Stats Unit 1.1-1.3

Data

Consist of information coming from observations, counts, measurements, or responses.

Statistics

The science of collecting, analyzing, interpreting, and presenting data to make descisions.

Population

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

Sample

A subset, or part, of the population.

Parameter

A numerical description of a population characteristic.

Statistic

A numerical description of a sample characteristic.

Descriptive Statistics

Involves the organization, summarization, and display of data.

Inferential Statistics

Involves using sample data to draw conclusions about a population.

Qualtative Data

Consists of attributes, labels, or nonnumerical entries.

Quantitative data

Numerical measurements or counts.

Nominal level of measurement

Qualitative data only

Categorized using names, labels, or qualities

No mathematical computations can be made

Ordinal level of measurement

Qualitative or quantitative data

Data can be arranged in order, or ranked

Differences between data entries is not meaningful

Interval level of measurement

Interval variables have a natural order and quantifiable differences between values, but they lack a true zero point.

Ex: Credit Scores (300–850)

SAT Scores (400–1600)

Ratio level of measurement

Has all the properties of interval variables, but they also have a true zero, allowing for meaningful ratios.

Ex: Height (in cm or inches)

Weight (in kg or pounds)

Length (in meters or feet)

Observational Study

A researcher observes and measures characteristics of a sample but does not change existing conditions.

Data may be collected at one time, from past records, or over a period of time.

Experiment

A treatment is applied to part of a population, called a treatment group, and responses are observed. Another part of the population may be used as a control group, in which no treatment is applied.

Subjects in the control group are often given a placebo. Subjects in both groups are called experimental units. The responses of both groups can then be compared and studied.

Survey

An investigation of one or more characteristics of a population, carried out on people by asking them questions. Commonly done by interview, Internet, phone, or mail. In designing one, it is important to word the questions so that they do not lead to biased results, which are not representative of a population

Confounding variables

Occurs when an experimenter cannot tell the difference between the effects of different factors on the variable

Blinding

A technique where subjects do not know if they are receiving a treatment or a placebo.

Double Blinding

Neither the experimenter nor the subjects know who is receiving a treatment or a placebo.

Randomization

The process of randomly assigning subjects to different treatment groups.

Randomized block design

Subjects with similar characteristics are divided into blocks. Then, within each block, subjects are randomly assigned to treatment groups.

Matched-Pairs Design

Subjects are paired up according to a similarity. One subject in the pair is randomly selected to receive one treatment while the other subject receives a different treatment.

Sample Size

The number of subjects in a study is very important to experimental design.

Replication

The repetition of an experiment under the same or similar conditions.

Census

A count or measure of an entire population

Sampling

A count or measure of part of a population and is more commonly used in statistical studies

Random Sample

Every member of the population has an equal chance of being selected

Simple Random Sample

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

Stratified Sample

Divide a population into groups and select a random sample from each group

Cluster Sample

Divide the population into groups and select all of the members in one or more, but not all, of the clusters.

Systematic Sample

Choose a starting value at random. Then choose every kth member of the population

Convenience Sample

Choose only members of the population that are easy to get. Often leads to biased studies