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Algebra 2 – 2.5 extended. Do Now. Continue making scatterplots (using data from the other day). Line of Best Fit. Def: The line that is the closest fit of the data that you have Should have about the same amount of points above and below Use to make predictions about the data.
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Do Now • Continue making scatterplots (using data from the other day)
Line of Best Fit • Def: The line that is the closest fit of the data that you have • Should have about the same amount of points above and below • Use to make predictions about the data
Line of Best Fit • We can use graphing calculators to find the line of best fit • For our project, I will show you, individually how to do this • But – how does the calculator figure out which line is the BEST?
Strong Correlation • The other day, we defined three types of correlation: positive, negative, none • There can also be STRONG or WEAK correlation • Strong Correlation: the data points are very close to the line of best fit • There are a few different ways to calculate how strong a correlation is.
Compare the line of best fit to the actual data points! If (x, y) is a data point, call the point on the line with the same x-value: (x, y) For each data point, calculate: y - y
Correlation Coefficient • SQUARE: so we end up with only positive values and the numbers don’t cancel each other out • SUM AND DIVIDE: we want the average distance • ONLY DIVIDE BY N – 2: N is the number of data points. We ignore two because it takes two points to define a line.
For your project data: • Pick x and y • Note: which do you think is influencing the other? • Caution: correlation and causation are NOT the same thing