AP Statistics - Chapter 2A Extra Practice

1.	A study is conducted to determine if one can predict the yield of a crop based on the amount of yearly rainfall. The response variable in this study is 
	
A)	yield of the crop         B) amount of yearly rainfall       C) the experimenter        D) either bushels or inches of water	

3.	When creating a scatterplot, one should 
	
A)	use the horizontal axis for the response variable                 B) use the horizontal axis for the explanatory variable	
C)	use a different plotting symbol depending on whether the explanatory variable is categorical or the response variable is categorical	
D)	use a plotting scale that makes the overall trend roughly linear	

8.	Volunteers for a research study were divided into three groups. Group 1 listened to Western religious music, group 2 listened to Western rock music, and group 3 listened to Chinese religious music. The blood pressure of each volunteer was measured before and after listening to the music, and the change in blood pressure (blood pressure before listening minus blood pressure after listening) was recorded. To explore the relationship between type of music and change in blood we could 
	
A)	see if blood pressure decreases as type of music increases by examining a scatterplot	
B)	make a histogram of the change in blood pressure for all of the volunteers	
C)	make side-by-side boxplots of the change in blood pressure, with a separate boxplot for each group	
D)	do all of the above	

10.	A student wonders if people of similar heights tend to date each other. She measures herself, her dormitory roommate, and the women in the adjoining rooms; then she measures the next man each woman dates. Here are the data (heights in inches):
Women	
66	
64	
66	
65	
70	
65	

Men	
72	
68	
70	
68	
74	
69	

Which of the following statements is true? 
	
A)	The variables measured are all categorical	
B)	There is a strong negative association between the heights of men and women, since the women are always smaller than the men they date	
C)	There is a positive association between the heights of men and women	
D)	Any height above 70 inches must be considered an outlier	

14.	Consider the scatterplot below.
  
The correlation between X and Y is approximately 
	
A)	0.999               B) 0.8               C) 0.0             D) –0.7	

I wish to determine the correlation between the height (in inches) and weight (in pounds) of 21-year-old males. To do this I measure the height and weight of two 21-year-old men. The measured values are
	Male #1	Male #2	
Height	70	75	
Weight	160	200	

16.	Referring to the information above, the correlation r computed from the measurements on these males is 
	
A)	1.0        B) positive and between 0.25 and 0.75       C) near 0, but could be either positive or negative    D) exactly 0	

17.	Referring to the information above, the correlation r would have units in 
	
A)	inches         B) pounds        C) inches-pounds       D) no units.  Correlation has no unites of measurement	

22.	Volunteers for a research study were divided into three groups. Group 1 listened to Western religious music, group 2 listened to Western rock music, and group 3 listened to Chinese religious music. The blood pressure of each volunteer was measured before and after listening to the music, and the change in blood pressure (blood pressure before listening minus blood pressure after listening) was recorded. A scatterplot of change in blood pressure versus the type of music listened to is given below.

The correlation between change in blood pressure and type of music is 
	
A)	negative               B) positive             C) first negative then positive           D) none of the above	

23.	The profits (in multiples of $100,000) versus the sales (in multiples of $100,000) for a number of companies are plotted below.

Notice that in the plot profits is treated as the response variable and sales the explanatory variable. The correlation between profits and sales is 0.814. Suppose we had taken sales to be the response variable and profits to be the explanatory variable. In this case, the correlation between sales and profits would be 
	
A)	0.814        B) –0.814       C) 0.000       D) any number between 0.814 and –0.814, but we can't state the exact value	

26.	The fraction of the variation in the values of y that is explained by the least-squares regression of y on x is 
	
A)	the correlation coefficient                                           B) the slope of the least-squares regression line	
C)	the square of the correlation coefficient                      D) the intercept of the least-squares regression line	

29.	Foresters use regression to predict the volume of timber in a tree using easily measured quantities such as diameter. Let y be the volume of timber in cubic feet and x be the diameter in feet. (measured at three feet above ground level). One set of data gives            Y = –30 + 60x            The predicted volume for a tree of 18 inches is 
	
A)	1080 cubic feet                B) 90 cubic feet                   C) 60 cubic feet                 D) 30 cubic feet	

30.	A researcher wishes to determine whether the rate of water flow (in liters per second) over an experimental soil bed can be used to predict the amount of soil washed away (in kilograms). The researcher measures the amount of soil washed away for various flow rates and from these data calculates the least-squares regression line to be amount of eroded soil =0.4+1.3(flow rate) The correlation between amount of eroded soil and flow rate would be 
	
A)	1/1.3           B) 0.4              C) positive, but we cannot say what the exact value is	
D)	either positive or negative. It is impossible to say anything about the correlation from the information given. 	

31.	The least-squares regression line is the line that 
	
A)	makes the square of the correlation in the data as large as possible 	
B)	makes the sum of the squares of the vertical distances of the data points from the line as small as possible	
C)	best splits the data in half, with half of the points above the line and half below the line             D) all of the above	

36.	In a study of 1991 model cars, a researcher computed the least-squares regression line of price (in dollars) on horsepower. He obtained the following equation for this line.
	
price = –6677 + 175 (horsepower)	

Based on the least-squares regression line we would predict that a 1991 model car with horsepower equal to 200 would cost 
	
A)	$41,677               B) $35,000              C) $28,323                D) $13,354	

37.	A scatterplot of the calories and sodium content of several brands of meat hot dogs is shown below. The least-squares regression line has been drawn in on the plot. Referring to this scatterplot, the value of the residual for the point labeled x 

	
A)	is about 40            B) is about 1300           C) is about 425         D) cannot be determined from the information given	

40.	The least-squares regression line is fit to a set of data. If one of the data points has a positive residual, then 
	
A)	the correlation between the values of the response and explanatory variables must be positive	
B)	the point must lie above the least-squares regression line	
C)	the point must lie near the right edge of the scatterplot               D) all of the above	

42.	Consider the scatterplot below. 
  
The point indicated by the plotting symbol x would be 
	
A)	a residual                 B) influential                 C) a z-score                 D) a least-squares point	

43.	A sample of 79 companies was taken, and the annual profits (y) were plotted against annual sales (x). The plot is given below. All values in the plots are in units of $100,000.
  
The correlation between sales and profits is found to be 0.814. Based on this information, we may conclude which of the following? 
	
A)	Not surprisingly, increasing sales causes an increase in profits. This is confirmed by the large positive correlation	
B)	There are clearly influential observations present	
C)	If we group the companies in the plot into those that are small in size, those that are medium in size, and those that are large in size and compute the correlation between sales and profits for each group of companies separately, the correlation in each group will be about 0.8	
D)	All of the above	

Answer Key

1.	A	
3.	B	
8.	C	
10.	C	
14.	B	
16.	A	
17.	D	
22.	D	
23.	A	
26.	C	
29.	C	
30.	C	
31.	B	
32.	D	
34.	D	
36.	C	
37.	A	
40.	B	
42.	B	
43.	B