Question 1

In the context of NHST, what is the purpose of a t-test?

Accepted Answer

To determine if there is a significant difference between the means of two groups

Answer

To find the correlation between two variables

Answer

To measure the central tendency of a dataset

Answer

To calculate the probability of a Type II error

Question 2

What is the typical significance level (alpha) used in a t-test to determine statistical significance?

Accepted Answer

0.05

Answer

0.01

Answer

0.50

Answer

0.10

Question 3

What does a high p-value indicate in the context of a t-test?

Accepted Answer

The data does not provide sufficient evidence to reject the null hypothesis

Answer

The sample size is too small

Answer

The data is skewed

Answer

There is a significant difference between group means

Question 4

What does the term 'degrees of freedom' refer to in the context of a t-test?

Accepted Answer

The number of independent values that can vary given a set of parameters

Answer

The critical value needed to reject the null hypothesis

Answer

The difference between the sample mean and the population mean

Answer

The total number of observations in the dataset

Question 5

In a one-sample t-test, what is being compared?

Accepted Answer

The sample mean to a known population mean

Answer

The sample variance to a known population variance

Answer

The sample mean to the median of the sample

Answer

Two different sample means

Question 6

Which of the following best describes the Type I error in hypothesis testing?

Accepted Answer

Rejecting the null hypothesis when it is actually true

Answer

Rejecting the alternative hypothesis when it is actually true

Answer

Failing to reject the alternative hypothesis when it is actually false

Answer

Failing to reject the null hypothesis when it is actually false

Question 7

What is the main consequence of setting a very low alpha level (e.g., 0.01) in hypothesis testing?

Accepted Answer

It reduces the likelihood of making a Type 1 error, but increases the chance of a Type 2 error.

Answer

It has no effect on Type 2 errors.

Answer

It guarantees statistical significance.

Answer

It increases the chance of making a Type 1 error.

Question 8

Which of the following statements is true regarding one-tailed versus two-tailed tests?

Accepted Answer

A one-tailed test has more statistical power to detect an effect in one direction.

Answer

A two-tailed test is only appropriate for larger sample sizes.

Answer

Two-tailed tests always require less stringent alpha levels.

Answer

One-tailed tests can detect effects in both directions.

Question 9

In a study, if researchers set an alpha level of 0.05, what does this imply about their willingness to accept Type 1 errors?

Accepted Answer

They are willing to accept a 5% chance of incorrectly rejecting a true null hypothesis.

Answer

They will accept a 10% chance of making a Type 2 error.

Answer

They are aiming for a 95% chance of detecting true effects.

Answer

They guarantee that their findings are significant at all times.

Question 10

If the correlation coefficient between two variables is 0.8, how would you interpret the strength and direction of this relationship?

Accepted Answer

Strong positive relationship

Answer

Strong negative relationship

Answer

No relationship

Answer

Weak positive relationship

Question 11

What range of values can the correlation coefficient (r) take?

Accepted Answer

Between -1 and 1

Answer

Any real number

Answer

Between -10 and 10

Answer

Between 0 and 1

Question 12

What does an effect size of 0.5 typically indicate in the context of Cohen's d?

Accepted Answer

A medium effect size

Answer

A large effect size

Answer

A small effect size

Answer

No effect at all

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