QUESTION 1

What is the most likely value of r, the correlation coefficient, in Plot A?

Plot A

	a.	0.45
	b.	1.00
	c.	0.95
	d.	0.65

1 points

QUESTION 2

What is the most likely value of r, the correlation coefficient, in Plot B?

Plot B

	a.	-0.65
	b.	0.00
	c.	-0.15
	d.	-0.95

1 points

QUESTION 3

Which of the following best describes the correlation between the variables show in Plot C?

Plot C

	a.	Weak, positive, and linear
	b.	Weak and non-linear
	c.	Strong, positive, and linear
	d.	Strong and non-linear

1 points

QUESTION 4

For questions 4 through 6, recall the formula for computing r:

What does, labeled in the image as A, refer to?

	a.	The standard deviation of a sample
	b.	The distance from each point in a sample to the mean of that sample
	c.	The mean of a sample
	d.	The z-score of a point in a sample

1 points

QUESTION 5

What does, labeled in the image as B, refer to?

	a.	The mean of a sample
	b.	The distance from a point in a sample to the mean of that sample
	c.	The standard deviation of the x-values in a sample
	d.	The z-score of a point in a sample

2 points

QUESTION 6

What does, labeled in the image as C, referto?

	a.	The standard deviation of a sample
	b.	The mean of a sample
	c.	The z-score of the y-values in a point in a sample
	d.	The distance from a point in a sample to the mean of that sample

2 points

QUESTION 7

What is the approximate slope of the line of best fit shown in Plot D?

Plot D

	a.	10
	b.	4
	c.	1
	d.	5

2 points

QUESTION 8

What is the approximate y-intercept of the best fit line shown in Plot D?

Plot D

	a.	20
	b.	140
	c.	8
	d.	0

2 points

QUESTION 9

Consider this simple linear equation for predicting how much value a certain car will lose during its first year on the road:

-0.08 *miles+ (-2400) =loss

What is the significance of the number -2400?

	a.	Even if the car is driven 0 miles, it will still lose $2400 in value
	b.	The car will be worth at least $2400 at the end of the year
	c.	The original value of the car is $2400

2 points

QUESTION 10

A line of best fit produced by the OLS method will always pass through _____________.

	a.	at least two of the points from the dataset
	b.	the point (0,0)
	c.	the point (mean of x, mean of y)

2 points

QUESTION 11

Using the convention ofresidual = data - fit, and considering the data and line of best fit shown on the left below, what would be the approximate shape of the residual plot among the four choices on the right?

	a.	C
	b.	A
	c.	B
	d.	D

2 points

QUESTION 12

Which of the following is always true of a model with a negative r-squared value?

	a.	there are too many variables in the model
	b.	there are not enough variables in the model
	c.	the data has a non-linear relationship
	d.	the model performs worse than a model that predicts the mean would perform

2 points

QUESTION 13

You have a dataset showing the sale price of 1000 used cars.If your data is distributed as seen in Plot F, you can transform this data to better approximate a normal distribution by taking the ____. The transformed data will be distributed as seen in Plot G.

Plot F

Plot G

	a.	integral
	b.	natural log
	c.	common log
	d.	square root

2 points

QUESTION 14

If you are trying to predict gas prices based on the distance in miles from an airport, price is the ________ variable and distance is the ___________ variable.

	a.	dependent, independent
	b.	they are both independent
	c.	independent, dependent

2 points

QUESTION 15

A cafe owner has noticed that the number of hot cocoas he sells seems to increase with the number of people wearing wool hats. While it might be possible to predict cocoa sales based on hat count (or vice versa), more people wearing hats does notcauseincreased cocoa sales. Which of the following is a possible confounding variable that affects both the number of people wearing hats and the sales of hot cocoa?

	a.	Changes in the cost of wool
	b.	Changes in the outside temperature
	c.	Changes in the popularity of the cafe

2 points

QUESTION 16

Consider the following hypothetical multiple linear model for estimating the number of cups of lemonade sold at a lemonade stand. "Weekend" is a boolean variable whose value is 0 for weekdays and 1 for weekends. All else being equal, how will the estimate for a Saturday differ from the estimate for a Friday?

cups sold= 2.3 *temperature+ (-40) *price+ 120 *weekend+ (-40)

	a.	There is not enough information to answer this question
	b.	The estimate for Saturday will be 120 times greater than the estimate for Friday
	c.	The estimate for Saturday will be 40 units (cups) less than the estimate for Friday
	d.	The estimate for Saturday will be 120 units (cups) greater than the estimate for Friday

2 points

QUESTION 17

Considering the multiple linear equation above (assuming temperature in degrees F and price in dollars) how many cups is the stand estimated to sell on a Wednesday when it's 80 degrees F and the cost of one cup is $1.50?

	a.	184 cups
	b.	84 cups
	c.	124 cups
	d.	204 cups