Scientific Reasoning & Research Ethics
Variables & Statistics
Measuring & Manipulating Variables
Descriptive & Correlational Methods
Experimental Methods
100

This explanation of a research study must be provided to participants in written format before they begin the study, and they must sign it to indicate that they agree to participate.

Informed Consent

100

This kind of variable is manipulated and is the hypothesized cause in an experiment.

Independent Variable

100

When participants complete Likert scales about their own thoughts/feelings, this measurement method is being used.

Self-report

100

A Pearson correlation of = 0.2 indicates a relationship of this strength and direction.

Small positive

100

This type of between-subjects design occurs when the dependent variable is measured twice, once before and once after the manipulation of the independent variable.

Pretest-Posttest

200

This type of validity increases when alternative explanations for the results, or confounds, are ruled out.

Internal Validity

200

"Failing at impossible anagrams will lead to participants reporting greater stress" is an example of this type of claim.

Causal Claim

200

"Recall a Time When..." and "Hypothetical Situations" are two examples of this type of manipulation.

Thought Exercises

200

When a company asks you to rate their service on a scale of 1-5, they are using this kind of descriptive method.

Descriptive Survey

200

This type of variability is present in an experiment when the two groups differ in some way other than the independent variable manipulation.

Systematic Variability

300

This way of knowing involves using logic.

Rationalism

300

In contrast to a conceptual variable, this is the way that a variable is measured or manipulated in an actual study, such as "happiness rating on a scale of 1-10."

Operational Definition

300

If you know a measure is valid, then you also know that it is this measure of consistency.

Reliable

300

This type of descriptive method has very high external validity because it takes place in the participants' natural environment.

Naturalistic Observation

300

This disadvantage of repeated measures designs occurs when one condition contaminates the next condition, like the leftover taste of toothpaste affecting the taste of orange juice.

Carryover Effect

400

This type of research question aims to enhance the general body of knowledge about a particular topic.

Basic research questions

400

This measure of variability in the data is used for the error bars on APA-style figures.

Standard Error

400

Inability to directly see internal mental processes, difficult operationalization for complex constructs, and viewer bias or error are all disadvantages of this measurement method.

Behavioral Observation

400

This type of hypothesis specifies the direction of a relationship using words like "more" or "greater."

One-tailed hypothesis

400

Imperfect distribution of participant characteristics through random assignment results in this disadvantage of between-subjects designs.

Nonequivalent Groups Problem

500

This Belmont Report principle refers to the idea that the same people who face the risks of research participation should also benefit from that research.

Justice

500

This statistical analysis should be used for a within-subjects design with two conditions.

Dependent samples t-test

500

This type of measurement validity means that the measure correlates more strongly with measures of related constructs.

Convergent Validity

500

This disadvantage of correlational designs occurs when some other unidentified variable causes both of the measured variables.

Third Variable Problem

500

Participants' preference between the conditions is always the dependent variable in this type of design.

Concurrent Measures