and determining a single output. Using examples, the narrator defines different...
Crash Course
When Predictions Fail: Crash Course Statistics #43
The world relies on statistics for important predictions like earthquakes, volcano eruptions, and winners of presidential elections. Examine some popular failed predictions and identify their flaws while watching the 43rd installment of...
Crash Course
When Predictions Succeed: Crash Course Statistics #44
Statistics show people eat more berries when the weather is nice. Young entrepreneurs learn how stores use statistics like this to plan their advertising and sales strategies. The narrator uses various examples to show how important...
Khan Academy
Khan Academy: Cumulative Geometric Probability (Greater Than a Value)
Probability for a geometric random variable being greater than a certain value.
Massachusetts Institute of Technology
Mit: Blossoms: Are Random Triangles Acute or Obtuse?
An MIT mathematics professor examines the probability of a random triangle being either obtuse or acute in a video [32:44] on geometrical probability. Video is accompanied by a teacher's guide, transcript, and several links on linear...
Khan Academy
Khan Academy: Probability: Probability 1 Module Examples
Video lesson showing how to solve three examples of simple probability, including geometric probability. Includes link to additional practice problems. [9:56]
Crash Course
Crash Course Statistics #16: Geometric Distributions
Geometric probabilities, and probabilities in general, allow us to guess how long we'll have to wait for something to happen. This video discusses how they can be used to figure out how many Bertie Bott's Every Flavour Beans you could...