Significance Tests

When performing a significance test, we're looking for convincing evidence to __________ the null hypothesis in favor of the alternative hypothesis.

• refute

• dispute

• reject

• accept

To answer the question, "Is the evidence convincing enough to reject the null?" we can't just look at our sample statistic. Why not? Because samples ________.

• are all the same

• vary

• are too small

• affect the standard deviation

A significance test produces a _______ that accounts for the variability in sampling.

• z-score

• critical value

• t*-value

• p-value

Small p-values mean that our sample was very unlikely if the null hypothesis is true. Therefore, small p-values are ________________ that the null hypothesis is wrong.

• convincing evidence

• believable proof

• reliable information

• justifiable inference

How small is a small p-value? All year we have defined small as any probability that is less than _________.

• 1%

• 2.5%

• 5%

• 10%

Whatever probability we choose as the cutoff for what is small is what we call the ____________________.

• importance level

• significance level

• meaningfulness level

• insightfulness level

The symbol for the significance level is ____.

• $\alpha$

• $\theta$

• $\pi$

• $\mu$

The most common significance levels are _____ ______.

• 0.1 and 0.5

• 0.05 and 0.1

• 0.05 and 0.01

• 0.5 and 0.01

• fail to reject, statistically significant

• reject, statistically significant

• fail to reject, not statistically significant

• reject, not statistically significant

If the p-value > $\alpha$  , then the sample is not unusual if the null is true, so we ______ the null, so there is not convincing evidence that the alternative hypothesis is true, so the results are ________. 

• fail to reject, not statistically significant

• fail to reject, statistically significant

• reject, not statistically significant

• reject, statistically significant