The position of the graphically represented keys can be found by moving your mouse on top of the graphic.
When counting rows, I will not count the 4 bullet shaped keys on top: ON, MODE, 2ND, CONST. Row 1, therefore, starts with DATA.
To work the arrow keys, press the big black oval shaped key (between the ON and MODE keys) in the proper place. is on the left, is on top, etc.
Turn your calculator on | |||||||||
Press . | |||||||||
Clearing the memory | |||||||||
Press . You should see the word CLRDATA underlined on the screen. |
Entering data | |||
one variable | |||
Press to enter the statistics menu. The cursor should be on 1-VAR. If it isn't, arrow to it. Press . Enter the first value and press . (Not sure on this point, the second number is the frequency of the data. So if the number 15 showed up twelve times in your list, you would enter 12 here. I think 1 is a default value, so you can just press the down arrow twice if the value only shows up once.) Enter the rest of the values, pressing after each one. | |||
two variables | |||
Press to enter the statistics menu. The cursor should be on 1-VAR. Press to move the cursor to 2-VAR. Press . Enter the first x-value and press . Enter the corresponding y-value and press . Enter the rest of the ordered pairs in the same way. |
Calculating one-variable statistics | ||||
mean (x) | ||||
Press . The letter n should be underlined. Press to move the cursor (the underline) to the mean (designated x). It's value will now be on the screen. | ||||
standard deviation for populations (s or sn) | ||||
Press . The letter n should be underlined. Press to move the cursor (the underline) to the population standard deviation (designated sx). It's value will now be on the screen. | ||||
standard deviation for samples (s or sn-1) | ||||
Press . The letter n should be underlined. Press to move the cursor (the underline) to the sample standard deviation (designated sx). It's value will now be on the screen. |
Calculating two-variable statistics |
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r (correlation) | |||||
Press . The letter n should be underlined. Press nine times to move the cursor (the underline) to the correlation (designated r). It's value will now be on the screen. | |||||
regression coefficients | |||||
slope | |||||
Press . The letter n should be underlined. Press eight times to move the cursor (the underline) to the slope (designated b). It's value will now be on the screen. (Alternatively, you can press four times.) | |||||
y-intercept | |||||
Press . The letter n should be underlined. Press seven times to move the cursor (the underline) to the y-intercept (designated a). It's value will now be on the screen. (Alternatively, you can press five times.) |
Calculating combinations and permutations | ||||
combinations (nCr) | ||||
Enter the n value. Press (the word nCr should be underlined). Press . Enter the r value and press . | ||||
permutations (nPr) | ||||
Enter the n value. Press (the word nPr should be underlined). Press . Enter the r value and press . |
Turning the calculator off | ||
Press . |
Worked Out Examples
In the following examples, we list the exact key sequence used to find the answer. We will list the keys by the main symbol on the key. In parentheses, we will list a helpful mnemonic, e.g. we will list ex as (ex).
A: What is the mean and standard deviation of the following list of numbers?
15 16 20 21
1: Clear Memory | |
2: Enter Data | (1-VAR) |
3: Compute the mean | (x) |
4: Compute the population standard deviation | (sx) |
5: Compute the sample standard deviation | (sx) |
You should get a mean of 18, population standard deviation of
2.549509757 and a sample standard deviation
of 2.943920289.
B: Find the linear regression line for the following table of numbers. Also find the correlation.
x | 1 | 2 | 3 | 4 |
y | 2 | 4 | 5 | 7 |
1: Clear Memory | |
2: Enter Data | (2-VAR) |
3: Compute the slope of the regression line | (b) |
4: Compute the y-intercept of the regression line | (a) |
5: Compute the correlation | (r) |
You should get a slope of 1.6, a y-intercept of 0.5, and a
correlation of 0.992277876.
The regression line would be: y = 1.6x + 0.5.
1:Compute 10C6 |
(nCr) |
2: Compute 9P5 | (nPr) |
You should get 10C6 = 210 and 9P5=
15120.
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