A statistician analyzing a randomized controlled experiment has tested
Null: The treatment does nothing. Alternative: The treatment does something.
using a 4% cutoff for P-values. The P-value of the test turns out to be about 1.8%.
1.
The conclusion of the test is
-The treatment does nothing.
- The treatment does something.
2.
“P=1.8% means that there is only about a 1.8% chance that the treatment does nothing.”
The quoted statement is
-True
-False
problem 1:
The treatment does something
Problem 2:
False
thanks
1. The conclusion of the test is that the treatment does something. We reject the null hypothesis (the treatment does nothing) in favor of the alternative hypothesis (the treatment does something) when the p-value is below the cutoff (4% in this case).
To get this answer, we compare the p-value (1.8%) with the predetermined significance level (4%). If the p-value is less than the significance level, we reject the null hypothesis and conclude that the treatment does something.
2. The quoted statement is false. The p-value (1.8%) represents the probability of observing the data (or more extreme data) under the assumption that the null hypothesis is true. It does not directly represent the probability of the treatment having any effect. It is used to determine whether there is evidence to reject the null hypothesis in favor of the alternative hypothesis.