Introduction to Bivariate Data

A study compared the number of cars a person owns and that person’s average yearly salary. It was determined that the relationship between these two quantities was linear and the correlation was 0.37. Which conclusion can be made on the findings of this study?

• There was a weak relationship.

• There was a strong relationship.

• There was no relationship.

• Unpredictable.

Which value of r represents data with a strong negative linear correlation between two variables?

• -0.86

• -0.50

• 0.89

• 0.07

What is another way to say regression line?

• Histogram

• Boxplot

• Line of best fit

• Scatterplot

Scatterplots

• Are the line of best fit.

• Are a numerical measure of the direction and strength of a linear association.

• Show the relationship between two quantitative variables measured on the same cases.

• Are a point that doesn’t fit the overall pattern.

Correlation coefficients are:

• A point that does not fit the overall pattern.

• A histogram.

• A numerical measure of the direction and strength of a linear association.

• A graphical display.

Which correlation coefficient shows the strongest linear relationship between x and y?

• 0.97

• -0.02

• 0.86

• -0.99

A linear regression equation of best fit between how often someone runs and their weight (in kg) is w = 90.21 - 1.14r. The correlation coefficient would be

• 0<r<1

• -1<r<0

• r=1

• r=-1

Which value of r represents data with a strong positive linear correlation between two variables?

• -1.07

• 1.04

• 0.86

• 0.48

The relationship between a, a person’s age, and p, the amount of pets they’ve had, is modeled by the equation p = 0.01a + 4.3. Based on the linear regression model, the correlation coefficient could be:

• Between -1 and 0

• Between 0 and 1

• Equal to 0

• Equal to -1

What type of correlation (association)?
The outside temperature and the amount of layers you wear. 

• Positive correlation
• Negative correlation
• No correlation