The position of the graphically
represented keys can be found by moving your mouse on top of the graphic.
The row of function keys: f1, f2, etc. do not count as a row. Row 1 starts
with the blue 2nd key.
Turn your calculator on | |||||||||
Press . | |||||||||
Clearing the memory | |||||||||
In the Stats/List area, arrow to the top of the list and press the as many times as needed. |
Entering data | |||
one variable | |||
Press , then arrow over to the Stats/List Editor. (Which arrows you press depends on which APP you used last.) Press . Enter the first number in your list and press . Enter the remaining numbers in your list, pressing after each one. | |||
two variables | |||
Press , then arrow over to the Stats/List Editor. Press . Enter the first x-value in your list and press . Enter the remaining x-values, pressing after each one. Press to get to the next column. Type in each corresponding y-value, pressing after each number. |
Calculating one-variable statistics | ||||
mean (x) | ||||
Press (CALC). Now press for 1-Var Stats. Enter list1 in the List: area. You only have to do this once. The calculator will remember it for future calculations. Press . A list in a new window will appear. The first entry in the list is x. | ||||
standard deviation for populations (s or sn) | ||||
As above. sx is the fifth entry in the list. | ||||
standard deviation for samples (s or sn-1) | ||||
As above. sx is the fourth entry in the list. |
Calculating two-variable statistics |
|||||
r (correlation) | |||||
Press (CALC). Now press for Regression, then for LinReg(ax+b). Enter list1,list2 in the List: area. You only have to do this once. The calculator will remember it for future calculations. Press . A list in a new window will appear. The fourth entry in the list is r. | |||||
regression coefficients | |||||
slope | |||||
Press (CALC). Now press for Regression, then for LinReg(ax+b). Enter list1,list2 in the List: area. You only have to do this once. The calculator will remember it for future calculations. Press . A list in a new window will appear. The first entry in the list is the slope a. | |||||
y-intercept | |||||
Press (CALC). Now press for Regression, then for LinReg(ax+b). Enter list1,list2 in the List: area. You only have to do this once. The calculator will remember it for future calculations. Press . A list in a new window will appear. The second entry - b - is the y-intercept. | |||||
Note: Instead of for LinReg(ax+b), you could press for LinReg(a+bx). Then a would be the y-intercept and b would be the slope. Whatever you're most comfortable with. |
Calculating combinations and permutations | ||||
combinations (nCr) | ||||
Press (says MATH over it). A menu will appear. Press (for 7:Probability) (for 3:nCr) Enter n. Press . Enter r. Press . | ||||
permutations (nPr) | ||||
Press (says MATH over it). A menu will appear. Press (for 7:Probability) (for 2:nPr) Enter n. Press . Enter r. 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: Enter Data | and to Stats/List editor |
2: Compute the mean | (CALC) (1-Var Stats) list1(if necessary) x is the first entry |
3: Compute the population standard deviation | (CALC) (1-Var Stats) list1(if necessary) sx is the fifth entry |
4: Compute the sample standard deviation | (CALC) (1-Var Stats) list1(if necessary) sx is the fourth entry |
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: Enter Data | and to Stats/List editor |
2: Compute the slope of the regression line | (CALC) (Regression) (LinReg(ax+b)) list1 list2 (if necessary) a is first |
3: Compute the y-intercept of the regression line | (CALC) (Regression) (LinReg(ax+b)) list1 list2 (if necessary) b is second |
4: Compute the correlation | (CALC) (Regression) (LinReg(ax+b)) list1 list2 (if necessary) r is fourth |
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 |
(MATH) (Probability) (nCr) |
2: Compute 9P5 | ( MATH) (Probability) (nPr) |
You should get 10C6 = 210 and 9P5=
15120.
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