0 100 200 300 400 500 600 Objective - To find the equation of the line of best fit for a given set of data. Animal Brain Weight (g) Max. Life (yr.) Mouse.

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Objective - To find the equation of the line of best fit for a given set of data. Animal Brain Weight (g) Max. Life (yr.) Mouse Fox Jaguar Sheep Pig Seal Donkey Chimp x y Brain Weight (g) Max. Life (yrs.)

x y Brain Weight (g) Max. Life (yrs.) Trend is increasing Scatterplot - a coordinate graph of data points. Line of Best Fit -Points act like magnets attracting the line. Trend looks linear

x y Brain Weight (g) Max. Life (yrs.) Line of Best Fit -Points act like magnets attracting the line. Trend is increasing Trend looks linear Scatterplot - a coordinate graph of data points.

x y Brain Weight (g) Max. Life (yrs.) Line of Best Fit -Points act like magnets attracting the line. Trend is increasing Trend looks linear Scatterplot - a coordinate graph of data points.

x y Brain Weight (g) Max. Life (yrs.) Line of Best Fit -Points act like magnets attracting the line. Trend is increasing Trend looks linear Scatterplot - a coordinate graph of data points.

x y Brain Weight (g) Max. Life (yrs.) Line of Best Fit -Points act like magnets attracting the line. Trend is increasing Trend looks linear Scatterplot - a coordinate graph of data points.

x y Brain Weight (g) Max. Life (yrs.) Steps 1) Plot the points. 2) Draw the line of best fit. 3) Take two points off the line. (50, 10) (450, 50) (50, 10)(450, 50)

x y Brain Weight (g) Max. Life (yrs.) Steps 1) Plot the points. 2) Draw the line of best fit. 3) Take two points off the line. (50, 10) (450, 50) (50, 10)(450, 50) 4) Find the equation of the line using the two points.

Steps 1) Plot the points. 2) Draw the line of best fit. 3) Take two points off the line. (50, 10)(450, 50) 4) Find the equation of the line using the two points. Actual

Scatterplots Which scatterplots below show a linear trend? a) c)e) b) d)f)

Finding the Line of Best Fit Outlier x y Line of Best Fit Ignore outliers.

Finding the Line of Best Fit x y No Line of Best Fit Equal # of points above and below the line. Does not have to go through any points. Ignore outliers.

Finding the Line of Best Fit x y No Line of Best Fit Equal # of points above and below the line. Does not have to go through any points. Ignore outliers. Points attract the line like magnets to a metal rod.

Finding the Line of Best Fit x y Yes Line of Best Fit Equal # of points above and below the line. Does not have to go through any points. Ignore outliers. Points attract the line like magnets to a metal rod.

Choosing Two Points x y Yes Chosen points are too close together.

Choosing Two Points x y Yes Chosen points have sufficient spread.

Year Find the equation of the line of best fit for the data below. Sport Utility Vehicles (SUVs) Sales in U.S. Sales (in Millions) x y Year Vehicle Sales (Millions)

Find the equation of the line of best fit for the data below x y Year Vehicle Sales (Millions) Steps 1) Plot the points. 2) Draw the line of best fit. 3) Take two points off the line. (1992, 1.1) (1999, 3) (1992, 1.1)(1999, 3) 4) Find the equation of the line using the two points.

Find the equation of the line of best fit for the data below. Steps 1) Plot the points. 2) Draw the line of best fit. 3) Take two points off the line. (1992, 1.1)(1999, 3) 4) Find the equation of the line using the two points. Actual

Find the equation of the line of best fit for the data below x y Year Vehicle Sales (Millions) (1992, 1.1) (1999, 3) If this trend continues, predict the sales for the year 2004.

The data below shows the gold medal perform- ance in high jump in some of the past Olympics Year High Jump (in.) x y Year High Jump (in.)

The data below shows the gold medal perform- ance in high jump in some of the past Olympics x y Year High Jump (in.) (1948, 78) (1988, 94) (1948, 78)(1988, 94)

The data below shows the gold medal perform- ance in high jump in some of the past Olympics (1948, 78)(1988, 94) Actual

The data below shows the gold medal perform- ance in high jump in some of the past Olympics x y Year High Jump (in.) (1948, 78) (1988, 94) If this trend continues, predict the gold medal height in 2004.