Chapter 3 AP Stats Review

Write the linear regression equation for the data set foot length (x) and height (y).

• y = 28.93 + 1.155x

• y = 28.39 + 1.155x

• y = 1.878 + 117.99x

• y = 117.99 + 1.878x

LSRL stands for

• Least Sum Regression Line

• Least Squares Regression Line

• Lower Standard Regression Line

• Line Scatterplot Regression Line

The correlation coefficient, r, is a value between

• 0 and 1

• 0 and 100

• -1 and 1

• -2 and 2

In a scatterplot  r² is called

• Coefficient of Determination

• Correlation Coefficient

• Regression Line

• Slope

The graph shows the diameters of a number of white oak trees versus their ages.
The growth factor of white oak trees is approximatively:

• 0.2 years/inch

• 2 years/inch

• 5 years/inch

• 10 years/inch

Tags

CCSS.HSF.IF.B.4

• This residual graph represents a linear fit.
• This graph represents a nonlinear fit.
• This residual graph represents no fit.

What type of correlation exists between the number of people that go to the pool and the temperature outside.

• positive

• negative

• no correlation

• unknown

The point in the upper right hand corner of the scatterplot is

• not an outlier or an influential point

• not an outlier but an influential point

• an outlier and an influential point

• an outlier but not an influential point

The table shown is comparing a person's foot length to their height in cm. Calculate the regression equation

• yhat = 25.05x + 5.57

• yhat = 5.57x + 25.05

• yhat = -5.57x + 25.05

• yhat = 5.57x - 25.05

Write the linear regression equation for the data set foot length (x) and height (y).

• yhat = 28.93 + 1.155x

• height = 28.39(foot length) + 1.155

• yhat = 1.878 + 117.99x

• height = 117.99 + 1.878(foot length)