Gender	Age	Salary	Overtime	Job
1	34	72000	1	3
1	37	54000	2	2
0	30	50000	5	2
1	27	46000	10	2
0	30	48000	4	2
1	34	59000	1	1
1	48	55000	2	2
0	25	40000	6	2
0	21	45000	5	1
1	39	57000	1	1
1	54	78000	1	3
1	47	64000	2	3
0	21	38000	3	2
0	34	62000	0	2
1	24	58000	2	2
1	42	63000	1	2
1	19	32000	8	1
0	24	31000	6	3
0	26	40000	10	2
1	40	58000	0	2
0	39	62000	1	2
0	22	43000	4	3
1	39	51000	6	2
0	22	46000	0	2
1	31	54000	3	3
1	45	54000	5	3
1	33	54000	4	3
0	31	49000	5	2
0	20	41000	13	1
0	22	51000	2	1
1	23	43000	7	2
0	39	31000	5	2
0	40	64000	3	2
0	29	62000	9	3
1	29	45000	13	3
0	42	66000	4	3
0	39	63000	2	2
0	37	57000	5	2
1	42	67000	1	1
1	44	65000	4	3
1	37	49000	1	1
1	33	61000	0	3
1	31	44000	0	1
0	24	38000	12	2
0	31	42000	5	2
1	36	73000	3	3
1	26	42000	11	2
0	49	61000	1	3
1	34	53000	2	2
0	25	39000	7	2
0	28	26000	11	2
0	23	34000	12	1
0	28	60000	5	1
1	35	34000	6	1
0	33	79000	3	2
0	40	77000	1	2
1	27	54000	11	1
0	33	57000	5	1
0	31	66000	2	2
0	33	83000	2	1

A study was commissioned to investigate the characteristics of employees at a major business. Data was collected on 60 employees and the following variables recorded.

Column 1 Gender What is your gender? (1 = Male, 0 = Female)

Column 2 Age How old are you?

Column 3 Salary What is your yearly salary (before Tax)?

Column 4 Overtime How much overtime do you work each week?

Column 5 Job Type What department do you work in? (1 = Purchasing,

2 = Marketing/Human Resource, 3 = Accounting)

Q.

Can we conclude, at a 5% level of significance, that a linear relationship exists between the employee's Salary (y) and employee's Age (x)?