TMW Media
Mean, Median & Mode
This program covers the important topic of Mean, Median, and Mode in Probability and Statistics. We begin by discussing what mean, median, and mode is and why it is important. Next, we solve several problems that involve these concepts...
Science360
Greenstreets Drexel University researchers investigate urban ecosystem improvements
"Greenstreets" are specially engineered vegetated areas, such as medians and traffic islands, with benefits that go beyond beautifying a city's landscape. From managing stormwater to alleviating air pollution, greenstreets can provide...
Crash Course
Intro to Big Data: Crash Course Statistics #38
What makes data big? The 38th installment in the series Crash Course Statistics provides a definition of big data and its origins. It shows various methods and resources on how to collect big data and how companies use big data for a...
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
Mean, Median, and Mode: Measures of Central Tendency: Crash Course Statistics #3
If you have two feet, you have more than the average number of feet! Explore the meaning of the numbers of measures of central tendency of different data sets with the third of five lessons in a video statistics playlist. Using unique...
Crash Course
Charts Are Like Pasta - Data Visualization Part 1: Crash Course Statistics #5
Clever marketers can use visual statistics to mislead their target populations. Explore these visual misrepresentations with a video lesson from a larger statistics playlist. The lesson instructor explains visual representations of both...
Crash Course
Plots, Outliers, and Justin Timberlake - Data Visualization Part 2: Crash Course Statistics #6
How many ways can you visualize data? An informative video showcases data representations, with specific attention to stem-and-leaf plots and box plots. Viewers also learn to identify and interpret outliers in data.
Corbett Maths
Reading Stem and Leaf Diagrams
What are you growing in your math classroom? Scholars use a video lesson to learn how to read a stem and leaf diagram. The video instructor explains how to interpret the key and then explores how to find the range, mode, and median from...
Crash Course
The Shape of Data: Distributions: Crash Course Statistics #7
Keep your knowledge of distributions in shape. An informative YouTube video describes how to analyze data using the shape of the data distribution. The seventh installment of the Crash Course Statistics series looks at normal...
Anywhere Math
Box-and-Whisker Plots
Whiskers are more than just a cat facial feature! Learn how the whiskers of a box-and-whisker help make conclusions about a data set. An instructor first explains how to create a box-and-whisker and then how to read it. Several examples...
Khan Academy
Box-and-Whisker Plots
Elucidating the concept of box-and-whisker plots, Sal explains not only how to generate the diagram but also how to read one. He uses several examples to help young mathematicians become familiar with the format and explains its...
Crash Course
Measures of Spread: Crash Course Statistics #4
Sometimes the measures of center don't give us enough information. The spread of the data can tell statisticians much more about the data set. A video lesson, part of a statistics video series, describes different measures of spread such...
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...
Crash Course
Z-Scores and Percentiles: Crash Course Statistics #18
Learn about statistics from A to z-score. Young statisticians watch an informative video that explains how to compare different normally distributed quantities using z-scores and percentiles. An example using ACT and SAT scores...
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
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
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
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
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
Correlation Doesn't Equal Causation: Crash Course Statistics #8
There's likely a strong correlation between watching the video and learning about causation. Scholars hear about different types of correlation and correlation coefficients through the informative YouTube video. They also see how...
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
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
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...