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Power Regression Model Example

Side note:  Power regressions will not allow an independent variable value of zero.
This example does not utilize an independent variable value of zero.


The true antelopes are found only in Africa and Asia.  They range in size from the pygmy antelopes, which are 12 inches (30 cm) high at the shoulder, to the giant elands, which are over 6 feet (180 cm) high at the shoulder.  Most antelopes stand between 3 to 4 feet (90-120 cm) high at the shoulder. The horns of antelopes, unlike the antlers of deer, are unbranched, are made of a chitinous shell with a bony core, and are not shed.  The majority of antelopes reside in Africa..

Data:  The data below represents the length and mid-shaft diameters of the humerus bones of African Antelopes.

Diameter (mm) Length (mm)
17.6 159.9
26.0 206.9
31.9 236.8
38.9 269.9
45.8 300.6
51.2 323.6
58.1 351.7
64.7 377.6
66.7 384.1
80.8 437.2
82.9 444.7

 

Task: a.) Determine a power regression model equation to represent this data.
  b.) Graph the new equation.
  c.) Decide whether the new equation is a "good fit" to represent this data.
  d.) Extrapolate data:  What length will correspond to a diameter of 84 mm?
  e.) Interpolate data:  What length will correspond to a diameter of 47 mm?
  Express answers to the nearest thousandth, if necessary.
    
             
Step 1.  Enter the data into the lists. 
For basic entry of data, see Basic Commands.


 

Step 2.  Create a scatter plot of the data. 
     Go to STATPLOT (2nd Y=) and choose the first plot.  Turn the plot ON, set the icon to Scatter Plot (the first one), set Xlist to L1 and Ylist to L2 (assuming that is where you stored the data), and select a Mark of your choice.
           

Step 3.  Choose the Power Regression Model.
     Press STAT, arrow right to CALC, and arrow down to A: PwrReg.  Hit ENTER.  When PwrReg appears on the home screen, type the parameters L1, L2, Y1.  The Y1 will put the equation into Y= for you. 
 (Y1 comes from VARS → YVARS, #Function, Y1)

          
 


The power regression equation is

(answer to part a)

Step 4.  Graph the Power Regression Equation from Y1.
     ZOOM #9 ZoomStat to see the graph.


(answer to part b)

Step 5.  Is this model a "good fit"?
     The correlation coefficient, r, is .9999937121 which indicates a very strong correlation since it is close to 1.
     The coefficient of determination, r
2, is .99999250766 which means that 99% of the total variation in y can be explained by the relationship between x and y.
     Yes, it is a very "good fit".
   
 (answer to part c)

Step 6.  Extrapolate:  (beyond the data set)
    
 Go to TBLSET (above WINDOW) and set the Table to ASK mode for the Indpnt variable.  Go to TABLE (above GRAPH) and type in the value you wish to find, 84.  The answer will appear in the Y1 column.

     
           (answer to part d -- the length will be 448.35 mm)

Step 7.  Interpolate: 
                         (within the data set)

     From the graph screen, hit TRACE, arrow up to obtain the power equation, type 47, hit ENTER, and the answer will appear at the bottom of the screen.

  
             (answer to part e --
        the length will be 305.703 mm)

 


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