Psychology Research Methods 270

Front 1

Attrition/Mortality

Back 1

The term for the fact that participants may drop out of a study.

Front 2

Positive Correlation

Back 2

When one variable increases or decreases, another variable increases or decreases as well.

Front 3

Minimal Risk Research

Back 3

Research involving risks that the participants may experience in everyday life.

Front 4

Frequency Distribution

Back 4

A list that records the number of individuals who received each of the possible scores for a variable.

Front 5

Pie Chart/Bar graph

Back 5

The only graphic technique that makes sense for nominal data.

Front 6

Mean

Back 6

The sum of all the scores, divided by the number of scores.

Front 7

Median

Back 7

The score that divides the group in half.

Front 8

Mode

Back 8

The most frequent score. Also the only measure of central tendency that works for nominal data.

Front 9

Standard Deviation

Back 9

How far away, on average, each score is from the mean.

Front 10

Effect Size

Back 10

Strength of association between variables (how much of an effect the independent variable had on the dependent variable.)

Front 11

Regression Equation

Back 11

Calculations used to predict a person's score on one variable when that person's score on another variable is already known.

Front 12

Null hypothesis

Back 12

There is no difference between group means.

Front 13

Research hypothesis

Back 13

There IS a difference between group means.

Front 14

Alpha level

Back 14

Probability that the difference between group means is due to chance.

Front 15

One-tailed test

Back 15

There is a specified direction of difference between the groups.

Front 16

Confidence interval

Back 16

An interval of values defines the most likely range of actual population values.

Front 17

Type I error

Back 17

the null hypothesis is rejected but is actually true

Front 18

type II error

Back 18

we fail to reject the null hypothesis, despite the fact that the research hypothesis is true

Front 19

risk-benefit analysis

Back 19

weighing the risks against the benefits of a research study to ensure that the benefits outweigh the risks

Front 20

demand characteristics

Back 20

the fact that participants may guess the purpose of a study and change their behavior accordingly

Front 21

factorial design

Back 21

experimental design with more than one independent variable

Front 22

regression towards the mean

Back 22

the fact that outlier scores tend to end up closer to the mean when tested again

Front 23

Independent groups design

Back 23

each participant participates in only one group

Front 24

repeated measures design

Back 24

each participant participates in every level of the independent variable

Front 25

Double-barreled question

Back 25

a question with two parts in survey research

Front 26

loaded question

Back 26

a question that persuades participants into answering it in a certain way

Front 27

placebo effect

Back 27

the effect of the independent variable is due to the participant's expectations

Front 28

Internal validity

Back 28

the independent variable caused the change in the dependent variable

Front 29

external validity

Back 29

the results of a study can be generalized to the population of interest

Front 30

confound variable

Back 30

a variable that is systematically linked to the independent variable and has an effect on the dependent variable

Front 31

Empiricism

Back 31

the idea that knowledge is based on observations

Front 32

negative correlation

Back 32

as one variable increases, the other decreases or vice versa

Front 33

case study

Back 33

the in depth examination of one or a few individuals

Front 34

systematic observation

Back 34

naturalistic observation, but the variables of interest are already known and will be recorded

Front 35

participant observation

Back 35

A subtype of naturalistic observation, involving the participation of the experimenter

Front 36

reactivity

Back 36

one of the problems of naturalistic observation is that people may behave differently while being observed. This is called:

Front 37

Third variable problem

Back 37

one of the problems inherent in correlational research is that another variable may be responsible for the relationship between two variables of interest

Front 38

ratio scale

Back 38

this scale has an absolute zero

Front 39

interval scale

Back 39

this scale does not have an absolute zero, however, the mean can be calculated with this scale

Front 40

range

Back 40

this value is calculated by subtracting the lowest score from the highest score