Scatterplots and Linear Regression
6.6 in your textbook
Trend Line/Line of Best Fit
• Shows the relationship between 2 sets of data
• Rough estimate; more than one possible
correct answer
Linear Regression
• Same idea as finding a trend line, but we use a
calculator to do the dirty work for us
• More accurate; there will be one correct answer
Types of Correlation
• Positive when the values increase together
• Negative when one value decreases the other
increases
Correlation Coefficient
• Be careful! The value of the correlation shows
how good the correlation is! Not how steep the
line is!
• Values of r close to 0 imply that there is little to
no linear relationship between the data.
• Values of r close to 1 imply that there is a positive
linear relationship between the data. This means
that as x increases that y also increases.
• Values of r close to -1 imply that there is a
negative linear relationship between the data.
This means that as x increases that y decreases.
Draw a trend line.
• Use this line to predict the sales for 21°C.
• Use this line to predict the sales for 27°C.
Important Vocab
• Interpolation: finding values of data within
your sample
• Extrapolation: finding values beyond your
sample.
Graphing Calculator
Before we get started…
Just a quick set-up!
• Go to catalog
– Hit diagnostic on (This will allow you to calculate
your correlation coefficient) If you didn’t do this,
then your ‘r’ would be MIA
Using a Graphing Calculator!
• We will work through this example together
• Turn to page 321 #7
*Write down any notes or hints to help you find
the Linear Regression using a calculator.
Homework
• Practice 6.6 #s 1-3, 8-10
*If you have a graphing calculator available at
home, you can try #s 4-7