If the p-value is less than 0.05 then we would only see a sample as extreme as the one that we saw less than 5% of the time Correct Answer assuming that the null hypothesis is true, we would only see a sample as extreme as the one that we saw less than 5% of the time there is more than a 5% chance that the null hypothesis is true there is less than a 5% chance that the null hypothesis is true.
Question
If the p-value is less than 0.05 then we would only see a sample as extreme as the one that we saw less than 5% of the time Correct Answer assuming that the null hypothesis is true, we would only see a sample as extreme as the one that we saw less than 5% of the time there is more than a 5% chance that the null hypothesis is true there is less than a 5% chance that the null hypothesis is true.
Solution
The correct answer is: "assuming that the null hypothesis is true, we would only see a sample as extreme as the one that we saw less than 5% of the time".
This is because the p-value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p-value, the greater the statistical evidence you have to reject the null hypothesis.
So, if the p-value is less than 0.05, it means that there is less than a 5% chance that the difference you observed happened by chance, assuming the null hypothesis is true. Therefore, we would only see a sample as extreme as the one we saw less than 5% of the time.
The other statements are incorrect. The p-value does not directly tell us the probability that the null hypothesis is true or false.
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