Measuring 'intellect' is a difficult task. Check out one way scientists are attempting to make this endeavor more testable. Hosted by: Hank Green

When you're getting medical treatment, or taking part in medical testing, privacy is important; strict laws limit what researchers can see and know about you. But what if your medical data could be used -- anonymously -- by anyone...

When you have a study with a small sample size, how do you know that the results represent the broader population? Well, thanks to a brewer who needed to assess beer quality in the early 1900s, we now have a simple statistical test that...

Paul Andersen introduces science for the science classroom. He starts with a brief description of Big Data and why it is important that we prepare future scientists to deal intelligently with large amounts of data. He explains the...

Today we're going to talk about degrees of freedom - which are the number of independent pieces of information that make up our models. More degrees of freedom typically mean more concrete results. But something that is statistically...

In this video Paul Andersen explains the importance of standard deviation. He starts with a discussion of normal distribution and how the standard deviation measures the average distance from the mean, or the "spread" of data. He then...

Today we’re going to talk about confidence intervals. Confidence intervals allow us to quantify our uncertainty, by allowing us to define a range of values for our predictions and assigning a likelihood that something falls within that...

Paul Andersen shows you how to calculate the standard error of a data set. He starts by explaining the purpose of standard error in representing the precision of the data. The standard error is based on the standard deviation and the...

Today is the day we finally talk about the normal distribution! The normal distribution is incredibly important in statistics because distributions of means are normally distributed even if populations aren't. We'll get into why this is...

Paul Andersen explains how scientists analyze and interpret data. Data can be organized in a table and displayed using a graph. Students should learn how to present and evaluate data.

Elon Musk thinks that we can make Mars habitable by nuking it. But would that really work?

This video provides an elaborate solution to the practice exercise of the central limit theorem concept.

In this lesson, we will work through all the steps of hypothesis testing with an example of proportion testing.

In this video, you will learn more about the student's t-test and t-distribution in detail.

This video provides the solution and explanation to the hypothesis testing practice exercise we worked on above.

This video elaborates on performing actual hypothesis testing through a demonstration.

After exploring confidence intervals and margin of error, we will now understand how to determine a sample size to reduce the error size caused by the sample size.

This lesson will explore a confidence interval while estimating the significance level and determining an acceptable margin of error.

This video will look at the errors we make while addressing the significance level or determining the probability value, which we classify as type I and II errors.

This is a hands-on challenge to understand better the central limit theorem concept with a practical example.

In this video, we will understand the central limit theorem intuitively. We will explore this concept online using the onlinestatbook.com webpage.

In this video, you will learn about a fundamental concept of probability, the central limit theorem. The author explains this comprehensively as the base for the following lectures.

After learning about the measures of spread, the range, and IQR, we will now learn more about the two most common measures of spread, the variance, and standard deviation.

This lecture will explain the fundamental difference between a sample and a population in statistical data.