Common TI-83 or TI-84 Calculator Procedures
Univariate Data Analysis
1-Variable Statistics
Creating a Histogram
Creating a Box Plot
Linear Regression
Creating a Scatterplot
Why a scatterplot?
Calculating the Line of Regression
Interpreting the Calculator Output
Graphing the Line of Regression
UNIVARIATE DATA ANALYSIS
In order to show how to do all things relating to univariate data analysis, the following data set will be used:
The data in the table represents the number of soldiers in 45 Ohio Companies in the Union Army.
100 / 112 / 113 / 90 / 93 / 179 / 99 / 111 / 107156 / 152 / 72 / 134 / 180 / 143 / 110 / 157 / 101
115 / 103 / 90 / 105 / 104 / 102 / 112 / 87 / 92
108 / 86 / 82 / 76 / 79 / 85 / 85 / 85 / 87
85 / 83 / 101 / 99 / 10 / 98 / 10 / 78 / 89
1-Variable Statistics Back to Top
1. Press STAT and select 1:EDIT…(Figure 1)
2. Type the data into L1 (Figure 2)
3. Press STAT and use the LEFT ARROW to
access the CALC menu. Select 1:1-VAR STATS
(Figure 3)
4. If you have an older calculator, press ENTER. (Figure 4)
If you have a newer calculator, arrow
down to CALCULATE and press ENTER
5. On the screen will be displayed (in order): (Figure 5)
Average of the items in the list
Sum of the items in the list
Sum of the items squared in the list
Standard deviation of the items in the list
(assuming it is a sample)
Standard deviation of the items in the list
(assuming it is a population)
The number of items in the list
Arrow down to see the following: (Figure 6)
The minimum item in the list
The first quartile of the items in the list
The median of the items in the list
The third quartile of the items in the list
The maximum of the items in the list
Creating a Histogram Back to Top
1. Type the data into L1. If you don’t know how to access L1,
refer to steps 1 and 2 of 1-Variable Statistics
2. Press 2ND + Y= to access the STAT PLOT menu.
Select 1:Plot1… (Figure 7)
3. 5. Turn Plot 1 ON by pressing ENTER. (Figure 8)
(Off should not be highlighted)
4. Check TYPE: and make sure the third graph is highlighted
5. XLIST: should reference the list where you input the data.
06. Press ZOOM and choose 9:ZOOMSTAT (Figure 9)
7. The histogram will appear. (Figure 10)
8. To change your bin width or window, press WINDOW(Figure 11)
a) Xmin, Xmax, Ymin, Ymax will adjust the minimum
and maximum values on the axes
b) Xscl will adjust the bin width
Press GRAPH to see the new histogram (Figure 12)
Creating a Box Plot Back to Top
1. Type the data into L1. If you don’t know how to access L1,
refer to steps 1 and 2 of 1-Variable Statistics
2. Turn on PLOT 1. If you don’t know how to access PLOT 1,
refer to steps 2 and 3 of Creating a Histogram
4. Check TYPE: and make sure the fourth or fifth graph is highlighted (Figure 13)
(Graph four shows outliers; Graph five does not show outliers)
5. XLIST: should reference the list where you input the data.
06. Press ZOOM and choose 9:ZOOMSTAT (Figure 9)
7. The boxplot will appear. (Figure 14)
8. Press TRACE and use the ARROW KEYS to see the 5-number summary (Figure 15)
LINEAR REGRESSION Back toTop
In order to show how to do all things relating to linear regression, the following data set will be used:
The number of chirps per second of the striped ground cricket were counted and the temperature (in degrees Fahrenheit) was recorded. The study sought to determine if there was a relationship between the temperature (explanatory) and the chirps per second (response),
Temp (oF) / 88.6 / 71.6 / 93.3 / 84.3 / 80.6 / 75.2 / 69.7 / 82 / 69.4 / 83.3 / 79.6 / 82.6 / 80.6 / 83.5 / 76.3Chirps/Sec / 20 / 16 / 19.8 / 18.4 / 17.1 / 15.5 / 14.7 / 17.1 / 15.4 / 16.2 / 15 / 17.2 / 16 / 17 / 14.4
Creating a Scatterplot Back to Top
1. Press STAT and select 1:Edit…(Figure 16)
2. Enter the explanatoryvariable data into L1 and the
response variable data into L2. (Figure 17)
3. To view the scatterplot, press 2ND + Y=
4. Select 1:Plot1…
5. Turn Plot 1 ON by pressing ENTER.
(Off should not be highlighted) (Figure 18)
6. Check TYPE:and make sure the first graph is
highlighted
7. XLIST: should reference the list where you put the
explanatory variable. YLIST: should reference where
you put the response variable.
8. Select an appropriate WINDOW by
a) press ZOOM and select 9:ZoomStat
b) press WINDOWand change Xmin, Xmax,
Ymin, Ymax to appropriate sizes. The Xscl and
Yscl will change the scale on the axes. (Figure 19)
9. If you selected your window using 8a, the scatterplot
should appear when you select 9:ZoomStat (Figure 20). If you
selected your window using 8b, press GRAPH and the
scatterplot should appear.
Why create a scatterplot? Back to Top
All of the mathematics regarding linear regression can be calculated on any set of data, even if the data isn’t remotely linear! A scatterplot is needed to show people that the correlation coefficient (r), coefficient of determination (), and line of regression actually have meaning and are applicable.
Calculating the Line of Regression Back to Top
1. Enter the explanatory variable in L1 and the
response variable in L2 (if you do not know how to
get to the LISTS, refer to steps 1 and 2
of Creating a Scatterplot)
2. Press STAT and use the RIGHT ARROW
key to get to the CALC menu. (Figure 21)
3. Select 4:LINREG(ax+b) or 8:LINREG(a+bx)
4. If you have an older calculator, press ENTER. If you have
a newer calculator, arrow down to highlight CALCULATE
and press ENTER. (Figure 22)
5. The line of regression should show up on the screen. (Figure 23)
(Note: if and do not show up, refer to the FAQ)
Interpreting the Calculator Output Back toTop
In the output to the right, the slope of the line of regression is
and the y-intercept of the line is . Therefore the line of regression is
Interpreting the y-intercept: If the temperature was 0oF, crickets would chirp at a rate of about -.309 chirps per second. This makes no sense in context, as it is impossible for crickets to chirp at a negative rate.
Interpreting the slope: For every one-degree increase in the temperature, the rate of chirping of a striped ground cricket increases by about 0.212 chirps per second.
Note: the use of the word about is very important in the interpretation of the line of regression. The resulting y-values () are approximations or predictions of what we might observe.
Graphing the Line of Regression Back to Top
1. Press Y=(Figure 24)
2. You can insert the equation in two ways:
a) Round the slope and y-intercept. Type the
equation into the calculator.
b) 1. Press VARS and select 5:STATISTICS…(Figure 25)
b) 2. Arrow over to the EQ menu and select 1:REGEQ. (Figure 26)
The full equation will enter into Y=. (Figure 27)
3. Press GRAPH
(Figure 28)