MATH121
Linear Regression on TI-83

1. Enter lists
wpe8.jpg (1064 bytes) wpe9.jpg (809 bytes) wpeA.jpg (825 bytes) wpeB.jpg (1308 bytes) Clear all lists
wpeC.jpg (1230 bytes) wpeE.jpg (832 bytes) wpeB.jpg (1308 bytes) Set up editor
wpeC.jpg (1230 bytes) wpe11.jpg (818 bytes) Get ready to edit lists; position
cursor at top of list L1
Enter x values, pressing wpeB.jpg (1308 bytes)
after each one
wpe12.jpg (858 bytes) Position cursor at top of L2 list
Enter y values, pressing wpeB.jpg (1308 bytes)
after each one
wpe8.jpg (1064 bytes) wpe15.jpg (1300 bytes) Quit
     
2. Graph the data
wpe8.jpg (1064 bytes)  wpe16.jpg (948 bytes) wpe11.jpg (818 bytes) wpeB.jpg (1308 bytes) Turn Plot 1 On
wpe17.jpg (857 bytes) wpeB.jpg (1308 bytes)
wpe17.jpg (857 bytes) wpe8.jpg (1064 bytes) wpe11.jpg (818 bytes) wpeB.jpg (1308 bytes)
wpe8.jpg (1064 bytes)  wpe18.jpg (878 bytes) wpeB.jpg (1308 bytes)
wpeB.jpg (1308 bytes)
zoom.jpg (1365 bytes)  9.jpg (888 bytes)
Highlight first type of graph

Xlist is L1
Ylist is L2
Mark is ú
Window is set to fit data and data is
graphed

wpe8.jpg (1064 bytes) wpe15.jpg (1300 bytes) Quit
     
3. Do the linear regression; the equation will be of the form y(x) = ax + b
wpeC.jpg (1230 bytes) wpe12.jpg (858 bytes) wpeA.jpg (825 bytes) Go to STAT CALC and do
LinReg(ax+b)
wpeB.jpg (1308 bytes) Values of a, b, r, and r2 appear on
screen; a = slope; b = y intercept
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Note: If r and its value do not appear on screen, it must be turned on:
wpe8.jpg (1064 bytes) wpe1A.jpg (878 bytes) Use the CATALOG
Press wpe17.jpg (857 bytes) as many times as needed to position the pointer at DiagnosticOn
wpeB.jpg (1308 bytes) wpeB.jpg (1308 bytes) From now on, until it is turned off,
the values of r and r2 will appear on
screen for all linear regressions
Start at the top of Step 3 again.
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4. Paste the linear regression equation into Y1 and graph it
wpe16.jpg (948 bytes) clear.jpg (1409 bytes) vars.jpg (1279 bytes) 5.jpg (890 bytes). Regression equation is pasted into Y1
zoom.jpg (1365 bytes) 9.jpg (888 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,
2nd.jpg (1055 bytes) trace.jpg (1392 bytes) 1.jpg (813 bytes) And then enter the x value where the
prediction is to be made
wpeB.jpg (1308 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:
2nd.jpg (1055 bytes) window.jpg (1570 bytes) Use TblSet
dnarrow.jpg (850 bytes) dnarrow.jpg (850 bytes) rtarrow.jpg (858 bytes) wpeB.jpg (1308 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
2nd.jpg (1055 bytes) mode.jpg (1300 bytes)
2nd.jpg (1055 bytes) graph.jpg (1428 bytes)
wpeB.jpg (1308 bytes)
   
6. When regression is completed, turn scatter plots off
2nd.jpg (1055 bytes) wpe16.jpg (948 bytes) 4.jpg (882 bytes) wpeB.jpg (1308 bytes)