SRS vs. Convenience Sample in the Gettysburg Address

Students have an interesting view of what a random sample looks like. They often feel that just closing their eyes and picking “haphazardly” will be enough to achieve randomness. This lesson should remove this misconception. Students will be allowed to pick words with their personal definition of random and then forced to pick a true simple random sample and compare the results.

Roll a Distribution

The purpose of this lesson is to allow the students to discover that data collected in seemingly similar settings will yield distributions that are shaped differently. Students will roll a single die 30 times counting the number of face up spots on the die and recording the result each time as a histogram or a histogram. Students will be asked to describe the shape of the distribution. Combining work with several students will yield more consistent results.

Who’s the Best Home Run Hitter of All time?

This lesson requires students to use side-by-side box plots to make a claim as to who is the "best home run hitter of all time" for major league baseball.

Why do we need MAD?

Students will wonder why we need to have a value that describes the spread of the data beyond the range. If we give them three sets of data that have the same mean, median, and range and yet are clearly differently shaped then perhaps they will see that the MAD has some use.

The Forest Problem

Students want to know why they would ever use a sampling method other than a simple random sample. This lesson visually illustrates the effect of using a simple random sample (SRS) vs. a stratified random sample. Students will create a SRS from a population of apple trees and use the mean of the SRS to estimate the mean yield of the trees. Students will then create a stratified random sample from the same population to again estimate the yield of the trees. The use of the stratified random sample is to control for a known source of variation in the yield of the crop, a nearby forest.

Sochi Olympics - Junior High Math Contest

This is the 2013 Chandler-Gilbert Community College Junior High Math Contest Team Project. You may use all or just parts of it as it contains lots of different math topics including: The idea of AVERAGE The idea of AVERAGE SPEED and GRAPHS of LINEAR FUNCTIONS The idea of CREATING and INTERPRETING BOX and WHISKER PLOTS  The idea of SLOPE The idea of ANGLE The idea of PERCENT Look at the project and decide what parts your students are ready to tackle...and HAVE FUN!

Sampling Techniques - Jelly Blubbers

This activity introduces the Simple Random Sample (SRS) to students, and shows why this process helps to get an unbiased sample statistic. Relying on our perceptions can often be deceiving. In this exercisestudents are asked to determine the average length of a jellyblubber (a hypothetically recently discovered marine species) using a variety of techniques. The student will learn that a Simple Random Sample (SRS) is the most accurate method of determining this parameter, and that intuition can be deceptive. 

Pennies From Heaven

The focus of this activity is to describe the shape of a distribution and to describe the center and spread. Students use data they collect (penny ages) to describe the distribution by its SOCS (Shape, Outlier, Center, Spread). 

Straighten up and Fly Right!

The purpose of this lesson is to allow the students gather data in a fun way and answer a statistical question through analysis of the data.  Students will fly paper airplanes and analyze the data to determine which style of plane flies longer.

M & M Variablility

Outlier Activity

Goal: The goal of this activity is for students to interpret measures of central tendency when an outlier is present. They will also be able to identify which value is an outlier and create a boxplot as well.

Creating a histogram using temperatures

Goal: The goal of the current activity is to have students read data from a map of the U.S., create a frequency table, answer questions and create a frequency histrogram.