Chapter 10 Guiding Questions

Here are a few questions you need to address:

1) What is the Ladder of Powers? (make a chart and explain what each part of the ladder means)

2) What are the four goals of re-expressing data?

3) What are exponential, logarithmic, and power models and what are their roles in re-espressing data?


To help answer these questions use the Ladder of Powers_Aligators.ftm to explore the ladder of powers.


Wildlife biologists can fairly accurately determine the length of an alligator from aerial photographs or from a boat. Determining the weight of an alligator from a distance is much more difficult. Wildlife biologists in Florida captured 25 alligators in order to collect data and to develop a model from which weight can be predicted from length. The data set (in case fathom isn't working on your computer) alligator.txt contains the resulting 25 measurements, the first variable is the alligator's weight (in pounds?) and the second is its length (in inches?). 

 

1. Create a scatterplot of the raw data.
2. Play around with the scatterplot, swapping out the values for your x and or y variables with the the calculated re-expressed values, such as y-squared, sqrt_y, sqrt_x..., in order to get a scatter plot that is approximately linear. 
3. When you have a scatter plot that is approximately linear, create a least squares regression line (LSRL)  by right clicking on the scatter plot and selecting "Least Squares Line
4. Using Google docs, explain how you can uses this model to predict the weight of an aligator with length 140 inches. 
1. Log into google apps.  One team member should create a file "Group # Alligator Problem"
2. Then in the upper right hand corner of the document, click "share"  Add your group members email addresses and your teacher's email address.
3. Be sure to include images from fathom, that show the original data, re-expressed data, LSRL, residual plots, and an explanation of how you find the predicted weight of a 140 inch alligator.