Chapter 1: Introduction to Statistics Flashcards

Vocabulary flashcards covering core terms, definitions, levels of measurement, sampling methods, study designs, and experimental concepts from Chapter 1.

Statistics

The science of collecting, classifying, organizing, summarizing, analyzing, and interpreting data for the purpose of making informed decisions.

Descriptive Statistics

The branch of statistics that involves organizing, summarizing, and presenting data in an informative manner.

Inferential Statistics

Methods for determining something about a population based on a sample, or making decisions, predictions, and drawing conclusions about populations.

Data

Any collection of numbers, characters, images, or other items that provide information about something.

Population

A collection or set of all units (usually people, individuals, objects, or events) of interest in a study.

Sample

A representative subset of the population's units.

Census

A data collection obtained from every member of the population.

Parameter

A numerical value that summarizes a characteristic of an entire population.

Statistic

A numerical value that summarizes the data from a sample.

Unit (or Subject / Individual)

The entity from which data are collected or observed in a statistical study.

Variable

A characteristic of each individual element of a population or sample.

Datum

A single value in a dataset.

Qualitative (Categorical) Variable

A variable that describes attributes, labels, or nonnumerical entries.

Quantitative (Numerical) Variable

A variable that consists of numerical measurements or counts.

Nominal Level of Measurement

A measurement scale that categorizes data into mutually exclusive, non-overlapping groups with no inherent order or ranking.

Ordinal Level of Measurement

A measurement scale that organizes data into categories that can be ranked or ordered, but where precise differences between ranks are not defined.

Interval Level of Measurement

A measurement scale that orders data and allows meaningful comparisons of differences between values, but lacks a true zero point.

Ratio Level of Measurement

A measurement scale that possesses all properties of the interval level and includes a true zero point, allowing meaningful ratios to be formed.

Simple Random Sampling (SRS)

A sampling method in which every possible combination of $n$ individuals has an equal chance of being selected from the population list.

Stratified Random Sampling

A sampling method where the population is divided into non-overlapping, homogeneous subgroups (strata) and simple random sampling is conducted within each stratum.

Cluster Random Sampling

A sampling method where the population is divided into non-overlapping subgroups (clusters), a simple random sample of clusters is chosen, and every member within selected clusters is sampled.

Multistage Cluster Sampling

A sampling method similar to cluster sampling, but where a random sample of elements is drawn from within the selected clusters rather than surveying all cluster members.

Systematic Random Sampling

A sampling method where population members are listed, a random starting point is selected, and every $k^{\text{th}}$ member of the population is chosen.

Convenience Sampling

A non-random sampling method that involves selecting individuals or objects that are easiest to access.

Sampling Error

The difference between a sample statistic and the true population parameter it aims to estimate, resulting from observing a subset rather than the entire population.

Non-Sampling Errors

Errors occurring during data collection, processing, or analysis that are unrelated to the sampling process, including measurement errors, response bias, and non-response bias.

Observational Study

A research design where the investigator observes and measures subjects without manipulating any variables or applying direct interaction.

Experimental Study

A controlled study where researchers manipulate explanatory variables and apply treatments to determine cause-and-effect relationships.

Associated Variables (Dependent Variables)

Variables that show a connection or relationship with one another.

Independent Variables

Variables that show no evident connection or relationship with one another.

Retrospective Study

An observational study in which researchers analyze previously collected data to investigate an exposure and outcome that have already occurred.

Cross-Sectional Study

An observational study in which all measurements (exposures and outcomes) are collected simultaneously at one point in time.

Prospective Study (Cohort Study)

An observational study in which participants sharing common factors are followed forward in time at regular intervals to observe outcomes.

Response Variable

The outcome or effect being measured in a statistical study (also called outcome or dependent variable).

Explanatory Variable

The variable believed to influence or predict the response variable (also called covariate or independent variable).

Confounding Variable

An external factor that affects both the explanatory and response variables, potentially leading to misleading conclusions.

Lurking Variable

A hidden variable not included in a study that influences the observed relationship between independent and dependent variables.

Treatment

Any specific experimental condition applied to subjects in an experiment.

Placebo

A fake treatment used as a control in experimental studies.

Placebo Effect

The phenomenon where experimental units show improvement simply because they believe they are receiving a special treatment.

Single-Blind Experiment

An experiment in which subjects do not know whether they are in the control or treatment group.

Double-Blind Experiment

An experiment in which both the subjects and the researchers interacting with them do not know who is in the control group and who is in the treatment group.

Completely Randomized Design

An experimental design in which subjects are randomly assigned directly to different treatment groups without prior blocking.

Block Design

An experimental design in which subjects are first divided into homogeneous groups (blocks) based on a characteristic before random treatment assignment within each block.

Matched Pairs Design

An experimental design in which subjects are paired based on similar characteristics (or receive two treatments themselves) and assigned treatments randomly within pairs.