stress_levels.xlsx contains data on the corticosterone levels of students measured before attending a biological data analysis class (column 'corticosterone_concentration_before_lecture') and the corticosterone levels of the same students measured before they took their final biological data analysis exam (column 'corticosterone_concentration_before_test'). Corticosterone is a stress hormone and, thus, its levels are an indication of the amount of stress the individual students are experiencing. This is clearly a paired design and you would ordinarily use a paired t-test to check if the stress levels increased before the exam. However, the data is skewed to the right and because some cortisol differences are negative a log transformation will not work. Therefore, you need to perform an appropriate non-parametric test to check if stress levels increase. What is the appropriate null hypothesis for the proper non-parametric test to run on stress_levels.xlxs? The shapes of the distributions of the corticosterone concentrations before a lecture and before a test are the same. The median corticosterone levels before a lecture and before a test are the same. The mean corticosterone levels before a lecture and before a test are the same. The median difference between the corticosterone levels before a lecture and before a test is 0. The mean difference between the corticosterone levels before a lecture and before a test is 0. What is the P-value obtained from an appropriate two-tailed non-parametric test of the data in stress_levels.xlsx? 2X10-9 0.35 0.05 0.001 2X10-20 1X10-11 5X10-5
stress_levels.xlsx contains data on the corticosterone levels of students measured before attending a biological data analysis class (column 'corticosterone_concentration_before_lecture') and the corticosterone levels of the same students measured before they took their final biological data analysis exam (column 'corticosterone_concentration_before_test'). Corticosterone is a stress hormone and, thus, its levels are an indication of the amount of stress the individual students are experiencing. This is clearly a paired design and you would ordinarily use a paired t-test to check if the stress levels increased before the exam. However, the data is skewed to the right and because some cortisol differences are negative a log transformation will not work. Therefore, you need to perform an appropriate non-parametric test to check if stress levels increase.
What is the appropriate null hypothesis for the proper non-parametric test to run on stress_levels.xlxs?
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The shapes of the distributions of the corticosterone concentrations before a lecture and before a test are the same. |
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The |
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The mean corticosterone levels before a lecture and before a test are the same. |
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The median difference between the corticosterone levels before a lecture and before a test is 0. |
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The mean difference between the corticosterone levels before a lecture and before a test is 0. |
What is the P-value obtained from an appropriate two-tailed non-parametric test of the data in stress_levels.xlsx?
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2X10-9 |
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0.35 |
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0.05 |
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0.001 |
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2X10-20 |
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1X10-11 |
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5X10-5 |
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