The position of the graphically represented keys can be found by moving your mouse on top of the graphic.
Turn your calculator on | |||||||||
Press ![]() |
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Clearing the memory | |||||||||
Press ![]() ![]() |
Entering data | |||
one variable | |||
Press ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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two variables | |||
Press ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Calculating one-variable statistics | ||||
mean (x) | ||||
Press ![]() ![]() ![]() ![]() |
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standard deviation for populations (s or sn) | ||||
Press ![]() ![]() ![]() ![]() |
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standard deviation for samples (s or sn-1) | ||||
Press ![]() ![]() ![]() |
Calculating two-variable statistics |
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r (correlation) | |||||
Press ![]() ![]() ![]() ![]() |
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regression coefficients | |||||
slope | |||||
Press ![]() ![]() ![]() |
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y-intercept | |||||
Press ![]() ![]() ![]() |
Calculating combinations and permutations | ||||
combinations (nCr) | ||||
Enter n, press ![]() ![]() ![]() |
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permutations (nPr) | ||||
Enter n, 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 | ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
3: Compute the mean | ![]() ![]() ![]() ![]() |
4: Compute the standard deviation (population) | ![]() ![]() ![]() ![]() ![]() ![]() |
5: Compute the standard deviation (sample) | ![]() ![]() ![]() ![]() ![]() |
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: To start | ![]() ![]() |
2: Enter Data | ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
3: Compute the slope of the regression line | ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
4: Compute the y-intercept of the regression line | ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
5: Compute the correlation | ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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 | ![]() ![]() ![]() ![]() ![]() ![]() |
2: Compute 9P5 | ![]() ![]() ![]() ![]() ![]() |
You should get 10C6 = 210 and 9P5=
15120.
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