Stats Quiz #13 Hypothesis Testing

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A type 2 error is always worse than a type 1 error.

false

As alpha gets smaller, your CV gets smaller.

false

As alpha increases, power decreases.

false

Beta is both your statistical significance level and your type 1 error rate.

false

Convicting an innocent man is the equivalent of making a type 2 error.

false

If your results are statistically significant, you should fail to reject the null hypothesis.

false

It is always appropriate to use a directional alternative hypothesis.

false

It is technically correct to conclude by "accepting" rather than "failing to reject" H0.

false

Stating that the President's approval rating is between 44-48% is an example of a point estimate.

false

The alternative hypothesis must be nondirectional.

false

The more stringent the alpha level is, the easier it is to detect an effect of the independent variable on the dependent variable.

false

Type I errors are always worse to make than Type II errors.

false

If we set alpha at 0.05 instead of 0.01

greater risk of a Type I error and a lesser risk of a Type II error

With the effect of the independent variable and N held constant, as a gets more stringent _________.

power decreases

If p(obtained) from an experiment equals 0.05 and alpha equals 0.05 (both two-tailed), what would you conclude?

reject H0

If a = 0.051 tail and the obtained result has a probability of 0.01 and is in the opposite direction to that predicted by H1, we conclude by _________.

retaining H0

lf alpha is changed from 0.05 to 0.01, _________.

the probability we will retain a false H0 increases

In an experiment with a repeated measures design _________.

the same subjects receive both treatments

A power analysis is useful when the results of an experiment fail to reach significance.

true

Alpha is usually set to .05.

true

As alpha gets smaller, your CV gets larger.

true

As alpha increases, power increases.

true

If H0 is false and we reject it, we have made a Type II error.

true

If H0 is false, and we retain it, we have made a Type II error.

true

If H0 is true and we reject it, we have made a Type I error.

true

If H0 is true, beta equals 0.00.

true

If a = 0.01 and H1 is 2-tailed then there is 0.005 under each tail.

true

If alpha is made more stringent, beta increases.

true

If sample size increases, power increases.

true

If the result turns out to be in the direction opposite to a directional H1, we must conclude by retaining H0. Group of answer choices

true

If your results are statistically significant, you should reject the null hypothesis.

true

If your test statistic (TS) is smaller than the critical value (CV), you should fail to reject the null.

true

In hypothesis testing it is incorrect to evaluate the probability of the specific outcome of the experiment.

true

It is permissible to use a directional H1 when there are good theoretical as well as strong supporting data to justify the predicted direction.

true

Letting a guilty man go free is equivalent to a type 2 error.

true

Power goes up if effect size increases.

true

Regardless of whether H1 is directional or nondirectional, when evaluating H0 we always assume chance is responsible for the differences in results between conditions.

true

Together, power and type 2 error rates must equal 1.0.

true

It is important to know the possible errors (Type I or Type II) we might make when rejecting or retaining H0 _________.

Answer: All of the above to minimize these errors when designing the experiment to be aware of the fallacy of "accepting H0" to maximize the probability of making a correct decision by proper design

If you retain the null hypothesis, you may be making _________.

a Type II error and a correct decision

If H0 is true, then the probability of rejecting H0 is limited by _________.

alpha


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