Chapter 4

Question 1

Conceptual Hypothesis

Answer 1

State expected relationships among concepts.

Question 2

Research Hypothesis

Answer 2

Concepts are operationalized so that they are measurable.

Question 3

Statistical Hypotheses

Answer 3

State the expected relationship between or among summary values of populations, called parameters.
Null hypothesis (H0) 
Alternative hypothesis (H1)

Question 4

Null Hypothesis

Answer 4

The hypothesis being statistically tested when you use inferential statistics.
The researcher hopes to show that the null is not likely to be true (i.e., hopes to nullify it).

Question 5

Alternative Hypothesis

Answer 5

The hypothesis the researcher postulated at the outset of the study.
If the researcher can show that the null is not supported by the data, then he or she is able to accept the alternative hypothesis.

Question 6

Steps in Testing a Research Hypothesis

Answer 6

1. State the null and the alternative.
2. Collect the data and conduct the appropriate statistical analysis.
3. Reject the null and accept the alternative or fail to reject the null.
4. State your inferential conclusion.

Question 7

Statistical Difference

Answer 7

The probability that the groups are the same is very low.

Question 8

Significance levels (α)

Answer 8

Alpha (α) is the level of significance chosen by the researcher to evaluate the null hypothesis.
5% (p< .05) or 1% (p< .01)

Question 9

Type I Error

Answer 9

Rejecting a true null.

Probability is equal to alpha (α). ex: sending an innocent man to jail.

Question 10

Type II Error

Answer 10

Failing to reject a false null.

Probability is beta (β). ex: setting a guilty man free

Question 11

Power

Answer 11

our ability to reject false nulls. 1-Beta. Our ability to not make a Type II Error.

Question 12

Ways to Increase Power

Answer 12

Be careful about how you measure your variables.
Use more powerful statistical analyses.
Use designs that provide good control over extraneous variables.
Restrict your sample to a specific group of individuals.
Increase your sample size  reduces variance due to sampling error.
Maximize treatment manipulation.

Question 13

Effect Size

Answer 13

a measure of the strength of the relationship between/among variables.Helps us determine if differences are not only statistically significant, but also whether they are important.

Question 14

Ways to Calculate Effect Size

Answer 14

Cohen’s d – use with t-tests.
Coefficient of determination (r2) – use with correlations.
eta-squared (η2) – use with ANOVAs.
Cramer’s v – use with Chi-square analyses.

Question 15

External Validity

Answer 15

When the findings of a study can be generalized to other populations and settings.

Question 16

Internal Validity

Answer 16

Refers to the validity of the measures within the study.

The internal validity of an experiment is directly related to the researcher’s control of extraneous variables.

Question 17

Extraneous Variable

Answer 17

A variable that may affect the outcome of a study but was not manipulated by the researcher.

Question 18

Confounding Variable

Answer 18

A variable that is systematically related to the independent and dependent variable. It offers an alternative explanation for the outcome.

Question 19

Spurious Effect

Answer 19

An outcome that was influenced not by the independent variable itself but rather by a variable that was confounded with the independent variable.

Question 20

Controlled Variable

Answer 20

A variable that the researcher takes into account when designing the research study or experiment.

Question 21

Nuisance Variable

Answer 21

Variables that contribute variance to our dependent measures and cloud the results.

Question 22

Elimination

Answer 22

Get rid of the extraneous variables completely (e.g., by conducting research in a lab).

Question 23

Constancy

Answer 23

Keep the various parts of the experiment constant (e.g., instructions, measuring instruments, questions).

Question 24

Secondary Variable as an IV

Answer 24

Make variables other than the primary IV secondary variables to study (e.g., gender).

Question 25

Randomization: Random Assignment of Particpants to Groups

Answer 25

Randomly assigning participants to each of the treatment conditions so that we can assume the groups are initially equivalent.

Question 26

Repeated Measures

Answer 26

Use the same participants in all conditions.

Question 27

Statistical Control

Answer 27

Treat the extraneous variable as a covariate and use statistical procedures to remove it from the analysis.