Lecture Notes on Sampling, Variables, and Experimental Design

Vocabulary flashcards covering key concepts from the notes on sampling, variables, and experimental design.

Categorical variable

A variable that sorts individuals into categories or groups (qualitative), not measured on a numerical scale.

Quantitative variable

A variable that assigns numerical values to observations (measurable on a numeric scale, e.g., age, height).

Dependent variable (response variable)

The outcome that is measured to assess the effect of the independent variable.

Independent variable (explanatory/treatment variable)

The variable that is deliberately manipulated or varied to observe its effect on the dependent variable.

Experimental study

A study in which treatments are imposed to observe causal effects; IVs are manipulated and causal conclusions are possible.

Observational study

A study where no treatment is applied; researchers simply observe and measure existing conditions.

Population

The entire group about which we want information.

Sample

A subset of the population selected for study.

Census

Surveying the entire population.

Representative sample

A sample that accurately reflects the characteristics of the population.

Biased sample

A sample that does not adequately represent the population, leading to distorted results.

Sampling frame

A list or source from which a sample is drawn.

Simple random sample (SRS)

A sampling method where every member of the population has an equal chance of being selected.

Voluntary response sample

A sample formed by individuals who choose to participate, often leading to bias.

Parameter

A numerical summary of a population (e.g., population mean μ, population proportion p).

Statistic

A numerical summary of a sample (e.g., sample mean x̄, sample proportion p̂).

Bias

A systematic distortion that favors a particular outcome or characteristic.

Variability

The spread or dispersion of data; higher variability means less precise estimates.

Margin of error (MOE)

The range around a sample estimate that reflects sampling variability; smaller MOE with larger samples.

Confidence level

The probability that a confidence interval contains the true parameter (commonly 95%).

Confidence interval

A range of values within which the parameter is expected to lie with a stated level of confidence.

Non-sampling errors

Errors not due to the act of sampling (e.g., measurement error, nonresponse, data processing).

Undercoverage

When some groups in the population are inadequately represented in the sampling frame.

Stratified random sampling

Divide population into strata (groups) with similar characteristics, then take SRS from each stratum.

Probability sample

A sample where inclusion probabilities are known and nonzero (e.g., SRS, stratified).

Non-probability sample

A sample where inclusion probabilities are unknown (e.g., voluntary response, convenience).

Explanatory variable

Another term for the independent variable; explains the change in the response variable.

Confounding variable

A variable that influences both the independent and dependent variables, potentially biasing results.

Placebo

A dummy treatment used as a control in experiments to account for expectation effects.

Double blind

Neither participants nor researchers know which treatment any participant receives, to reduce bias.

Randomized comparative experiment

An experiment that randomly assigns participants to different treatments to compare outcomes.

Control group

The group that does not receive the active treatment or receives a placebo for comparison.

Matched pairs design

Divide subjects into similar pairs and randomly assign treatments within each pair.

Block design

Group subjects into blocks of similar characteristics and randomly assign treatments within blocks.

External validity

The extent to which study results generalize to the population beyond the sample.

Internal validity

The extent to which a study convincingly demonstrates a cause-and-effect relationship within the study.

Validity

The degree to which a measurement actually measures what it intends to measure.

Reliability

The consistency of a measurement or measurement system across repeated trials.

Mean (x̄)

The average value of a sample; a measure of central tendency.

Measurement error

Discrepancy between the observed value and the true value due to imperfect measurement.

Nonresponse

A type of non-sampling error where selected individuals do not participate or respond.

Random error

Variability in measurements due to unpredictable factors; reduces precision.

Hidden agenda / plausibility concerns

Beware authors’ potential bias or manipulation of numbers to influence interpretation.