Stat Psy Test 2

Front 1

The criteria for a decision regarding the value stated in a null hypothesis is set by the

Back 1

Level of significance

Front 2

In hypothesis testing, a researcher can never

Back 2

Prove that his or her hypothesis is correct.

Front 3

In step two of hypothesis testing, researchers state a level of significance to minimize the probability of

Back 3

Rejecting a true null hypothesis

Front 4

The power of the decision making process is

Back 4

The likelihood of rejecting a false null hypothesis.

Front 5

A researcher reports that the size of an affect in some population is D equals 0.88. Which of the following is an appropriate interpretation for D?

Back 5

Mean scores shifted .88 standard deviation’s in the population.

Front 6

Increasing sample size will

Back 6

Increase the power of the decision

Front 7

What are the degrees of freedom for the related samples t-test?

Back 7

(Nd-1)

Front 8

Hypothesis testing is also called

Back 8

Significance testing

Front 9

In hypothesis testing, researchers decision

Back 9

Is based on the probability, depends on the level of significance for a hypothesis test, can be retained or reject the null hypothesis (all the above)

Front 10

__________ Allows researchers to describe how far mean scores have shifted in the population or, the percentage of variance that can be explained by a given variable

Back 10

Effect size

Front 11

The t distribution is similar to the Z distribution, except

Back 11

It is associated with greater variability, it is characterized by thicker tails compared with the Z distribution, it is associated with scores being more likely in the tales of the distribution. (All of the above)

Front 12

The t distribution is similar to the Z distribution, except

Back 12

It is associated with greater variability, it is characterized by thicker tails compared with the Z distribution, it is associated with scores being more likely in the tales of the distribution. (All of the above)

Front 13

A key difference between a T statistic and a Z statistic is that the standard error is ________ to compute a T statistic.

Back 13

Estimated

Front 14

As a requirement for the t-test, researchers compute any type of t-test with sample selected from the populations in which

Back 14

The population variance is unknown

Front 15

To compute a one sample t-test, a researcher has to know many values. Which of the following is not a value that the researcher must know to compute this test?

Back 15

The population variance

Front 16

A researcher asks a sample of brothers and sisters to write how positive their family environment was during childhood. In this study, the differences and ratings between each brother and sister pair were compared. The type of design described here is called a

Back 16

Matched sample design

Front 17

Which of the following is the denominator for the test statistic for the related samples t-test

Back 17

Estimated standard error for difference scores

Front 18

Regardless of the distribution of scores in a population, the sampling distribution of sample means selected at random from the population will approach the shape of a normal distribution

Back 18

Central limit theorem

Front 19

As population increases,

Back 19

Standard error decreases

Front 20

Set of principles which explain observations and from which predictions can be made

Back 20

Theory

Front 21

Set of principles which explain observations and from which predictions can be made

Back 21

Theory

Front 22

Specific, testable predictions which follow from a theory

Back 22

Hypothesis

Front 23

The default assumption is that our experimental hypothesis is false, and this opposite of our experimental hypothesis is called the

Back 23

Null hypothesis

Front 24

The distribution of scores we expect under the no hypothesis is the

Back 24

Comparison distribution

Front 25

Wrongly rejecting the null hypothesis is called a

Back 25

Type one error

Front 26

Our willingness to commit a type one error in hypothesis testing is called the

Back 26

Level of significance or type one error rate

Front 27

What is the power in hypothesis testing

Back 27

The likelihood of detecting an effect

Front 28

The probability of retaining a null hypothesis that is actually false

Back 28

Type two error

Front 29

How are the rejection regions, the probability of a type one error, the level of significance, and the alpha level related

Back 29

They are all the same thing

Front 30

What three factors can be decreased to increase power

Back 30

Population standard deviation, beta error, and standard error