Sophia: Sampling Error and Sample Size: Lesson 4

The 19th installment in a 25-part series builds upon the sampling from the previous unit and takes a larger sample. Pupils compare the dot plots of sample means using two different sample sizes to find which one has the better variability.

Based on your current level of human capital, how long would it take you to earn $1,000,000? What about your potential human capital? Learners explore the importance of education and experience when entering the workforce, and compare...

What is the appropriate model? Sample problems show the extent of the Smarter Balanced assessments Claim 4, Modeling and Data Analysis. Items provide pupils the opportunity to use mathematical modeling to arrive at a reasonable answer....

Experimental design can be both incredibly intuitive and very high-concept when first introduced to learners. This video does a great job of discussing sampling methods and bias simply, without over-reducing...

How many of you found the video to be useful? Young statisticians learn about surveys in the 10th installment of the Crash Course Statistics playlist. An informative video describes different sampling methods and possible sources of bias.

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.

This lesson will explain sampling error and sample size. It is 2 of 4 in the series titled "Sampling Error and Sample Size."

This lesson will explain sampling error and sample size. It is 3 of 4 in the series titled "Sampling Error and Sample Size."

In this lesson, students are shown the relationship between roots and fractional exponents (one can be rewritten as the other). It is 4 of 10 in the series titled "Roots and Fractional Exponents."

Using a 2002 California Gray David recall vote as an example, young statisticians  identify sources of bias in samples and find ways of reducing and eliminating sampling bias. They consider ways to select random samples from a...