Ch 9 Regression Wisdom

The image shows a cluster of points with a "stray point." Which answer choice best describes this stray point? 

• Leverage Point
• Influential Point 
• Outlier
• A "Loner" Point

Tags

CCSS.HSS.ID.A.3

The image shows a cluster of points with a "stray point." Which answer choice best describes this stray point? 

• High Leverage only
• Influential Point, outlier, high leverage 
• Outlier only 
• High Residual 

Tags

CCSS.HSS.ID.A.3

CCSS.HSS.ID.B.6

Which statement(s) about influential points is true?

I. Removal of an influential point changes the regression line.

II. Influential points have high leverage.

III. Influential points have large residuals.

• I only

• I and II

• I and III

• II and III

• I, II, and III

Tags

CCSS.HSS.ID.A.3

If the point in the upper right corner of this scatterplot is removed from the data set, then what will happen to the slope(b) of the line of best fit and to the correlation(r)?

• both will increase

• both will decrease

• b will increase, and r will decrease

• b will decrease, and r will increase

• both will remain the same

Tags

CCSS.HSF-LE.A.1B

Which is true?

I. Random scatter in the residuals indicates a model with high predictive power.

II. If two variables are very strongly associated, then the correlation between them will be near

+1.0 or -1.0.

III. The higher the correlation between two variables the more likely the association is based in cause and effect.

• none

• I only

• II only

• I and II only

• I, II, and III

Tags

CCSS.HSS.ID.B.6

CCSS.HSS.ID.C.9

Two variables that are actually not related to each other may nonetheless have a very high correlation because they both result from some other, possibly hidden, factor. This is an example of

• leverage

• a lurking variable

• extrapolation

• regression

• an outlier

Tags

CCSS.HSS.ID.C.9

The database printout shows the analysis of correlation between height and foot length. Write the linear regression equation for the data set foot length (x) and height (y).

• yhat = 28.93 + 1.155x

• height = 117.99+1.878(foot length)

• yhat = 1.878 + 117.99x

• predicted height = 117.99 + 1.878(foot length)

Tags

CCSS.HSF.LE.B.5

What is an outlier?

• A data point that cannot be explained
• A data point that is normal
• A data point that does not fit the overall pattern
• A data point that has eaten too much ice cream

Tags

CCSS.HSS.ID.A.3

What is a line of best fit used for?

• To make predictions
• To make the graph look pretty
• To connect the points
• To make it look like you know what you are doing

Tags

CCSS.8.EE.B.5

The _________________ ____________________ measures the strength of the relationship between 2 variables.

• Correlation Coefficient
• Causation
• Independent Variable
• Coefficient of Determination

Tags

CCSS.HSF-LE.A.1B