Section 2 7 notes

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					              Section 2.7 Notes – Curve Fitting with Linear Models

Akron, Ohio, and Wellington, New Zealand are about the same distance from
the equator. Make a scatter plot for the temperature data, identify the
correlation, and then find the equation for the line of best fit.

                     Average High Temperatures
           Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Akron      33 37 48 59 70         78 82 80 73   61 49 38
Wellington 67 67 65 61 56         53 51 52 55   57 60 64

Enter the data into the graphing calculator in L1 (Akron) and L2 (Wellington).
   CORRELATION Turn on the correlation r-value: 2nd, CATALOG, Scroll to DiagnosticOn,

      Clear the statistics lists: 2nd, MEM, 4:ClrAllLists, ENTER
      Enter the data into the calculator: STAT, 1:Edit… Type in independent (x) values in L1. Type
       in dependent (y) values in L2.

      Set up the scatterplot: 2nd, STAT PLOT, 1:Plot 1, Highlight On by pressing ENTER if
      Select first type (scatterplot), Xlist:L1, Ylist:L2, Select Mark
   Set up an appropriate window: WINDOW, Set domain and range values according to lists.


   Graph the scatterplot: GRAPH

       Calculate the regression: STAT, CALC, Select LinReg(ax + b), ENTER, ENTER


       To make the regression line so up on the grid:
        Go to y = then press the VARS key and select Statistics

   Press ENTER, Select EQ and 1:RegEQ

         This will return you to y = menu and it will put the entire regression equation in there.

Since r     -.971, this data has a strong negative correlation.

   1. Graph the scatter plot for this data and find the equation of the line of best fit.

   2. What is the correlation coefficient?

   3. Predict the weight of a $40 tire. How accurate do you think your prediction is?

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