Statistics (1.1 - 1.3 Review)

Observational Study

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

Experiment

A treatment is applied to a part of a population and responses are observed. Another part of the population may be used as the control group, in which no treatment is applied. In some cases there are subjects given a placebo made to look like a real treatment. The results of the groups can be compared and studied.

Simulation

The use of a mathematical or physical model to reproduce the conditions of a situation or process

Confounding Variables

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

Placebo Effect

When a subject reacts favorably to a placebo when in fact the subject has been given no medicated treatment at all.

Binding

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

Double-Blind Experiment

Neither the experimenter nor the subjects know if the subjects are receiving a treatment or a placebo. The experimenter is informed after all the data has been collected.

Randomization

A process of randomly assigning subjects to different treat groups.

Randomized Block Design

Dividing subjects with similar characteristics into blocks, and then, within each block, randomly assigning subjects 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.

If there are too few subjects in the sample, then there is not enough information to make a general statement about a population.

Replication

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

Simple Random Sample

A sample in which every possible sample of the same size has the same chance of being selected.

Stratified Sample

Depending on the focus of the study, members of the population are divided into two or more subsets, called strata, that share similar characteristics. A sample is then randomly selected from each of the strata.

Cluster Sample

Divide the population into groups, called clusters, and select all of the members in one or more of the clusters.

Systematic Sample

A sample in which each member of the population is assigned a number. The members are ordered in some way, a starting number is randomly selected, and then sample members are selected at regular intervals from the starting number.

Convenience Sample

Often leads to biased studies. Consists of only available members of the population.

Population

Collection of responses, outcomes, counts, and measurements in areas of interest.

Sample

Part, subset, or part of a population (SPECIFICS)

Parameter

A numerical description of a population characteristic. (Comes from a population)

Data

Consists of info coming from counts, observations, responses, or measurements

Qualitative

Attributes, labels, and numerical identities

Quantitative

Numerical information that can be measured and expressed using numbers. It involves collecting data through methods such as surveys, experiments, or observations, and the data is typically analyzed using statistical techniques. Examples of quantitative data include measurements, counts, percentages, and ratings.

Nominal

Words not numbers (Names, labels, and qualities)

Ordinal

Words and numbers ranked in an order (TV Guides of Top Shows or anything within a specific order from low to high)

Interval

Can be ordered and meaningful differences can be calculated. (Can have a zero entry)

Ratio

Similar to the interval level, data values can be meaningfully expressed as a multiple of another. (Can’t have a zero entry)

Statistic

The science of collecting, organizing, analyzing, and interpreting data in order to make decisions. A numerical description of a population characteristic.