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Group Projects

1. Give the students a survey; collect this data and put it into a spreadsheet. Have groups of students download the data. Each group is responsible for preparing this data for analysis. They should assign a unique identifying number to each row of data, reviewing the survey forms to identify common mistakes (that are hopefully present), coding open-ended questions, and creating a codebook.
    
2. Understanding quantitative measures can feel very complicated. This group project is supposed to fulfill the prophecy “when you know how to teach it, you will finally know it in its entirety.” In groups of three or four, craft a mock up of a children’s book that details how someone with a basic understanding of mean, median, and mode could understand how data analysis works. This children’s book should be at least ten pages long, and include drawings that help children better understand the concepts.
    
3. Select a data set (such as the Census or the GSS) that is easily accessible on the Internet or in a computer lab.  Divide the class into two groups; each group should be tasked with making graphs that convince the whole class that their position is correct. In other words, this group project involves demonstrating how substantially data can be manipulated to prove a point. Conclude the activity with a discussion of the safeties to put in place to avoid such extreme misrepresentation of data.
    
4. How good, or bad, can it get?  Each group member should review newspapers and magazines for one or two weeks, looking for graphs that purport to convey information about social issues.  The group should then review all the graphs and pick the best and the worst.  One group representative can then make a nominating speech for these selections to the entire class.  After all nominates are made, the class can review the criteria for good (and bad) graphs and vote for the winner and the loser.
    
5. Separate students into groups and have each group figure out the following and design rough graphs appropriate for each:  the modal favorite color, the median estimated distance that students in the group live from campus (distance is zero if they live on campus), and the mean number of credit hours that they are taking this term.  When they have completed this information, construct measures of central tendency for the class based on the measures of central tendency for each group.  What is the modal favorite color, the median distance from campus, and the mean number of credit hours for the class?  You can then poll individuals from the class as a whole to determine if the measures of central tendency based on a series of samples is similar to the measures of central tendency for the class as a whole (This is a also good way to demonstrate the advantages of using multiple samples from the same population, and/or to demonstrate the concept of a grand mean.) 

Mini-Projects

1.  Creating Cross Tabulations without knowing a statistical package 
The GSS website allows you to create cross tabs without any advanced knowledge of statistical software. 

1. Go to http://www3.norc.org/GSS+Website/Data+Analysis/
2. Browse the codebook for two variables that you think might be related to one another and a third that might be an extraneous variable to the bivariate relationship between the first two.  Make sure to write down the variable labels and what each variable measures.
3. Click on the “Analyze” button at the top of the screen.
4. Select “Frequencies or cross-tabulation.” 
5. Enter the proposed dependent variable name in the space provided for Row.
6. Enter the proposed independent variable name in the space provided for Column.  Make sure that after Percentaging, the box next to “Column” is checked.  It is also helpful to check “Color coding” among other options.
7. Select “Run the table.”  Print your results.
8. Click on the “Analyze” button at the top of the screen.
9. Select “Frequencies or cross tabulation.”
10. Re-enter the row and column variables, but add the proposed extraneous variable in the space provided for control.  Make sure that after Percentaging, the box next to “Column” is checked.  It is also helpful to check “Color coding” among other options.
11. Select “Run the table.”  Print your results.
12. Write a brief report, including a table constructed from the GSS output, that analyzes the relationship between the variables.  Does the data support your hypothesis?  Did an extraneous variable alter the relationship?

2.  Displaying Census Data 
This exercise will introduce you to the data available on-line from the US Census. 

1. Go to www.census.gov.  Click on “State and Country Quick Facts.” 
2. Pick any state from the drop down list to get an idea of what variables are available.
3. Select a variable that you think will vary by region within the United States.
4. Group states into regions that make sense given this variable (for example, Northeast, Southeast, Midwest, Southwest, Mountain States, and Pacific States).  Make sure to specify which states are in each region.  Select two regions that you will analyze (This assignment will be more difficult if you have only grouped states into two groups!)
5. For each region, compute the mode, median, and mean for the variable you have selected.  A calculator will do you a world of good here!  Also, note the range on the variable for each region.
6. Decide which measure of central tendency is most appropriate for the variable you selected. 
7. Construct a table or a graph that displays the comparison of the measure of central tendency between the two regions, as well as the national parameters (which can be found under “USA Quickfacts.”
8. Write a brief report in which you describe this entire procedure and present evidence of a regional difference or a lack of regional difference.

3.  Skittles vs. M&M’s: Mean, Median, and Mode

1. Give each student a pack of Skittles and a pack of M&M’s.
2. Instruct each student to record the number of each color of each type of candy present in their package.
3. Instruct each student to calculate the mode, mean, and median of the colors.
4. Have each student construct two bar graphs to display their data.
5. Gather students back together; collate data each student collected to garner a larger sample.
6. Given the larger, generalizable data set, have students craft recommendations for possible candy consumers anticipating different potential preferences (ex: if a consumer prefers red candies to blue candies then pick the type of candy with, on average, more red candy.