STATS C1000 TERMS AND DEFINITIONS

Data

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

Statistics

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

Population

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

Sample

a subset, or part, of a population

Parameter

A numeral 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. A basic tool in the study of _____ _______ is probability

Qualitative Data

consist of attributes, labels, or nonnumerical entries

Quantitative Data

Consist of numerical measurements or counts.

Nominal level of measurement

Measures qualitative data and categorizes data by using names, labels or qualitites. No mathematical computations can be made at this level.

Ordinal level of measurement

Measures qualitative or quantitative data. This level of measurement can be arranged in order, or ranked, but differences between data entries are not meaningful.

Interval level of measurement

Can be ordered and meaningful differences between data entries can be calculated. On this level a zero entry simply represents a position on a scale; the entry is not an inherent zero.

Ratio level of measurement

Similar to the interval level, with added property that a zero entry is an inherent zero. A ratio of two data values can be formed so taht one data value can be meaningfully expressed as a multiple of another.

inherent zero

A zero that implies “none.”

Observational study

This method of data collection involves a researcher observing to measure characteristics of interest of part of a population but does not change existing conditions.

Perform an experiment

This version of study involves a treatment is applied to a part of a population and responses to the population that is observed. Another part of the population may be a control group where no treatment is applied. In many case subjects in the control group are given a placebo. The responses of the treatment group would then be compared and studied. In most cases its a good idea to use the name number of subjects for each treatment.

Placebo

A harmless unmedicated treatment that is made to look like real treatment

Use a simulation

This study of data collection involves te use of mathematical or physical model to reproduce the conditions of a situation or process. Collecting data in this form involves the use of computers. It also allow you to create study situations that are impratical or dangerous to create in real life. Often this form saves time and money.

Use a Survey

This study of data collection involves an investigation of one or more characteristics of a population. Most often its carried out on people by asking them uestions. The most common types of this form of data collection are conducted by onterview, mail or telephone. Its important however to make sure the questions ask do not lead to bias results. Which are not representative of a population.

Confounding variable

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

Binding

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

Double-blind experiment

Neither experiment nor the subjects know if subjects are receiving a treatment or a placebo. The experimenter is informed after all the data has been collected. This type of experiment is preferred by researchers.

Randomization

a process of randomly assigning subjects to different treatment groups.

Completely randomized design

Subjects are assigned to different treatment groups through random selection

Blocks

A group of subjects whith similar characteristics

Matched-Pair Design

Where subjects are paired up according to similarity.

Sample Size

The number of subjects, another important part of experimental design.

Replication

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

Census

A count or measure of an entire population. This provides complete information.

Sampling

A count or measure of part of a population. More commonly used in statistical studies.

Sampling Error

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

Random Sample

One in which every member of the population has an equal chance of being selected.

Simple Random Sample

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

With replacement

Acceptable to have the same population member selected more than once.

Without replacement

Not acceptable to have the same population member selected more than once.

Strata

Depending on the focus of the study, members of the population are divided into two or more subsets.

Stratified Sample

When it is important for the sample to have members from each segment of the population. Put strata that share similar characteristics. A sample is then selected from each of the strata and this version of data sample will ensure that each segment of the population is represented.

Cluster Sample

When the population falls into naturally occuring subgroups, each have similar characteristics. This type of sample may be the most appropriate.

Systematic Sample

A sample in which each member of the population is assigned a number. The members of the population 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

A type of sample that often leads to biased studies. - Consists of only AVAILABLE members of the population