Correlation and Regression

Estimate the correlation coefficient for this scatterplot.

• A) r = 1.2

• B) r = 0.89

• C)r = 0

• D) r = -0.89

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

Describe the correlation in the graph shown.

• A) Strong Negative

• B) Strong Positive

• C) Weak Negative

• D) No Correlation

Tags

CCSS.HSF-LE.A.1B

Estimate the correlation coefficient for this scatterplot.

• A) r = -0.9

• B) r = 1

• C) r = 0.9

• D) r = -1

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

What type of correlation does this graph show?

• A) Positive

• B) negative

• C) none

• D) all of the above

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.8

As x increases, y decreases.

• A) no correlation

• B) negative correlation

• C) correlation coefficient

• D) positive correlation

Tags

CCSS.HSF-LE.A.1B

Which of the following statistics show how much variance there is between y–values and x–values?

• Coefficient of Determination
• Slope of the Regression Line
• Standard Deviation
• Variance

Tags

CCSS.HSS.ID.B.6

What is the best definition of the least squares regression line?

• The line that minimizes the squares of the horizontal distances between the data points and the line.
• The line that minimizes the squares of the vertical distances between the data points and the line.
• The line that minimizes the vertical distances between the data points and the line.
• The line that passes through the most number of data points.

Tags

CCSS.HSS.ID.C.7

Which of the following is the least–square regression line for this data?

• y = 3.85 – 0.01x
• y = 4.09 – 0.32x
• y = 6.30 – 0.59x
• y = 8.18 – 0.64x

Tags

CCSS.8.EE.C.8C

An influential observation is most often

• larger than most other values in the y–direction
• larger than most other values in the x–direction
• not an outlier
• an outlier in the x direction

Tags

CCSS.HSS.ID.A.3

A residual is

• the difference between the squares of predicted values in a LSRL and data points on a scatterplot
• the difference between the observed x–value and the predicted x–value.
• the difference between the predicted x–value and the observed x–value.
• the difference between the observed y–value and the predicted y–value.

Tags

CCSS.HSF-LE.A.1B