Linear Regression
The following example
illustrates step-wise the use of the TI-83 to do a scatter-plot and a linear
regression.
Part 1: (Scatter- plot) Scatter plot the following data:
|
x |
6.5 |
11 |
13.2 |
15 |
18 |
23.1 |
24.4 |
26.6 |
30.5 |
34.3 |
37.6 |
41.5 |
|
y |
0.51 |
0.68 |
0.73 |
0.79 |
0.88 |
0.99 |
1.01 |
1.08 |
1.13 |
1.26 |
1.28 |
1.32 |
1. Press:
MODE u
u u ENTER (sets FUNC graphing mode)
2. Press:
STAT 5
(selects 5:SetUpEditor)
3. Press:
ENTER (stores
lists
in columns)
4. Press:
STAT 1
(selects 1:Edit)
If elements are stored in
press:
t CLEAR ENTER 4 t CLEAR ENTER
(clears both lists)
then press: 3
(moves cursor back to first row in
)
5. Press:
6 · 5 ENTER (stores 6.5 in
)
Repeat to enter each of the
twelve x-coordinates in the data-table.
6 Press: 4
(moves cursor to the first row
in
)
7. Press: · 5
1 ENTER (stores .51
in
)
Repeat to enter each of the
twelve y-coordinates in the data-table.
8. Press: y = (if necessary, clear any previous function by pressing CLEAR )
9. Press: t ENTER 4 (turns
off Plot 1, Plot 2, and Plot 3)
10. Press: u 3 ENTER ( to deselect function if necessary)
11. Press: 2nd STAT PLOT 1 ENTER (turns on Plot 1)
12. Press: u ENTER
(to select scatter plot)
13. Press: u 2nd
( to specify xlist:
for Plot 1)
14. Press: u 2nd
( to specify ylist:
for Plot 1)
15. Press: u 4 ENTER (to select + as mark)
16. Press: ZOOM 9 (to select 9:ZoomStat)
(Scatter) Plot 1 is
displayed.
Part 2 (Linear regression)
To obtain a linear
regression to the data:
1. Press: STAT 4 4 (
to select 4:LinReg(ax + b) from STAT CALC)
2. Press: 2nd
,
2nd
,
3. Press: VARS 4 1 (displays VARS Y-VARS FUNCTION)
4. Press: 1 (
selects 1:
)
Observe that
,
, and
are pasted to the home screen as arguments of
LinReg(ax + b).
5. Press: ENTER (executes
LinReg(ax + b) )
Values for ‘a’
and ‘b’ are displayed on the home screen and the linear regression equation is stored
in
. To observe the scatter plot and the
regression line Press:
GRAPH
Exercise: The following table lists data that show the life
expectancy of women for various years.
|
Year (t) |
1950 (t=0) |
1960 (t=10) |
1970 (t = 20) |
1980 (t = 30) |
1990 (t = 40) |
|
Life Expectancy in Years |
70.9 |
73.2 |
74.8 |
77.5 |
78.6 |
(a) Find a linear function that fits the data.
(b) Use the model to predict
the life expectancy in the year 2000.