Rsearch methods Final flashcards

Producers of research

People who conduct studies, collect data, analyze results, and create new scientific knowledge.

Consumers of research

People who read, interpret, evaluate, and apply research findings, even if they do not conduct studies themselves.

Why are producers of research important?

They generate new knowledge, test theories, solve problems, and expand what we know scientifically.

Why are consumers of research important?

They use research to make informed decisions, evaluate claims, apply evidence in real-world settings, and avoid being misled by weak or false claims.

Empiricism

The approach of using systematic observation, measurement, and evidence to understand the world.

Why is empiricism important in research?

It bases conclusions on evidence rather than intuition, opinion, or anecdote.

Theory-data cycle

The scientific process in which theories lead to hypotheses, hypotheses are tested with data, and the data support, change, or refine the theory.

Theory

A broad explanation or set of principles that organizes observations and predicts outcomes.

Hypothesis

A specific, testable prediction derived from a theory.

Role of data in the theory-data cycle

Data provide evidence that supports, weakens, or refines hypotheses and theories.

Basic research

Research conducted to enhance general knowledge and understand fundamental principles, without an immediate practical goal.

Example of basic research

A study examining how memory works in the brain.

Applied research

Research conducted to solve a specific, practical problem.

Example of applied research

Testing whether a new therapy reduces anxiety in college students.

Translational research

Research that uses knowledge from basic research to develop practical applications.

Example of translational research

Using discoveries about brain functioning to design treatments for depression.

Main goal of basic research

To understand and explain behavior or mental processes.

Main goal of applied research

To address a real-world issue directly.

Main goal of translational research

To bridge the gap between basic science and practical use.

How is research different from personal experience?

Research uses systematic methods and often comparison groups, while personal experience is unsystematic and usually lacks a comparison group.

Why is experience weaker than research as evidence?

Experience is limited, biased, and usually does not allow us to compare outcomes systematically.

How is research different from intuition?

Research is based on evidence and systematic testing; intuition is based on gut feeling or immediate judgment.

Being swayed by a good story

Believing a claim because it is vivid, compelling, or memorable, even if evidence is weak.

Availability heuristic

The tendency to judge how common or likely something is based on how easily examples come to mind.

Why can the availability heuristic be misleading?

Memorable events are not always the most common or accurate representation of reality.

Confirmation bias

The tendency to notice, seek, and remember evidence that supports what we already believe, while ignoring contradictory evidence.

Bias blind spot

The tendency to think other people are biased while believing we ourselves are objective.

Why is research better than intuition?

Research uses structured methods to reduce bias and test ideas objectively.

Empirical journal article

A scholarly report of a research study that includes the study’s question, methods, results, and conclusions.

Purpose of the abstract

Gives a brief summary of the study’s question, methods, results, and conclusions.

Purpose of the introduction

Explains the background, theory, previous research, and the study’s hypotheses.

Purpose of the method section

Describes how the study was conducted, including participants, measures, and procedures.

Purpose of the results section

Presents the statistical analyses and findings of the study.

Purpose of the discussion section

Interprets the results, explains implications, notes limitations, and suggests future directions.

Purpose of the references section

Lists the sources cited in the article.

Reading with a purpose

Actively identifying the study’s argument, evidence, methods, and conclusions instead of reading passively.

Argument in a research article

The main claim or conclusion the authors are making.

Supportive evidence in a research article

The data, methods, and results that back up the authors’ argument.

Variable

Something that can vary or take on different values.

Constant

Something that does not vary in a study.

Manipulated variable

A variable the researcher controls or changes.

Measured variable

A variable the researcher observes and records without changing it.

Conceptual definition

The abstract, general meaning of a variable.

Operational definition

The specific way a variable is measured or manipulated in a study.

Example of a conceptual definition of stress

Stress as a psychological state involving pressure or tension.

Example of an operational definition of stress

Score on a stress questionnaire or cortisol level.

Frequency claim

A claim that describes the rate or level of a single variable.

Example of a frequency claim

Thirty percent of students experience test anxiety.

Association claim

A claim stating that two variables are related.

Positive association

As one variable increases, the other also increases.

Example of a positive association

More study time is associated with higher exam scores.

Negative association

As one variable increases, the other decreases.

Example of a negative association

More stress is associated with lower sleep quality.

Zero association

There is no relationship between the two variables.

How can association claims be used for prediction?

If two variables are related, knowing one variable may help predict the other.

Causal claim

A claim stating that one variable causes a change in another.

Four validities

Construct validity, external validity, statistical validity, and internal validity.

Construct validity

How well a study’s variables are measured or manipulated.

External validity

The extent to which the findings generalize to other people, settings, or times.

Statistical validity

The extent to which the statistical conclusions are accurate and reasonable.

Internal validity

The extent to which a study supports a cause-and-effect conclusion.

Which validities are most important for frequency claims?

Construct validity and external validity.

Why does a frequency claim need construct validity?

Because the variable must be measured well.

Why does a frequency claim need external validity?

Because the estimate must generalize to a broader population.

Which validities are most important for association claims?

Construct validity, external validity, and statistical validity.

Which validities are most important for causal claims?

All four, especially internal validity.

Null hypothesis

The idea that there is no effect or no relationship.

Alternative hypothesis

The idea that there is an effect or a relationship.

Type I error

Concluding there is an effect when there really is not one; a false positive.

Type II error

Concluding there is no effect when there really is one; a false negative.

Three criteria for a causal claim

Covariation, temporal sequence, and ruling out third variables.

Covariation

The two variables must be related.

Temporal sequence

The cause must come before the effect.

Third variables or confounds

Other variables that could explain the relationship between the two main variables.

Three main types of measurement

Behavioral, physiological, and self-report.

Behavioral measure

A measure based on observing actions or behaviors.

Example of a behavioral measure

Number of times a person checks their phone.

Physiological measure

A measure based on biological or bodily data.

Example of a physiological measure

Heart rate, blood pressure, or cortisol level.

Self-report measure

A measure in which people answer questions about themselves.

Example of a self-report measure

A depression inventory or survey.

Converging measures

Using multiple kinds of measures to assess the same construct.

Why use converging measures?

They strengthen confidence that the construct is being captured accurately.

Reliability

The consistency or stability of a measure.

Test-retest reliability

The consistency of scores when the same people take the same measure at two different times.

How is test-retest reliability evaluated?

By correlating Time 1 scores with Time 2 scores.

What does a reliability coefficient around .70 suggest?

Generally acceptable reliability.

How can a scatterplot help evaluate test-retest reliability?

If the points cluster around a line, scores are consistent across time.

Internal consistency reliability

The extent to which items on a measure are consistent with one another.

What does high internal consistency mean?

The items are all measuring the same general construct.

Validity in measurement

The extent to which a measure actually measures what it claims to measure.

Face validity

Whether a measure appears, on the surface, to assess what it is supposed to assess.

Content validity

Whether a measure covers all important parts of the construct.

Which kinds of measures are often evaluated with face and content validity?

Subjective measures, especially self-report scales.

Difference between content validity and internal consistency

Content validity asks whether the measure covers the full construct; internal consistency asks whether the items hang together statistically.

Why might a measure have strong internal consistency but poor content validity?

Because all items may be similar but may fail to cover the whole construct.

Convergent validity

When a measure correlates with other measures of the same or similar construct.

Discriminant or divergent validity

When a measure does not correlate strongly with measures of different constructs.

Why are convergent and divergent validity considered empirical?

Because they are tested using actual data and relationships among measures.

Random sampling

Selecting participants so every member of the population has an equal or known chance of being chosen.