MATH121
Linear Regression on TI-82

1. Enter lists
wpe7.jpg (1064 bytes) wpe9.jpg (809 bytes) wpeA.jpg (832 bytes) wpeB.jpg (892 bytes) Clear all lists
wpeD.jpg (1305 bytes) . .wpeE.jpg (1305 bytes) Press ENTER until all that is on
screen is DELETE:List .
   
wpe8.jpg (1064 bytes) wpeC.jpg (1300 bytes) Quit
wpeF.jpg (1230 bytes) wpe10.jpg (818 bytes) Get ready to edit lists; position
cursor at top of list L1
Enter x values, pressing wpeE.jpg (1305 bytes)
after each one
wpe11.jpg (858 bytes)
Position cursor at top of L2 list
Enter y values, pressing wpeE.jpg (1305 bytes)
after each one
wpe8.jpg (1064 bytes) wpeC.jpg (1300 bytes)
Quit
          
2. Graph the data
wpe8.jpg (1064 bytes) wpe12.jpg (949 bytes) wpe10.jpg (818 bytes) wpeE.jpg (1305 bytes) Turn Plot 1 On
wpe13.jpg (857 bytes) wpeE.jpg (1305 bytes) Highlight first type of graph
wpe14.jpg (857 bytes) wpeE.jpg (1305 bytes) Xlist is L1
wpe15.jpg (857 bytes) wpe11.jpg (858 bytes) wpeE.jpg (1305 bytes) Ylist is L2
wpe16.jpg (857 bytes) wpeE.jpg (1305 bytes) Mark is ú
wpe19.jpg (1365 bytes) wpe1A.jpg (888 bytes) Window is set to fit data and data is
graphed
wpe8.jpg (1064 bytes) wpeC.jpg (1300 bytes) Quit
     
3. Do the linear regression; the equation will be of the form y(x) = ax + b
wpe26.jpg (1230 bytes) wpe11.jpg (858 bytes) wpe24.jpg (890 bytes) Go to STAT CALC and do
LinReg(ax+b)
wpeE.jpg (1305 bytes) Values of a, b, and r appear on screen
a = slope; b = y intercept
        
4. Paste the linear regression equation into Y1 and graph it
wpe12.jpg (949 bytes) wpe22.jpg (1409 bytes) wpe23.jpg (1279 bytes) wpe24.jpg (890 bytes) wpe11.jpg (858 bytes) wpe11.jpg (858 bytes) wpe25.jpg (874 bytes) Regression equation is pasted into Y1
wpe1D.jpg (1428 bytes) Regression line is graphed with data points
         
5. Use the regression line to make predictions
        
Method 1:
If the x value where the prediction is to be made is in the current graphing window,
wpe8.jpg (1064 bytes) wpe28.jpg (1392 bytes) wpe10.jpg (818 bytes) And then enter the x value where the
prediction is to be made
wpeE.jpg (1305 bytes) Y value is the predicted value
        
If the x value is not in the current graphing window, the window can be reset to include that x value. It is not necessary to have the y value in the window. Then use the process above.
       
Method 2:
wpe8.jpg (1064 bytes) wpe20.jpg (1570 bytes) Use TblSet
wpe15.jpg (857 bytes) wpe15.jpg (857 bytes) wpe11.jpg (858 bytes) wpeE.jpg (1305 bytes) Set Indpnt: to Ask and Depend: to
Auto
Quit
And then enter the x value in the X
column; the corresponding value in
the Y1 column is the predicted value
wpe8.jpg (1064 bytes) wpeC.jpg (1300 bytes)
wpe8.jpg (1064 bytes) wpe1D.jpg (1428 bytes)
wpeE.jpg (1305 bytes)
       
6. When regression is completed, turn scatter plots off
wpe8.jpg (1064 bytes) wpe12.jpg (949 bytes) wpe21.jpg (882 bytes) wpeE.jpg (1305 bytes)