Data
consist of information coming from observations, counts, measurements, or responses.
Statistics
is the science of collecting, organizing, analyzing, and interpreting data to make decisions.
Population
is the collection of all outcomes, responses, measurements, or counts that are of interest. A sample is a subset, or part, of a population.
Sample
is a subset, or part, of a population.
Parameter
is a numerical description of a population characteristic.
Descriptive Statistic
is the branch of statistics that involves the organization, summarization, and display of data.
inferential statistics
is the branch of statistics that involves using a sample to draw conclusions about a population. A basic tool in the study of inferential statistics is probability.
Qualitative date
consist of attributes, labels, or nonnumerical entries.
Quantitative data
consist of numbers that are measurements or counts.
nominal level of measurement
are qualitative only. Data at this level are categorized using names, labels, or qualities. No mathematical computations can be made at this level.
ordinal level of measurement
are qualitative or quantitative. Data at this level can be arranged in order, or ranked, but differences between data entries are not meaningful.
Interval level
can be ordered, and meaningful differences between data entries can be calculated. At the interval level, a zero entry simply represents a position on a scale; the entry is not an inherent zero.
Ratio level
are similar to data at the interval level, with the added property that a zero entry is an inherent zero. A ratio of two data entries can be formed so that one data entry can be meaningfully expressed as a multiple of another.
observational study
a researcher does not influence the responses.a researcher observes and measures characteristics of interest of part of a population but does not change existing conditions.
Experimental study
a researcher deliberately applies a treatment before observing the responses.
Treatment
is applied to part of a population, called a treatment group, and responses are observed.
Control
In an experiment, the standard that is used for comparison
Placebo
which is a harmless, fake treatment that is made to look like the real treatment.
Simulation
is the use of a mathematical or physical model to reproduce the conditions of a situation or process. Collecting data often involves the use of computers.
Survey
is an investigation of one or more characteristics of a population.
Confounding variable
occurs when an experimenter cannot tell the difference between the effects of different factors on the variable.
Placebo effect
occurs when a subject reacts favorably to a placebo when in fact the subject has been given a fake treatment.
Blinding
is a technique in which the subjects do not know whether they are receiving a treatment or a placebo.
Double-blind experiment
neither the experimenter nor the subjects know whether the subjects are receiving a treatment or a placebo.
Randomization
is a process of randomly assigning subjects to different treatment groups.
Randomized block design
To use a randomized block design, the experimenter divides the subjects with similar characteristics into blocks, and then, within each block, randomly assign subjects to treatment groups.
Matched pairs design
in which subjects are paired up according to a similarity. One subject in each pair is randomly selected to receive one treatment while the other subject receives a different treatment.
Sample size
which is the number of subjects in a study, is another important part of experimental design.
Replication
is the repetition of an experiment under the same or similar conditions.
Census
is a count or measure of an entire population.
sampling
is a count or measure of part of a population and is more commonly used in statistical studies.
Sampling error
A sampling error is the difference between the results of a sample and those of the population.
Random sample
is one in which every member of the population has an equal chance of being selected.
Stratified sample
When it is important for the sample to have members from each segment of the population, you should use a stratified sample
Cluster sample
When the population falls into naturally occurring subgroups, each having similar characteristics, a cluster sample may be the most appropriate.
systematic sample
A systematic sample is a sample in which each member of the population is assigned a number.
Convenience sample
A convenience sample consists only of members of the population that are easy to access.