Problem1 the data below shows the number of absences x and

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Reference no: EM13347768

PROBLEM1: The data below shows the Number of absences X and the Final Grade, Y of seven students in the statistics class.

Student	Number of absences x	Final Grade y
A	6	82
B	2	86
C	15	43
D	9	74
E	12	58
F	5	90
G	8	78

1365_Calculate the correlation coefficient.png

The relationship is linear. The negative slope shows that the relationship is negative; the more number of absences the lower the grade.

	X	Y	XY	X²	Y²
	6	82	492	36	6724
	2	86	172	4	7396
	15	43	645	225	1849
	9	74	666	81	5476
	12	58	696	144	3364
	5	90	450	25	8100
	8	78	624	64	6084
SUM	57	511	3745	579	38993

r = (7*3745-57*511)/squareroot[(7*579-57²)*(7*38993-511²)] =

= -2912/squareroot(804*11830)=-2912/3084.043= -.944

The correlation coefficient is -.944: It shows a very strong, negative relationship between the number of absences and the obtained grades.

r²= 89.15%. It represents the percent of the variances in the values of Y that can be explained by knowing the value of X. 89.15% of the variation of Y (number of absences) is explained by X (grades) and 10.85% is unexplained.

PROBLEM 2: The data below shows the reading (x) and math scores (y) of students.

Reading Scores	Math Scores
1	4
2	3
3	8
3	6
4	7
5	7
6	8
7	8
7	9
8	10
8	9
9	8

PROBLEM 3

The data below shows the score on a promotion test given to police officers and the number of hours studied. Calculate the correlation coefficient.

Hours Studied	Score on promotion test
0	0
1	1
2	1
3	2
4	5
6	6
12	8
16	10

PROBLEM 4: An emergency service wishes to see whether there a relationship exists between the outside temperature and the number of emergency calls it receives for a 7 hours period. The data is shown below.

Temperature x | 68 74 82 88 93 99 101

Number of calls | 7 5 7 9 11 12 15

PROBLEM 5:

A company that manufactures small lathes is interested in establishing standards for employees. A random sample of 18 employees is selected in order to develop the standards. The data collected is below.

A manager at the firm feels that assembly time is related to intelligence. She feels that employees who did well in high school (as measured by high school averages) should be able to do the job faster. Does the data support her hunch?

high school average	Time to assemble lathe (minutes)
50	52
62	53
65	62
68	70
71	73
73	78
75	80
79	82
80	85
82	86
83	90
85	94
88	95
90	106
90	111
94	120
94	139
100	145

Reference no: EM13347768

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