1. Notes 1-6 Linear Regression
Linear Regression can be used as
a tool for modeling real-world
data. This “line of best fit”
will help make predictions.

2. See diagrams on page 40 of your textbook.
r = correlation coefficient The more closely the data points fit a line, the closer the r value is to 1 or -1.
Positive r value = positive slope/trend
Negative r value = negative slope/trend
See diagrams on page 40 of your textbook.

3. See page 40: r is the correlation coefficient

4. Please turn to page 41 and begin #4a
Work on #4 together!!

5. b. Select 2 points on your graph and write an equation that could model the data. y = mx + b

6. 2nd catalog (above the zero button) Matrix D (above button)
Now that you have jumped to the D section, arrow down to find DiagnosticOn
Push <enter>, then <enter> again
Calculator should say “Done”

7. Please write these instructions in your notes:
STAT 1: edit
enter your “x” values
enter your “y” values
STAT calculate
4: Lin Reg (ax + b)
To clear values from a list:
highlight
push CLEAR, then ENTER

8. c. Enter data into two lists using the STAT menu and edit

9. STAT calculate 4: Lin Reg (ax + b)
c. Write an equation based on your linear regression, then state the “r” value (correlation coefficient)
STAT calculate
4: Lin Reg (ax + b)

10. d. Use your equation from part c to predict the missing value.

11. Reminder: only complete parts c and d for #5-10

12. Reminder: only complete parts c and d for #5-10
Find y = mx + b
Find r
Predict value

13. To clear values from a list:
Highlight a value, then push DEL (delete is toward the top row of buttons)
OR…
arrow up to very top of list and highlight
Push CLEAR, then ENTER to clear the entire list of values

14. If some of your lists have been completely deleted:
Go to STAT
5: set up editor
Push ENTER
Calculator should say “done”
Now push STAT, then edit
All lists should be on your screen