lesson_10.1.2_version_1.6_student

12 central limit theorem for sample means 11 what

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 10 Sketch the simulated sampling distribution, when n = 2, in the box below. Run the simulation for sample sizes n = 10, and n = 30. Sketch your results in the boxes below. For each simulation, set N = 1000 so 1000 random samples are created. Skewed Right Population n=2 n = 10 n = 30 © 2011 THE CARNEGIE FOUNDATION FOR THE ADVANCEMENT OF TEACHING A PATHWAY THROUGH STATISTICS, VERSION 1.6, STATWAY™  ­ STUDENET HANDOUT STATWAY™ STUDENT HANDOUT | 4 Lesson 10.1.2 Central Limit Theorem for Sample Means 11 What happens to the center and variability of the sampling distribution when the sample size increases to n = 30? 12 Identify the mean and standard deviation (or error) of the sampling distribution when n = 30. How do they compare to the mean and standard deviation of the population? Sampling from Any Population We now sample from a population with an unusual distribution. Try to create a population distribution so weird, so wild, that even when we increase the sample size, the sampling distribution will not become bell shaped. We will again simulate 1000 random samples using three different sample sizes.  Set the Population type to Custom, and then click the Reset button. Click on the population graph to draw the wildest population you can imagine.  Set the sample size, n, to 2 and set the number of samples, N, to 1000.  Click Sample. 13 Sketch your population in the box below. 14 What is the range of the sample means in this simulated sampling distribution? © 2011 THE CARNEGIE FOUNDATION FOR THE ADVANCEMENT OF TEACHING A PATHWAY THROUGH STATISTICS, VERSION 1.6, STATWAY™  ­ STUDENET HANDOUT...
View Full Document

Ask a homework question - tutors are online