MATH121
Linear Regression on TI-85

1. Enter lists
    
stat.jpg (1230 bytes) wpe12.jpg (1139 bytes) enter.jpg (1308 bytes) enter.jpg (1308 bytes) wpe14.jpg (1307 bytes) Cursor is now on x1 and y1
value is 1; xStat list is empty
Enter pairs of x and y values, pressing enter.jpg (1308 bytes) after each value
 
2. Graph the data
    
graph.jpg (1428 bytes) wpe15.jpg (1142 bytes) Then put cursor on any equation present
clear.jpg (1409 bytes), more if needed Clear all equations
wpe17.jpg (1164 bytes) range.jpg (1409 bytes), then set the window so that all x and y values will be included in the viewing rectangle.
    
stat.jpg (1230 bytes)  wpe18.jpg (1340 bytes) wpe19.jpg (1253 bytes) The data points are shown on a scatter graph
       
3. Do the linear regression; the equation will be of the form y(x) = a + bx
   
exit.jpg (1164 bytes) wpe1A.jpg (1252 bytes) enter.jpg (1308 bytes) enter.jpg (1308 bytes) wpe1B.jpg (1159 bytes) Values of a, b, corr (which is r), and n on screen;
a = y intercept, b = slope
       
4. Graph the linear regression line
    
graph.jpg (1428 bytes) y(x)equals.jpg (1142 bytes) stat.jpg (1230 bytes) vars.jpg (1279 bytes)
wpe1C.jpg (1329 bytes) wpe1D.jpg (1329 bytes) wpe1E.jpg (1276 bytes) The regression equation is pasted into y1
The regression line is graphed
stat.jpg (1230 bytes) wpe18.jpg (1340 bytes)
wpe19.jpg (1253 bytes) The data points are added to the graph
      
5. Use the regression line to make predictions
exit.jpg (1164 bytes) wpe20.jpg (1237 bytes) Then enter x value where prediction is to be made
dnarrow.jpg (857 bytes)
wpe21.jpg (1401 bytes) Put cursor on line where ‘y=' is
Predicted y value is given