Chapter 1 Flashcards
(24 cards)
contains measurements or observations, taken on people or objects
data set
characteristics being measured
variables
is the collection of all subjects (humans, plants, computers) of interest.
population
is any subset of the population of interest
sample
If the sample and the population are equal, the study is called a
census
consists of the collection, organization, summarization, and presentation of data
Descriptive statistics
consists of generalizing from samples to populations, performing estimation of population summaries, and testing hypotheses (claims) about populations
inferential statistics
assume values that can be counted
discrete variables
can assume an infinite number of values between any two specific values. The arise from taking measurements.
continuous variables
is a type of classification that tells how variables are categorized, counted, or measured; the four types of scales are nominal
measurement scale
classifies data into mutually exclusive (no overlapping) categories in which no order or ranking can be imposed on the data
nominal level of measurement
classifies data into categories that can be ranked; however, precise differences between the ranks do not exist.
ordinal level of measurement
ranks data, and precise differences between units of measure do exist; however, there is no meaningful zero.
interval level of measurement
possesses all the characteristics of interval measurement, and there exists a true zero.
ratop level of measurement
to make a statement about a population using the sample
statistical inference
is a sample in which all members of the population have an equal chance of being selected
random sample
any difference between the sample and population can be understood using probability rules
random sampling error
is a sample obtained by selecting every kth member of the population
systematic sample
is obtained by dividing the population into sections or clusters and then selecting one or more clusters and using all members in the clusters as the members of the sample
cluster sample
the researcher merely observes what is happening or what has happened in the past and tries to draw conclusions based on these observations
observational study
the researcher manipulates one of the variables and tries to understand how the manipulated variable (independent/explanatory) influences the resultant variable (dependent/response)
experimental study
when data are collected at the same point in time the study is called
cross sectional
data are collected over time
longitudinal
data from the past are gathered
retrospective
