Pysch Methods Exam 2

Linear relationships

In a graph showing the changing variables, a pattern in which the data points tend to cluster around a straight line

Experimental research strategy

A research strategy that attempts to establish the existence of a cause-and-effect relationship between two variables by manipulating one variable while manipulating one variable while measuring the second variable and controlling all other variables

External validity

The extent to which we can generalize the results of a research study to people, settings, times, measures, and characteristics other than those used in that study

Internal Validity

The extent to which a research study produces single, unambigious explanation for the relationship between two variables

Extraneous variable

Any variable that exists within a study other than the variables being studied. In an experiment, any variable other than the independent and dependent variables

Confounding variable

A extraneous variable (usually unmonitored) that is allowed to change systematically along with the two variables being studied. In the context of an experiment, an extraneous variable that changes systematically along with the independent variable and has the potential to influence the dependent variable.

Convenience Sampling

A nonprobability sampling method involving selection of individuals on the basis of their availability and willingness to respond; that is, because they are easy to get.

Debriefing

An explanation of the study or what the true purpose, usually if the study involved deception

Empiricism

Knowing through a different sensory observation, usually not a good science

Deductive reasoning

Drawing a conclusion intended to follow logically from a given set of premises, reasoning from general to specific

Validity

The ability of a test to measure what one thinks it is measuring

Reliability

The ability of a test to get the same result over and over again

Operational definition

Clearly defining every part of the hypothesis, words aren’t as important in this scenario (?)

Independent variable

The aspect of an experiment that the experimenter manipulates

Dependent variable

A variable that is measured, counted, or recorded by the investigator (outcome of the experiment)

Nominal

Categorical data where one counts every member in a group and names said group: different color of hair

Ordinal

Putting variables/data in order in some fashion: strongly disagree to strongly agree

Interval

Numbers with meaning- for example, 0 degrees C doesn’t mean a lack of temperature

Ratio

Numbers where 0 means a lack of something, for example, 0 cats

Range effects

Data should be nice and in the middle of a set in order to avoid floor and ceiling effects

Floor effect

A test is too hard and the tail of a study is steered to the right. example- test at school is too hard so everyone gets a 50 (hit the floor)

Ceiling effect

A test is much too easy and has an extreme left tail. for example- my students all get a 100 on a test

Quantitative research

Research with numbers that can be analyzed

Qualitative research

Non-number research, usually survey/interview based

Beneficence and non-malfeasance

Experiments must benefit people and not harm then

Convenience sampling

Taking whatever participants you can find without random sampling, often gives very skewed results, used the most due to ease

Purposive sampling

“snowball samples,” finding people who fit your criteria and then asking them to ask their friends to join your study

Quota samples

Seeking out people from different groups and then trying to get a certain number from each group (ex- getting 50 men and 50 women)

Sample/selection bias

When the participants in the study don’t look like the population one wants to generalize to, sampling doesn’t represent the population being generalized to

Compensatory Equalization

A threat to internal validity that occurs when an untreated group demands to receive a treatment that is the same as or equivalent to the treatment received by another group in the research study.

Diffusion

A threat to internal validity that occurs when a treatment effect spreads from the treatment group to the control group, usually from participants talking to each other.

Compensatory rivalry

A threat to internal validity that occurs when an untreated group learns about special treatment received by another group, then works extra hard to show they can perform just as well as that group.

Resentful demoralization

A threat to internal validity that occurs when an untreated group learns of special treatment given to another group, and becomes less productive and less motivated because they resent the other group’s expected superiority.

Differential attrition

A threat to internal validity that occurs when attrition in one group is systematically different from the attrition in another group.

Two Independent Samples t-test

To see if there is signifcant difference bewteen the mean of two unrelated groups

Paired Samples t-test

Comparing sampling distribution of the sample mean of the difference scores to the sampling

distribution of the hypothetical mean of the difference scores. SIMILAR GROUPS

Anova

Comparing groups, more than three with one independent variable and multiple dependent