Which of the following correctly describes the effect of decreasing the significance level (e.g. from p < .05 to p < .01) in hypothesis testing?
A. It increases the likelihood of rejecting H0 and increases the risk of a Type I error.
B. It decreases the likelihood of rejecting H0 and increases the risk of a Type I error.
C. It increases the likelihood of rejecting H0 but decreases the risk of a Type I error.
D. It decreases the likelihood of rejecting H0 but also decreases the risk of a Type I error.
It decreases the likelihood of rejecting H0 but also decreases the risk of a Type I error.
Option D is correct.
Which of the following correctly describes the effect of decreasing the significance level (e.g. from p...
Which statement best describes the significance level of a hypothesis test? The probability of obtaining a sample under the assumption that the null hypothesis is true that is more unusual than the observed sample b. The probability of making a Type 1 error The probability of making a Type Il error. d. The probability of correctly rejecting the null hypothesis.
1.) The Probability of correctly rejecting H0 when H0 is false is called the: a.) Level of significance b.) Type I error c.) Power of the Test d.) large-sample validity .................................................................................. 2.) As the sample size increases, the power of the test: a.) decreases b.) increases c.) does not change
Keeping everything else the same, if you were to change your alpha level from .01 to .05, the likelihood of rejecting the null hypothesis A. Increases B. Decreases C. Remains the same
1. a) For a test at a fixed significance level, and with given null and alternative hypotheses, what will happen to the power as the sample size increases? b) For a test of a given null hypothesis against a given alternative hypothesis, and with a given sample size, describe what would happen to the power of the test if the significance level was changed from 5% to 1%. c) A test of a given null hypothesis against a given alternative...
11. If the null hypothesis is rejected at a 05 significance level, it (a) must also be rejected at a.10 significance level. (b) might also be rejected at a .10 significance level. (c) must not be rejected at a.10 significance level. (d) none of the above lfte null hypothesis İs not rejected at a .05 significance level, it: (a) will also not be rejected at a.01 significance level. (b) might be rejected at a .01 significance level. (e) will be...
Choose the correct definition of significance level from the
list below.
A significance level is
Option 1 and 5 are WRONG
Choose the correct definition of significance level from the list below A significance level is the probability of failing to reject the null hypothesis when the alternative hypothesis is true. the minimum acceptable chance of making a type I error. O the probability that an event occurred as a result of a causative factor rather than by chance. the...
Which of the following statements about α level is true? a. As α level decreases, the critical F value will decrease as well. b. As α level decreases, the computed F value will increase. c. If α level is smaller than the p value, then the null hypothesis is rejected. d. α level describes the highest risk of Type I error we are willing to take.
A significance level for a hypothesis test is given as . Interpret this value. The probability of making a Type II error is .99. The smallest value of α that you can use and still reject H0 is .01. There is a 1% chance that the sample will be biased. The probability of making a Type I error is .01.
Which of the following is NOT true about the level of significance of a hypothesis test? The larger the significance, the higher the risk that we make an error The level of significance is the maximum risk we are willing to accept in making an error. The significance level is also called the α level The significance level is determined by your sample size
2. (2 True-False. Just say whether each statement is True or False – no need to justify your answer. 1. If the number of trials in the binomial distribution increases by 1 (and P equals .50), the probability of getting either of the most extreme possible outcomes (that is, 0 or N) is cut in half. 2. If the number of trials in the binomial distribution increases by 1 (and P does not equal .50), the probability of getting either of...