2.5 a correlation & best fitting lines

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2.5 Correlation & Best-Fitting Lines Today’s objectives: 1. I will use linear regression to approximate the best-fitting line for a set of data.

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Page 1: 2.5 a correlation & best fitting lines

2.5 Correlation & Best-Fitting Lines

Today’s objectives:1. I will use linear regression to

approximate the best-fitting line for a set of data.

Page 2: 2.5 a correlation & best fitting lines

Line of Best Fit Plot the data given in the table as

ordered pairs on a coordinate plane. This is a scatter plot.

Draw a line that models the data with the same # of points above and below the line.

Choose two points on the line and estimate their coordinates. Don’t have to be original data points.

Write the equation of the line.

Page 3: 2.5 a correlation & best fitting lines

Type of Correlation Positive Correlation: if the data fits a

line with a positive slope, it represents positive correlation.

Negative Correlation: if the data fits a line with a negative slope, it represents negative correlation.

Relatively No Correlation: if the data doesn’t fit a line with a positive or negative slope, it represents relatively no correlation.

Page 4: 2.5 a correlation & best fitting lines

Correlation Strength:Correlation Coefficient (r)

If r >0 but close to 1, there is a strong positive correlation.

If r >0 but close to 0, there is a weak positive correlation.

If r < 0 but close to -1, there is a strong negative correlation.

If r < 0 but close to 0, there is a weak negative correlation.