The position of the graphically represented keys can be found by moving your mouse on top of the graphic. The top row of round buttons is not counted as a row. The first row starts with the Short Cut 1 key.
Turn your calculator on | |||||||||
Press . | |||||||||
Clearing the memory | |||||||||
Not a problem. The memory seems to be cleared automatically. If it's not, just type over the current data and press once for every extra entry in the list. |
Entering data | |||
one variable | |||
Press to get to the statistics menu. Press to accept the first listing: 1-VAR:EXE. You'll see a column labeled X. Enter the numbers in your list, pressing after each one. Press to get back to the main screen. | |||
two variables | |||
Press to get to the statistics menu. Press to accept the second listing: A+BX:EXE. You'll see a two columns labeled X and Y. Enter the x-values in your list, pressing after each one. Press to get to the y-column. Press as many times as needed to get to the top of the list. Enter the y-values in your list, pressing after each one. Make sure the y-values correspond to the x-values. Press to get back to the main screen. |
Calculating one-variable statistics | ||||
mean (x) | ||||
Press . You'll see a menu. Press for 5:Var. A new menu appears. Press for x. Press for the calculation. | ||||
standard deviation for populations (s or s_{n}) | ||||
Press . You'll see a menu. Press for 5:Var. A new menu appears. Press for xsn. Press for the calculation. | ||||
standard deviation for samples (s or s_{n-1}) | ||||
Press . You'll see a menu. Press for 5:Var. A new menu appears. Press for xsn-1. Press for the calculation. |
Calculating two-variable statistics |
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r (correlation) | |||||
Press . You'll see a menu. Press for 7:Reg. A new menu appears. Press for r. Press for the calculation. | |||||
regression coefficients | |||||
slope | |||||
Press . You'll see a menu. Press for 7:Reg. A new menu appears. Press for B - the slope. Press for the calculation. | |||||
y-intercept | |||||
Press . You'll see a menu. Press for 7:Reg. A new menu appears. Press for A - the y-intercept. Press for the calculation. |
Calculating combinations and permutations | ||||
combinations (nCr) | ||||
Enter the n-value. Press , then press 9 times to get to the C entry. Press . You should see your number and C on the top line of the screen. Enter the r-value and press . | ||||
permutations (nPr) | ||||
Enter the n-value. Press , then press 18 times to get to the P entry. Press . You should see your number and C on the top line of the screen. Enter the r-value and press . | ||||
The Casio
FC-200V has two shortcut keys. I will describe how to make a short cut for
the nCr function: Press (down to C). Press (STO means Store). Press (down to FMEM1). Press . To use this in practice: Enter the n-value. Press (The FMEM above the key stands for function memory.) You should see C appear next to your n-value. Enter the r-value and press . |
Turning the calculator off | ||
Press . (You should see OFF above the key). |
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 e^{x} as (e^{x}).
A: What is the mean and standard deviation of the following list of numbers?
15 16 20 21
1: Clear Memory | automatic |
2: Enter Data | (1-VAR:EXE) |
3: Compute the mean | (5:Var) (x) |
4: Compute the population standard deviation | (5:Var) (xsn) |
5: Compute the sample standard deviation | (5:Var) (xsn-1) |
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 | automatic |
2: Enter Data | (A+BX:EXE) |
3: Compute the slope of the regression line | (7:Reg) (B) |
4: Compute the y-intercept of the regression line | (7:Reg) (A) |
5: Compute the correlation | (7:Reg) (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 _{10}C_{6} |
(9 times, C) |
2: Compute _{9}P_{5} | (18 times, P) |
You should get _{10}C_{6 }= 210 and _{9}P_{5}=
15120.
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