Mastering Data Collection: Sampling, Surveys, and Experimental Design

Statistics

The science of learning from data.

Observational Study

Researchers measure variables of interest without influencing responses.

Retrospective Study

Looks backward at existing data to find associations.

Prospective Study

Tracks individuals into the future to find outcomes.

Correlation

A mutual relationship or connection between two variables.

Causation

Indicating that one event is a result of the occurrence of another event.

Confounding Variables

Variables that can obscure the relationship between the studied variables.

Experimental Units

The individuals on which the experiment is done, called subjects if human.

Explanatory Variable

What is being manipulated in an experiment.

Response Variable

The outcome being measured in an experiment.

Random Sampling

A method of selecting a sample from a population in which each individual has an equal chance of being selected.

Simple Random Sample (SRS)

Every group of n individuals has an equal chance of being selected.

Stratified Random Sampling

Divide the population into strata and take a separate SRS from each stratum.

Cluster Sampling

Divide the population into clusters and include all individuals from selected clusters.

Systematic Sampling

Selecting every kth individual from a list.

Bias

A systematic error that occurs in the design of the study.

Voluntary Response Sample

Individuals choose themselves to participate.

Convenience Sample

Choosing individuals who are easiest to reach.

Undercoverage Bias

Occurs when segments of the population are excluded from the sample.

Nonresponse Bias

Occurs when individuals chosen for the sample cannot be contacted or refuse to participate.

Response Bias

A systematic pattern of incorrect responses due to various factors.

Experimental Design

The process of planning an experiment to ensure valid conclusions.

Comparison Principle

A design that compares two or more treatments.

Random Assignment

Chance assignment of experimental units to treatments.

Control in Experiments

Keeping other variables the same to prevent confounding.

Replication in Experiments

Using enough experimental units to distinguish effects from chance differences.

Control Group

A group that receives no treatment or an inactive treatment for comparison.

Placebo Effect

Response to a dummy treatment based on belief.

Single-blind

Subjects do not know which treatment they are receiving.

Double-blind

Neither subjects nor researchers know who receives which treatment.

Statistical Significance

An observed effect that is unlikely to occur by chance.

Completely Randomized Design

All experimental units are randomly allocated to treatments.

Randomized Block Design

Grouping similar experimental units into blocks before random assignment.

Matched Pairs Design

A method of comparing two treatments using paired subjects.

Scope of Inference

Determines the conclusions drawn based on study type.

Random Selection

Selecting individuals from the population at random.

Causation in Experiments

Can be established through rigorous experimental design.

Correlation vs. Causation

Correlation does not imply causation.

Control Variables vs Control Groups

Control variables are constant; control groups are for comparison.

Stratifying vs Blocking

Stratifying is for sampling; blocking is for experimenting.