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Theory
An organized set of principles used to explain observed phenomena

Construct
An abstract concept that one would like to measure (e.g., love, intelligence, aggression)

Hypothesis
A testable prediction about the association between two or more variables.

Operational definition
The specific procedures for manipulating or measuring a construct.

Construct validity
The degree to which the independent variable and/or dependent variable accurately reflect or measure the constructs of interest.

Population
All possible individuals making up a group of interest in a study (e.g., all U.S. women over 18 years old).

Sample
A relatively small number of individuals drawn from a population for inclusion in a study. Ideally, you should create a random sample (i.e., each potential participant has an equal chance of being selected). Moreover, your sample should be representative of the population of interest. A representative sample closely matches the characteristics of the population.

Methods to test ideas:
 1. Observation: Involves observing people in social situations. Though it is timeconsuming, it is a great way to see what is going on in natural setting. It provides a better understanding of the context the study participants are currently in and it can help you to come up with a new perspective to look at the question at hand.
 2. Archival research: Using the existing records as your basic source for data. It is purely descriptive, but it helps you to identify interesting correlations and trends. (No causal relationship)
 3. Surveys: Asking participants questions either by interviewing them or giving them written questions. A really important concept here is random sampling. In a random sample, every person in the population must have an equal chance of being chosen in the study. This is usually the problem with surveys you see in the magazines. Random sampling is especially necessary when you want to apply your findings directly to a population (e.g. political polls).
 4. Experiments: Method in which one or more factors are manipulated to observe the effect on some behavior or mental process. Unlike other methods, experiments can be used to establish causality.

Correlational relationship
A relationship in which the value of one variable changes systematically with the value of a second variable (does NOT show causality!). Correlation coefficient is always between 1 and 1.

Zero correlation
A correlation coefficient of 0 means there is no relationship between the two variables.

Negative correlation
A negative coefficient indicates a negative relationship between the two variables, meaning that when the value of one variable is increasing, the value of the other variable is decreasing.

Positive correlation
A positive coefficient indicates a positive relationship between the two variables meaning that when the value of one variable is increasing/decreasing, the value of the other variable is moving in the same direction.

Experimental research
Research in which independent variables are manipulated and behavior is measured while extraneous variables are controlled (shows causality).

Causal relationship
A relationship in which changes in the value of one variable cause changes in the value of another.

Independent variable
The variable that is manipulated in an experiment. Its value is determined by the experimenter, not the participant.

Dependent variable
The variable measured in a study. In an experiment, its value is said to “depend” on the value of the independent variable.

Control condition
A conditions comparable to the experimental condition in every way except that it lacks the one ingredient hypothesized to produce the expected effect on the dependent variable.

Confounding variable
An uncontrolledfor variable that varies systematically with the independent variable. The presence of confounds makes it hard to be confident that the manipulation was the true cause of the difference between groups.

Random assignment
The process of assigning subjects to different conditions randomly, such that they are as likely to be assigned to one condition as to another. It eliminates the influence of confounding variables.

Validity
The extent to which a measuring instrument measures what it was designed to measure.

Internal validity
Concerns the extent to which conclusions can be drawn about the causal effects of one variable on another.

External validity
The extent to which the results of a study extend beyond the limited sample used in the study.

Reliability
Whether a measure or questionnaire produces the same or similar responses with multiple administrations of the same or similar instrument.

Normal distribution
A specific type of frequency distribution in which most scores fall around the middle category. Scores become less frequent as you move from the middle category.

Mean
The arithmetic average of the scores in a distribution. The most frequently reported measure of center. Other measures are median and mode. Median is the middle score in an ordered distribution. Mode is the most frequent score in a distribution.

Variance
a measure of how much variability there is in the sample. It shows how much variation there is from the average.

Standard deviation
The most frequently reported measure of spread. It is closely related to variance (Variance = SD2).

ttest
A statistical test that assesses whether the means of two groups are statistically different from each other.

ANOVA (analysis of variance)
Another statistical test that assesses whether or not the means of several groups are equal. ANOVAs are useful in comparing two or more means and/or examining interaction effects between several independent variables.

Oneway ANOVA
Used to test for differences between two or more groups

Factorial ANOVA
Used to assess interaction effects in experiments with more than one independent variable

Main effect
The effect of an independent variable on the dependent variable. There is one main effect for every independent variable in the study.

Interaction effect
Occurs when the effect of one independent variable on the dependent variable differs depending on the level of another independent variable.

Statistical significance
A result is said to be statistically significant if it is unlikely to have occurred by chance. In statistics, “significant” does not mean important or meaningful.

pvalue
The probability in a statistical test that your results happened by chance. It should be less than or equal to the chosen alpha level (usually .05) for the result to be statistically significant.
 Institutional Review Board (IRB)
 A committee that screens proposals for research using human participants for adherence to ethical standards.

Informed consent
Agreeing to serve as a research participant after being informed about the nature of the research and the participants’ rights and responsibilities. The participant typically reads and signs a form specifying the purpose of a study, the methods to be used, requirements for participation, that participation is voluntary, and that the participant is free to withdraw from the study at any time without penalty.

Debriefing
A session conducted after an experimental session in which participants are informed of the purposes of the study, any deception used and the reasons for the deception, the methods used in the study and any results available.

Deception
A research technique in which participants are misinformed about the true nature and purpose of the study (Remember Milgram’s experiment. No real electric shocks were given but the participants did not know that.) It is ethical only if its use can be justified.

