The production department of Celltronics International wants to explore the relationship between the number of employees who assemble a subassembly and the number produced.

The following sample observations were randomly selected.

X : 4 5 3 6 10
Y: 4 6 5 7 7

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(1)

Fill in the blanks below: (Round your answers to 2 decimal places.)


	correlation between X and Y.

(3)

Fill in the blanks. (Round your answer to the nearest whole number.)

The coefficient of determination obtained here indicates X accounts for approximately relationship between X and Y. The coefficient of determination is is the dependent variable.

(c)

Determine the correlation coefficient. (Round your answer to 2 decimal places.)

Coefficient of correlation

correlation between the variables.

4) The production department of Celltronics International wants to explore the relationship between the number of employees who assemble a subassembly and the number produced. As an experiment, two employees were assigned to assemble the subassemblies. They produced 15 during a one-hour period. Then four employees assembled them. They produced 25 during a one-hour period. The complete set of paired observations follows.

Number of Assemblers	One-Hour Production (units)
2	15
4	25
1	10
5	40
3	30

The dependent variable is production; that is, it is assumed that different levels of production result from a different number of employees.

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(b)

A scatter diagram is provided below. Based on it, does there appear to be any relationship between the number of assemblers and production?


	, as the number of assemblers, so does the production.

(c)

Compute the coefficient of correlation. (Negative amounts should be indicated by a minus sign. Round s_x, s_y and r to 3 decimal places.)

X	Y			( )²	( )²	( )( )
2	15	is the independent variable and is the dependent variable.

(b-1)

Determine the coefficient of correlation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.)

X	Y			( )²	( )²	( )( )
9.0	8.1	correlation between age of car and selling price. So, H_o. Weconclude that the correlation in the population is greater than zero.

7) The following hypotheses are given.

A random sample of 15 paired observations have a correlation of −.46. Can we conclude that the correlation in the population is less than zero? Use the .05 significance level. (Negative amount should be indicated by a minus sign. Round your answer to 3 decimal places.)

Reject H₀ if t < −1.771

H_o.

8) The following sample observations were randomly selected.

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X:	5	3	6	3	4	4	6	8
Y:	13	15	7	12	13	11	9	5

(a)

Determine the regression equation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.)

X	Y			()²	()²	( )( )
5	13	[removed]	2.375	[removed]	5.641	[removed]
3	15	−1.875	[removed]	3.516	[removed]	−8.203
6	7	[removed]	[removed]	[removed]	13.141	−4.078
3	12	−1.875	1.375	[removed]	[removed]	[removed]
4	13	−0.875	[removed]	0.766	[removed]	−2.078
4	11	[removed]	0.375	[removed]	0.141	[removed]
6	9	1.125	−1.625	[removed]	[removed]	[removed]
8	5	[removed]	[removed]	[removed]	31.641	−17.578
[removed]	[removed]			[removed]	[removed]	[removed]

[removed]

s_x

[removed]

s_y

[removed]

Y’ = [removed]+ [removed]X

(b)	Determine the value of when X is 7. (Round your answer to 3 decimal places.)

	[removed]

9) Bradford Electric Illuminating Company is studying the relationship between kilowatt-hours (thousands) used and the number of rooms in a private single-family residence. A random sample of 10 homes yielded the following.

Number of Rooms	Kilowatt-Hours (thousands)	Number of Rooms	Kilowatt-Hours (thousands)
12	9	8	6
9	7	10	8
14	10	10	10
6	5	5	4
10	8	7	7

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(a)

Determine the regression equation. (Round your answers to 3 decimal places.)

= [removed] + [removed]X

(b)

Determine the number of kilowatt-hours, in thousands, for a six-room house.(Round your answer to 3 decimal places.)

Number of kilowatt-hours

[removed]

10) Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the Y column shows the value of sales ($ thousands) last month for each client sampled.

Number of Contacts, X	Sales ($ thousands), Y	Number of Contacts, X	Sales ($ thousands), Y
14	24	23	30
12	14	48	90
20	28	50	85
16	30	55	120
46	80	50	110

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(a)

Determine the regression equation. (Negative amounts should be indicated by a minus sign.Do not round intermediate calculations. Round final answers to 2 decimal places.)

X	Y			( ) ²	( )²	( )( )
14	[removed]	[removed]	[removed]	376.36	1376.41	719.74
12	14	−21.4	−47.1	[removed]	[removed]	[removed]
20	[removed]	−13.4	[removed]	179.56	[removed]	443.54
16	30	[removed]	−31.1	[removed]	967.21	[removed]
46	[removed]	12.6	[removed]	[removed]	357.21	[removed]
23	[removed]	−10.4	[removed]	[removed]	967.21	[removed]
48	90	[removed]	28.9	213.16	[removed]	421.94
50	85	[removed]	23.9	275.56	[removed]	396.74
55	[removed]	[removed]	[removed]	466.56	3469.21	1,272.24
50	110.0	16.6	48.9	[removed]	[removed]	[removed]
[removed]	[removed]			[removed]	[removed]	[removed]

[removed]

s_x

[removed]

s_y

[removed]

b =[removed]

a = [removed]

Y’ = [removed]+ [removed]X

(b)

Determine the estimated sales if 40 contacts are made.(Do not round intermediate calculations. Round final answers to 2 decimal places.)

[removed]