Math 11 1.1-1.3: Overview of Statistics, Data Classification, and Data Collection (Vocabulary Flashcards)

Vocabulary flashcards covering key terms from statistics notes: data, population vs sample, parameter vs statistic, data types, levels of measurement, data collection methods, sampling techniques, and experimental design concepts.

Statistics

The science of collecting, organizing, analyzing, and interpreting data to make decisions.

Data

Information coming from observations, counts, measurements, or responses.

Population

The collection of all outcomes, responses, measurements, or counts of interest.

Sample

A subset, or part, of a population.

Parameter

A numerical description of a population characteristic.

Statistic

A numerical description of a sample characteristic.

Descriptive statistics

The branch of statistics that involves the organization, summarization, and display of data.

Inferential statistics

The branch of statistics that involves using a sample to draw conclusions about a population.

Qualitative data

Data consisting of attributes, labels, or nonnumerical entries.

Quantitative data

Data consisting of numbers that are measurements or counts.

Nominal level

Qualitative data categorized by names or labels; no mathematical computation.

Ordinal level

Data that can be ordered; differences between entries may not be meaningful.

Interval level

Quantitative data that can be ordered with meaningful differences; zero is not inherent.

Ratio level

Quantitative data with meaningful order, differences, and an inherent zero; ratios are meaningful.

Census

A count or measure of an entire population.

Frame

A numbered list of all individuals in the population used for sampling.

Random Sample

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

Simple Random Sample (SRS)

Every possible sample of the same size has the same chance of being selected.

Stratified sampling

Divide population into strata and sample from each group.

Cluster sampling

Divide population into clusters and sample all members in one or more clusters.

Systematic sampling

Choose a starting value at random, then select every kth member.

Convenience sample

Sampling the easiest members of the population, often biased.

Observational study

A study where researchers observe and measure characteristics without applying treatments.

Experiment

A study where a treatment is applied to part of the population and responses are observed.

Simulation

Using a mathematical or physical model to reproduce conditions of a situation.

Survey

An investigation of one or more characteristics of a population by asking questions.

Randomization

Randomly assigning subjects to different treatment groups.

Placebo effect

A subject reacts favorably to a placebo when no real treatment is given.

Blinding

A technique where the subject does not know whether they are receiving a treatment or placebo.

Double-blind

Neither the subject nor the experimenter knows who receives the treatment or placebo.

Replication

Repeating an experiment with a large group of subjects to verify results.

Confounding variable

A factor whose effects cannot be distinguished from the treatment effect.

Population parameter

A numerical characteristic of the entire population (synonym for parameter).

Sample statistic

A numerical characteristic of a sample (synonym for statistic).

Sampling error

The difference between the results of a sample and those of the population.

Hawthorne effect

A change in behavior resulting from being studied.

Randomized block design

Grouping subjects into blocks of similar characteristics, then randomly assigning within each block.

Matched-pairs design

Subjects are paired by similarity; each receives a different treatment.