# data[].attributes.body
When hand drawing a line of best fit, ALWAYS USE A RULER

# data[].attributes.body
Hey! I’m on the whiteboard!

# data[].attributes.body
a LOBF is positioned as close as possible to all of the data points

# data[].attributes.body
A line of best fit generalises the relationship between two variables.

# data[].attributes.body
A line of best fit can be added when points on a scatter plot lie closely in a strong linear pattern.

# data[].attributes.body
*clap clap*

# data[].attributes.body
Interpolations are good, extrapolations arebad

# data[].attributes.body
Nice typing

# data[].attributes.body
The line is straight depicting a linear trend.

# data[].attributes.body
-A line of best fit is used to generalise the relationship between two variables.

# data[].attributes.body
-A line of best fig

# data[].attributes.body
• interpolation is predicting a value on the line of best fit
• A line of best fit is as close as possible to data points
• An equation only requires two points
• Most important! y-y1 = m(x-x1)
• Extrapolation is predicting a value not on the line of best fit

# data[].attributes.body
The predictions form L.O.B.F are not accurate values

# data[].attributes.body
Line is drawn to fit as many points as possible and if there are points that do not fit, line is positioned to have an equal number above and below.

# data[].attributes.body
line is positioned with an equal number of points above and below

# data[].attributes.body
make the line as close to as many data points as possible

# data[].attributes.body
equal number of points above and below the line

# data[].attributes.body
Provides a GENERAL relationship between two variables, if such relationship existS

# data[].attributes.headline
A line as close as possible to ALL data points

# data[].attributes.subject
A line as close as possible to ALL data points

# data[].attributes.body
A line of best fit needs to be as close as possible to the points of data

# data[].attributes.body
A line of best fit follows the formula y=mx+c

# data[].attributes.body
shows the relationship between two variables

# data[].attributes.body
2 types of prediction, extrapolation + interpolation. Interpolation is inside the dataset, extrapolation is outside the dataset