Redefinition

Redefinition toc



Introduction to Redefinition:
There are multiple opportunities to redefine and create vast new opportunities using Fathom. The fact that there are many survey, data generator, and other such sites out on the web make it very easy to create and fabricate new ideas and bring them to life using Fathom.

Files you need:
Fathom File: Also remember that there are 7 females and 3 males who have taken this survey (since one question asks about gender).

Activity:
Since everyone has completed the survey on surveymonkey that was distributed, the data collected for that will be found above along with a random data file that has been compiled into Fathom already.

Bring up a summary table and put the "favorite color" on the vertical (down arrow) area and the "favorite pizza" on the horizontal (right arrow) area. Notice the new table that has come up.

Use this table to find the probability that someone likes Cheese given that they like Purple. Now, do the reverse. Do the probability that someone likes that color given that they like that pizza topping.

Do the same kind of analysis with color and birth month. If someone was born in February, what is the chance that they like Pepperoni? Then reverse it

This is an activity that we aren't asking you to do due to time, but something that your students can do in your class when using Fathom. You could have your students consider questions like these in your classroom.

Try some quantitative data. Do these following aspects correlate? Why or why not? Number of TVs in house vs. Family Size First Name Number vs. Last Name Number Hours at work vs. Hours on Computer <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Number of texts vs. Amount of time on phone calls <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Computer hours vs. Facebook hours <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Height vs. Shoe Size <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Wake up time vs. Bed time

<span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Try some mix and match data. Put the quantitative on the horizontal axis and the qualitative on the vertical axis: <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Gender vs. Height <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Birth month vs. Family Size <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Color vs. Shoe Size <span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Pizza Topping vs. First name number.

<span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">Now, you might think that this was easily done by hand because there was a small data set. But, what if there was a huge data set? What would you do then? Think about the same concepts but use the randomly generated data. Answer some of these questions for the "rand1" collection in the file. What trends, patterns, similarities, differences do you see between the small class data set and the large random data set? Note that some of the information was abbreviated due to randomness limitations.

<span style="font-family: Georgia,serif; font-size: 140%;">Modeling:
<span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">This can be used to model class trends in schools. Think about some of the other college seniors you know. How would they fit in some of the quantitative and qualitative categories? Students can survey and poll in the community and bring it all together to consider the community.

<span style="font-family: Georgia,serif; font-size: 140%;">Why is this redefinition?
<span style="font-family: 'Palatino Linotype','Book Antiqua',Palatino,serif; font-size: 110%;">This is redefinition because it allows the use of live student data. A teacher could have a similar password protected survey for his/her class to fill out and bring those live data sets into the mix. It utilized the meshing of many different programs: Fathom, a survey creator, a random data generator, and spreadsheet, something that is impossible to do alone. The movement from the small level to the large data level in one activity is something that is not easily done with a graphing calculator or other grapher. It's hard to see those different representations without doing them by hand. Additionally, an activity like this can be discussed and commented upon by others using a wiki or blog site, thus allowing greater mobility between programs.