HLSC / PSYC 3450 - Variables, Sampling, and SPSS (Vocabulary Flashcards)

Variable

Anything that can take on different values; the basic object researchers study and that may vary or change. ex heart rate, BP, age

Operational Definition / Operationalization

Process of defining how a variable should be measured in a study, including the meaning and the data collection method (e.g., questionnaire, observation, interview).

• explaining the variable to those that want to use it - explaining how it’s measured.

• ex if someone has 1-5 pieces of jewelry, they have “little”, but if they have 11+, they have “many”. we are operationally defining the amount of jewelry someone is wearing.

Questionnaire

A data collection method that involves asking participants questions to obtain information.

Observation

A data collection method that involves counting and recording behaviors or events as they occur.

Interview

A data collection method that involves asking questions and recording responses from participants.

Independent Variable (IV)

An attribute or manipulated variable thought to explain changes in the DV; cannot always be manipulated; used in observational and experimental studies.

Active (Manipulated) IV

An IV that researchers actively control or change to test its effect (e.g., different treatments or groups). often used in experimental studies — can draw cause-effect conclusions

Attribute independent variable

An IV that cannot be manipulated by researchers (e.g., age, eye color, ethnicity). a pre=existing characteristic

Dependent Variable (DV)

The outcome or effect measured to assess the impact of the IV; also called the response, outcome, or criterion variable.

Extraneous Variable (EV)

Nuisance or confounding variables that may influence the DV but are not of primary interest; controlled to minimize their effects.

Confounding Variable

An EV whose effects on the DV cannot be distinguished from other IVs because it relates to both the IV and DV. ex in a study where you want to know if being male causes liver cancer, drinking would be a confounding variable

Research Question

A statement researchers seek to answer, which can be descriptive, associational, or difference-based.

Research Hypothesis

A theoretical, testable explanation about the relationship between variables; not a question or guess but an informed expectation. Proposed explanation for observation or phenomenon

Descriptive Research Question

Asks to describe or summarize data (e.g., average drinks, proportion of students in a group).

Associational Research Question

Examines relationships between two or more variables (e.g., smoking and cancer risk).

Difference Research Question

Asks whether there are differences between two or more groups on a variable.

Descriptive Statistics

Statistics that describe basic features of data (e.g., mean, median, mode, percentages), provide simple summaries about characteristics of data

Inferential Statistics

Statistics used to draw conclusions about a population from sample data (e.g., t-tests, ANOVA, correlations).

conclusions drawn about relationships between variables

Target Population

The population being studied from which samples are drawn and to which findings are generalized.

Subpopulation

A well-defined subset of the target population.

Unit of Population / Population Unit

The objects measured within the population (e.g., humans, rats, plants, organizations).

Sample

A subset of the target population actually studied.

sampling would be the process of selecting research units from a study population

Sample Size

The number of units in the sample (n). it’s size should be large enough to be an accurate representation of the population and to achieve statistically sifnificant results

Sampling Frame

The population unit available for sampling (the list or frame from which you sample).

Sampling Protocol

The method used to select a sample or participants (e.g., random sampling procedure).

Sampling Frame vs Population Parameters

Frame: what is available to sample; Parameters: numerical characteristics of the whole population, inferred from samples. sample is to statistic what population is to parameter

Sample Statistics

Numbers calculated from the sample data (e.g., mean, median, mode).

Population Parameters

Numerical characteristics of the entire population, often inferred from samples.

probability sampling

any sampling methods that uses some form of random selection. includes random sampling, stratified random sampling, cluster sampling (multi-stage), systemic random samplings.

allows you to generalize

non-probability sampling method

any method that doesn’t involve random selection - only depends onr eadily available subjects.

includes convenience sampling, quota sampling, snowball sampling, purposive sampling

Random Sampling

Probability sampling where every possible sample has an equal chance of being selected.

Stratified Random Sampling

A random sampling method that ensures representation from well-defined subgroups (strata) by sampling from each stratum. Categories that do not overlap. You cannot belong to more than one of the strata. This is especially helpful for biomedical research

Systematic Random Sampling

Select a random starting unit from the first k units, then pick every kth unit thereafter.

Cluster Sampling

Divide population into clusters, randomly select some clusters, and study all units within selected clusters.

non-homogenous.

Convenience Sampling

Non-probability sampling using readily available subjects; useful for pilot studies.

Quota Sampling

Non-probability sampling that mirrors population proportions across categories (non-random).

Snowball Sampling

Start with a small group and recruit through referrals to reach hard-to-reach populations.

Purposive Sampling

Non-probability sampling where participants are selected based on specific purpose or criteria. Ex you do a study on people that chew gum, your sample is going to be made up of people that chew gum

Sampling Error

The mismatch between the sample and the target population due to sampling variability or bias.

Experimental Study

A study where the researcher controls assignment to treatments and actively manipulates conditions.

Observational Study

A study where subjects are observed in their natural groups without manipulation; no assignment by researchers.

SPSS (IBM SPSS Statistics)

Statistical software used to enter, code, and analyze data; accessible via campus labs or cloud (Azure).

Variable View (SPSS)

SPSS view where each row is a variable; you name variables and set properties; rules apply to variable names.

Data View (SPSS)

SPSS view where each row is a case/subject and each column is a variable; data are entered and displayed.

Naming Variables in SPSS

Create clear, consistent variable names before data entry (as emphasized in SPSS guidance).

nominal variable

when a variable’s values are not numbered - just names. ex - gender or occupation. value labels are especially important when the variables are nominal.