Title: Creating a Sampling Distribution

Authors: Abdulaziz Elfessi, Heather Hulett - UW -La Crosse, Dan Nordman - University of Iowa

Contact: [email protected]

Discipline or Field: Statistics

Course Name: Elementary Statistics

Date: Last updated: August 14, 2006


Course Description

Elementary Statistics is a general education course aimed at promoting the use of statistics in many disciplines. A central learning outcome is for students to think critically about consuming information in terms of data collection, graphical summaries and other statistical tools. In particular, each student should be able to apply basic statistical techniques to draw inferences and evaluate claims by the end of the course. The calculations, as well are their interpretations, are stressed throughout the course.

The students enrolled in the course are varied in both their interest and mathematical backgrounds. Many take the course only to fulfill a general education requirement in mathematics. Other students rely on this course to provide a statistical background needed in future work across various programs of study.

The only prerequisite is college algebra and the range of ability varies dramatically from student to student. The class size is 38 and the class is 55 minutes long. Most of the course is taught as a lecture with occasional worksheets or projects for students.


Executive Summary

In this activity, we hope to help students differentiate and explain three statistical terms at the heart of statistical inference: the mean of a population, the mean of a sample of observations, and the mean of the sample means.

Past experience indicates that term ``mean" can be very confusing for students in an Elementary Statistics class, especially when the same word choice may be applied in all three situations above, with different meanings in each case. Understanding the differences, as well as the connection, between the three types of means above is important for the most basic hypothesis tests in statistics: testing if the population mean equals a certain value by looking at just one random sample. The idea that data from a small sample can be used to estimate the mean of an entire population, which cannot be obtained directly, is critical to statistical applications in many, many fields.

The specific learning goals of the lesson are as follows:

Students will practice applying statistical techniques to data collected from samples.

Students will see and explain sample variability and how sample size decreases the variability of sample means.

Students will see graphically that the ``typical/central/mean/expected" value of a sample mean is the same as the population mean.

In this lesson students will take random samples of different sizes and calculate their averages. They will then put their averages on Post-It notes and place them in the correct spot on the chalkboard to make histograms that will represent the sampling distributions. By comparing their sample means, the mean of the histogram (the mean of all the samples), and the population mean (which will be revealed at the right moment), they will hopefully get a fuller appreciation of the three different uses of the word ``mean''.

The activity was successful in several ways. Students enjoyed the short exercise in drawing random samples and were surprised by some of the sample means obtained. As the histograms were formed, they saw clearly how the variability decreased as sample size increased. Finally, they got to see how most sample means gave close approximations to the true population mean.


Complete Report

Final Report Statistics
Final Report for LSP on Sampling distributions.

The Lesson

Lesson
Description of the lesson activity.

Data Table
Data Table for the heights of students

Student Worksheet
Student Worksheet

The Study

The Study
What worked and what didn't in the activity.

Observation Guidelines
The observation guidelines that instructors used as guides during the lesson study activity.






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