Chapter 1- Introduction to Statistics
Convenience sample
leads to biased studies
Confounding variable
occurs when an experimenter cannot tell the difference between the effects of different factors on the variable
Control group
receives no treatment
Ratio level of measurement
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
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 used is probability
Population
the collection of all outcomes, responses, measurements, or counts that are of interest
Sample size
the number of subjects in a study
Replication
the repetition of an experiment under the same or similar conditions
Statistics
the science of collecting, organizing, analyzing, and interpreting data in order to make decisions
Simulation
the use of a mathematical or physical model to reproduce the conditions of a situation or process
Census
a count or measure of an entire population
Sampling
a count or measure of part of a population
Placebo
a harmless, fake treatment that is made to look like the real treatment
Parameter
a numerical description of a population characteristic
Statistic
a numerical description of a sample characteristic
Randomization
a process of randomly assigning subjects to different treatment groups
Experiment
a researcher deliberately applies a treatment before observing the responses
Observational study
a researcher does not influence the responses
Sample
a subset, or part, of a population
Blinding
a technique where the subjects do not know whether they are receiving a treatment or a placebo
Survey
an investigation of one or more characteristics of a population
Treatment
applied to a group called the treatment group
Nominal level of measurement
are qualitative only and are categorized using names, labels, or qualities; no mathematical computations can be made
Ordinal level of measurement
are qualitative or quantitative and can be arranged in order, or ranked, but differences between data entries are not meaningful
Double
blind experiment- neither the experimenter nor the subjects know if the subjects are receiving a treatment or a placebo
Interval level of measurement
can be ordered, and meaningful differences between data entries can be calculated; a zero entry simply represents a position on a scale; the entry is not an inherent zero
Data
consist from information coming from observations, counts, measurements, or responses
Qualitative data
consist of attributes, labels, and nonnumerical entries
Quantitative data
consist of numerical measurements or counts
