Psych 209 Exam 3

Linear relationship

Variables change together in a straight-line pattern.

Monotonic relationship

Variables move in the same direction, but not necessarily in a straight line.

Curvilinear relationship

The relationship changes direction or strength across values

Comparing multiple groups (3+ levels)

Examining differences among three or more groups or conditions.

Factorial Design

An experiment with two or more independent variables (factors).

2 × 2 Design

Two independent variables, each with two levels.

2 × 3 Design

Two independent variables; one has 2 levels and one has 3 levels.

Main effect

The direct effect of an independent variable on a dependent variable

Interaction

When the effect of one independent variable depends on the level of another independent variable.

Independent Groups Design

Requires the largest number of participants, as a different set of individuals is assigned to each condition

Repeated Measures Design

Requires the fewest participants, as the same individuals take part in all conditions

Mixed Factorial Design

Includes both independent groups (between-subjects) and repeated measures (within-subjects) variables

Single-Case Experimental Design (Single-Subject/Small-N Design)

A study that focuses on one participant or a small number of participants.

Baseline Period

A period where behavior is measured before treatment begins.

Reversal design

A single case design in which the treatment is introduced after a baseline period and then withdrawn during a second baseline period

ABA Design

Baseline → Treatment → Remove treatment.

ABAB Design

Baseline → Treatment → Remove treatment → Reintroduce treatment.

Multiple Baseline Design

Treatment is introduced at different times across people, behaviors, or settings.

Replication

Repeating a study or effect to see if results occur again.

Quasi-Experimental Design

A study that lacks random assignment.

One-Group Posttest-Only Design

One group is measured after a treatment.

One-Group Pretest-Posttest Design

One group is measured before and after a treatment.

History Effect

Outside events affect participants during the study.

Maturation Effect

Natural changes in participants occur over time.

Testing Effect

Taking a test once affects later performance.

Instrument Decay

Measuring tools or observers become less accurate over time.

Regression Toward the Mean

Extreme scores tend to move closer to the average on later testing.

Nonequivalent Control Group Design

Experimental and control groups exist, but participants are not randomly assigned.

Nonequivalent Control Group Pretest-Posttest Design

Both groups are measured before and after treatment.

Nominal Scale

Categories with no order (e.g., eye color).

Ordinal Scale

Categories with a meaningful order but unequal spacing (e.g., class rank).

Interval Scale

Equal intervals, but no true zero (e.g., temperature in Celsius).

Ratio Scale

Equal intervals and a true zero (e.g., height, weight).

Comparing Group Percentages

Comparing the proportion of people in different categories.

Correlating Scores

Examining how two variables are related.

Comparing Group Means

Comparing average scores between groups.

Frequency Distribution

A summary showing how often scores occur.

Pie Chart

Displays percentages as slices of a circle.

Bar Graph

Uses bars to compare categories.

Frequency Polygon

A line graph showing frequencies.

Histogram

A graph using connected bars to show score frequencies.

Central Tendency

The center or typical score in a distribution.

Mean

The average score.

Median

The middle score when ordered.

Mode

The most common score.

Variability

How spread out scores are.

Range

Highest score minus lowest score.

Variance

Average squared distance from the mean.

Standard Deviation

Average distance of scores from the mean.

Correlation Coefficient

A number showing the strength and direction of a relationship.

Pearson Product-Moment Correlation Coefficient (r)

The most common measure of correlation, ranging from -1 to +1.

Restriction of Range

Reduced variability that weakens a correlation.

Effect Size

The magnitude or strength of a relationship or difference.

Regression Equation

A formula used to predict one variable from another.

Criterion Variable

The outcome being predicted.

Predictor Variable

The variable used to make predictions.

Multiple Correlation

Relationship between one outcome and multiple predictors.

Multiple Regression

Using multiple predictors to predict one outcome.

Multiple Regression Equation

Mathematical formula used in multiple regression.

Mediation Model

Explains how or why two variables are related.

Mediating Variable

The variable that explains the relationship.

Moderating Variable

A variable that changes the strength or direction of a relationship.

Third Variable

An outside variable influencing two other variables.

Structural Equation Modeling (SEM)

Advanced statistical technique that tests complex relationships among variables.

Population

The entire group of interest.

Sample

A smaller group selected from a population.

Inferential Statistics

Statistics used to draw conclusions about populations from samples.

Null Hypothesis (H₀)

Assumes no effect or relationship exists.

Research Hypothesis (H₁)

Predicts an effect or relationship exists.

Statistical Significance

Results are unlikely to have occurred by chance.

Probability

The likelihood that something will occur.

Statistical Inference

Using sample data to make conclusions about a population.

Alpha Level (α)

The probability required for significance usually .05 or 5%

Sampling Distribution

Distribution of all possible sample statistics.

Sample Size

Number of participants in a sample.

t Test

Tests whether two group means differ significantly.

Finding a t Value

Difference between group means divided by variability/error.

One-Tailed Test

Predicts a difference in a specific direction.

Two-Tailed Test

Predicts a difference but not the direction.

Degrees of Freedom (df)

Number of values free to vary in a calculation.

Analysis of Variance (ANOVA)

Tests differences among three or more group means.

F Test

The test statistic used in ANOVA.

Systematic Variance

Variance caused by the independent variable.

Error Variance

Variance caused by random factors.

Confidence Interval

Range of values likely containing the true population value.

Type I Error

Rejecting a true null hypothesis (false positive).

Type II Error

Failing to reject a false null hypothesis (false negative).

Decision Matrix

Table showing correct decisions and Type I/II errors.

Power

Probability of correctly detecting a real effect.