The position of the graphically represented keys can be found by moving your mouse on top of the graphic.

 Turn your calculator on Press . Clearing the memory Press (you should see CA, for Clear All, above the key).

 Entering data one variable Press (this brings us to the STAT menu).  Press for one variable mode.  Enter the first number, then .   Enter the second number, then .  Continue until all the data has been entered. two variables Press (this brings us to the STAT menu).  Press for two-variable mode (it calls it linear regression mode).  Enter the first x-value,  then .  Enter the corresponding y-value, then .  Enter the next pair the same way, and continue until all the data has been entered.

 Calculating one-variable statistics mean (x) Press .  You should see x  over the 4 key. standard deviation for populations (s or sn) Press .  You should see sx over the 6 key. standard deviation for samples (s or sn-1) Press .  You should see sx over the 5 key.

 Calculating two-variable statistics r (correlation) Press .  You should see r over the ÷ key. regression coefficients slope Press . You should see a over the left parenthesis key. y-intercept Press . You should see b over the right parenthesis key.

 Turning the calculator off Press and the calculator will turn off.

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 (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 3: Compute the slope of the regression line (a) 4: Compute the y-intercept of the regression line (b) 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.