Stats Quiz #13 Hypothesis Testing
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
