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?