Chapter 1 Notes on Variables, Reliability/Validity, Study Design, and Data Representation

Vocabulary flashcards covering key terms from the lecture notes.

Population

The entire group of interest in a study (e.g., all fifth graders in the United States).

Sample

A subset of the population used for data collection (e.g., two fifth-grade classes).

Independent variable

The variable that is manipulated or used to group participants (e.g., new teaching method vs traditional method).

Dependent variable

The outcome measured to assess the effect of the independent variable (e.g., scores on photosynthesis questions).

Confounding variable

A variable other than the independent variable that can affect the dependent variable and bias results (e.g., state differences, teacher skill, classroom environment).

Operational definition

A precise, measurable definition of a concept used in a study (e.g., mastery of photosynthesis defined as 5 out of 10 correct).

Reliability

The consistency or repeatability of a measurement across time or trials.

Validity

The extent to which a measurement actually measures what it is intended to measure.

Between-subjects design

An experimental design that compares outcomes across different groups receiving different treatments.

Within-subjects design

An experimental design where the same participants are measured under different conditions or over time (e.g., pretest/posttest).

Pretest/posttest

A within-subjects measurement approach where data are collected before and after an intervention.

Random sampling

Selecting participants from the population by chance to obtain a representative sample.

Random assignment

Assigning participants to different groups by chance to control for confounding variables.

Correlation

A statistical association between two variables; does not by itself imply causation.

Causation

A cause-and-effect relationship where one variable directly influences another.

Nominal variable

Categorical data without an inherent order (e.g., treatment vs control; group membership).

Interval variable

A scale with equal intervals between values but no true zero (e.g., temperature in Celsius).

Ratio variable

A scale with equal intervals and a true zero, allowing meaningful ratios (e.g., test scores, height).

Discrete variable

A variable that takes on a finite or countable number of values (e.g., scores 0–10).

Outlier

An extreme value that lies far from the rest of the data and can distort statistics like the mean.

Frequency distribution

The pattern of how often each value occurs in a dataset, often shown as a frequency table or chart.

Bar chart

A chart suitable for nominal or ordinal data to display frequencies.

Hypothesis testing

The process of evaluating whether observed data provide evidence against a null hypothesis.

Hypothesis

A testable statement about a relationship between variables (often predicts a difference or association).