Analyzing Two Variable Data

Estimate the correlation coefficient for this scatterplot.

• r = -0.9

• r = 1

• r = 0.9

• r = -1

A perfect positive correlation has a correlation coefficient of ____. 

• 1

• -1

• 0

A perfect negative correlation has a correlation coefficient of ____. 

• 1

• -1

• 0

What is the explanatory variable?

• Precipitation

• Cucumber Yield

What type of correlation does this graph have?

• Linear and Negative

• Non-Linear and No Association

• Linear and Positive

• Non-Linear and Negative

• Non-Linear and Positive

r = -0.3 is considered to have...

• moderate negative correlation

• weak negative correlation

• no correlation

• strong negative correlation

What can we determine from the correlation coefficient? 

• Style + Type

• Percentage + Direction

• Strength + Direction

• Strength + Style

If r=0 , then there is...

• Negative association

• No correlation

• Positive association

• The estimated slope is 6.1, which implies that girls in this population between the ages of 5 and 18 are predicted to grow about 6.1 centimeters in heights for each year they grow older.

• The estimated y-intercept is 50.3 centimeters. We can conclude from the intercept that the typical height of girls in this population at birth is 50.3 cm.

• A 10-year-old girl in this population is at least 110.3 cm tall.

• One particular 8-year-old girl is 115 cm tall. She is shorter than expected for girls her age in this population.

• For every 1 degree C increase in temperature, fish activity is predicted to increase by 4.785 units.

• The typical distance of the temperature readings from their mean is about 4.785 degrees C.

• The typical distance of the activity level ratings from the least-squares regression line is about 4.785 units.

• The typical distance of the activity-level ratings from their mean is about 4.785 units.