1. The more power in a study, the greater the chance of identifying a non-significant difference when there actually is a significant difference.  True

/in /by

QUESTION 1

1. The more power in a study, the greater the chance of identifying a non-significant difference when there actually is a significant difference.

True

False

QUESTION 2

1. Inferential statistics are about a population, so the hypotheses are created using parameter statistics.

True

 False

 

QUESTION 3

1. As probability of making a Type I error increases, the probability of making a Type II error also increases.

True

False

 

QUESTION 4

1. Studies that lack sufficient power are more likely to make a type I error.

True

False

 

QUESTION 5

1. Hypothesis testing in univariate statistics is used to determine whether or not any change in the dependent variable is due to change in the independent variable or simply due to chance.

True

False

 

QUESTION 6

1. For social sciences, power is usually deemed sufficient at .80.

True

False

 

QUESTION 7

1. The easiest method of increasing power in a study is to increase sample size.

True

False

 

QUESTION 8

1. If the null hypothesis is rejected, then no statistical group differences were found.

True

False

 

QUESTION 9

1. The level of significance in a study is directly related to the amount of type I error allowed in a study.

True

False

 

QUESTION 10

1. In hypothesis testing, the null hypothesis is always tested.

True

False

 

QUESTION 11

1. Power is the same as confidence.

True

False

 

QUESTION 12

1. Scores that are below the stated level of significance and critical value are considered to be statistically significant.

True

False

 

Click Save and Submit to save and submit. Click Save All Answers to save all answers.