Kurtis is a statistician who claims that the average salary of an employee in the city of Yarmouth is no more than $55,000 per year. Gina, his colleague, believes this to be incorrect, so she randomly selects 61 employees who work in Yarmouth and record their annual salary. Gina calculates the sample mean income to be $56,500 per year with a sample standard deviation of 3,750. Using the alternative hypothesis Ha:μ>55,000, find the test statistic t and the p-value for the appropriate hypothesis test. Round the test statistic to two decimal places and the p-value to three decimal places. probability 0.0004 0.0014 0.0024 0.0034 0.0044 0.0054 0.0064 Degrees of Freedom               54 3.562 3.135 2.943 2.816 2.719 2.641 2.576 55 3.558 3.132 2.941 2.814 2.717 2.640 2.574 56 3.554 3.130 2.939 2.812 2.716 2.638 2.572 57 3.550 3.127 2.937 2.810 2.714 2.636 2.571 58 3.547 3.125 2.935 2.808 2.712 2.635 2.569 59 3.544 3.122 2.933 2.806 2.711 2.633 2.568 60 3.540 3.120 2.931 2.805 2.709 2.632 2.567

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Kurtis is a statistician who claims that the average salary of an employee in the city of Yarmouth is no more than $55,000 per year. Gina, his colleague, believes this to be incorrect, so she randomly selects 61 employees who work in Yarmouth and record their annual salary. Gina calculates the sample mean income to be $56,500 per year with a sample standard deviation of 3,750. Using the alternative hypothesis Ha:μ>55,000, find the test statistic t and the p-value for the appropriate hypothesis test. Round the test statistic to two decimal places and the p-value to three decimal places.

probability 0.0004 0.0014 0.0024 0.0034 0.0044 0.0054 0.0064
Degrees of Freedom              
54 3.562 3.135 2.943 2.816 2.719 2.641 2.576
55 3.558 3.132 2.941 2.814 2.717 2.640 2.574
56 3.554 3.130 2.939 2.812 2.716 2.638 2.572
57 3.550 3.127 2.937 2.810 2.714 2.636 2.571
58 3.547 3.125 2.935 2.808 2.712 2.635 2.569
59 3.544 3.122 2.933 2.806 2.711 2.633 2.568
60 3.540 3.120 2.931 2.805 2.709 2.632 2.567
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