Unit 6 Part 2 Test Study Guide

Sarah has an ice cream stand. She noticed that when it is hotter outside more people buy ice cream.

• There is no correlation between the temperature and ice cream sales

• There is a negative correlation between the temperature and ice cream sales.

• There is both a positive and negative correlation between the temperature and ice cream sales.

• There is a positive correlation between the temperature and ice cream sales.

Match the Scatter Plot to the correct correlation.

• $r=0.156$

• $r=-0.766$

• $r=0.821$

Match the Scatter Plot to the correct correlation.

• $r=0.156$

• $r=-0.766$

• $r=0.821$

Match the Scatter Plot to the correct correlation.

• $r=-0.766$

• $r=0.821$

• $r=0.156$

Which of the r values below indicates that a linear model fits the data very well?

• $r=0.21$

• $r=-1$

• $r=0$

Which graphs have a positive r value?

• 
• 
• 
• 
• 

The local ice cream shop keeps track of how much ice cream they sell versus the noon temperature on that day. Their findings for the last 12 days can be found in the table. Which of the following statements are true?

• There is a strong negative correlation between the temperature and ice cream sales.

• There is a strong positive correlation between the temperature and ice cream sales.

• There is a weak positive correlation between the temperature and ice cream sales.

• There is no correlation between the temperature and ice cream sales.

Find the y-intercept of the graph.

• When the hours worked is 0, the dollars earned is 24.

• When the dollars earned is 0, the hours worked is 24.

• When the hours worked is 8, the dollars earned is 24.

• When the hours worked is 0, the dollars earned is 0.

Kenny is a psychology professor studying the effect of media violence on a modern culture. As a part of his research, he analyzed the content of several recent action movies. For each movie ,he noted the running time (in minutes),x, and the number of explosions, y.
The least squares regression line of this data set is  $y=0.153x-5.017$  
For each additional minute of running time, the least squares regression line predicts that an action movie would have how many additional explosions?

• With each increase of 1 minute, the number of explosions increases by 0.153

• With each decrease of 1 minute, the number of explosions increases by 5.017

• With each increase of 1 explosion, the number of minutes increases by 0.153

• With each increase of 1 minute, the number of explosions decreases by 5.017

The following is a scatter plot relating Julie's age (years) and height (cm). Using technology, find the linear function that best models this situation

• $y=73.6x+10.1$

• $y=12.6x+45.7$

• $y=10.25x+59.4$

• $y=61.5x+16.8$