1)Sometimes an outlier can make or break a correlation. Data from 11 people regarding height and weight is given in the table below.

x= height (inches) y= weight (pounds)

72 180

72 219

66 138

63 105

66 181

63 191

72 182

63 180

63 151

60 103

6.4 198

(a) Find the correlation coefficient.

(b) Find the critical value.

(c) According to this data, is there a significant correlation between height and weight?

Yes

No

There seems to be something odd going on here. The height of 6.4 must be an error. No one is 6.4 inches tall. Perhaps the person entered his/her height in feet or maybe they meant to put 64 inches. Instead of trying to guess the error it is probably best to exclude it.

(d) If you exclude the last data point corresponding to a height of 6.4 inches, find the correlation coefficient.

(e) Find the critical value.

(f) According to this data, is there a significant correlation between height and weight?

Yes

No

2)Below is the time it took each of 15 students to get done with a Stats test and the score that each student got on the exam. Notice, the last data pair is somewhat unusual.

x= Test Time (minutes) y= Score (out of 100)

65 75

54 75

52 73

61 77

63 70

58 77

59 73

54 73

68 74

66 77

62 75

57 74

62 80

52 68

15 20

(a) Find the correlation coefficient.

(b) Find the critical value.

(c) Is there a significant correlation?

Yes

No

(d) Using only the first 14 data pairs, find the correlation coefficient.

(e) Find the critical value.

(f) Is there a significant correlation?

Yes

No