Lies and Statistics

The slope of the linear regression line (line of best fit) can be calculated using any two points in the scatterplot data.

• Sometimes True

• Always True

• Never True

If the correlation coefficient for a set of data is 0, then the line of best fit is horizontal.

• Sometimes True

• Always True

• Never True

The sum of the residuals for a good line of best fit is 0.

• Sometimes True

• Always True

• Never True

If the correlation coefficient is very large and close to 1, then there must be an outlier in the data.

• Sometimes True

• Always True

• Never True

A negative correlation coefficient means that the data points are very random and don't really fit a linear model.

• Sometimes True

• Always True

• Never True

A negative residual means that the regression line is very far from the actual data point.

• Sometimes True

• Always True

• Never True

If the correlation coefficient is positive, then the slope of the line of best fit will probably be positive.

• Sometimes True

• Always True

• Never True

If there is a perfect correlation between variables in the data, then the correlation coefficient is 1.

• Sometimes True

• Always True

• Never True

To find the value of a residual for a point (a,b) given a line of best fit, f(x)

find f(a)

find b- f(a)

if positive above the line

if negative below the line

• Sometimes True

• Always True

• Never True

The larger the residual for a given point, the further away the point is from the line of best fit.

• Sometimes True

• Always True

• Never True