Sampling and Sample Data Flashcards
population
collection of objects with properties
elements
the objects in the population
cencus
a study of the whole population
often unfeasible due to numbers and limited resources
sample
selection of one or more elements of the population
statistical inference
understand the whole population by studying a sample from it
representative sample
properties of sample match unknown properties of population
non-representative sample
biased
when is bias almost certain
samples are chosen from people who volunteer
samples are drawn from only part of a population
samples are chosen for their convenience
samples are selected by someone with a vested interest in the outcome
how to avoid biased sampling
choose elements at random
choosing at random
each element of the population has exactly the same chance of being selected
what are the two ways of random sampling
with replacement and without replacement
when do the two types of random sampling essentially become equivalent
when samples are much smaller than the population
systematic sampling
elements selected according to a random starting point and a fixed periodic interval
stratified sampling
useful when the population splits into distinct groups where the groups are quite different
together the groups cover the whole population
cluster sampling
useful when the population splits into distinct clusters where the clusters are similar
take a random sample of clusters and then take the elements from within these clusters
quota sampling
populations splits into many groups such as age, sex, income
only restricted by number of elements to be selected in each group
variable
feature of the population of interest, takes a value for each element of the sample
denoted by a capital letter
observation
each recorded value of a variable
denoted by a lower case letter corresponding to the variable
sample data
collection of all observations derived from the sample
can be assembled in a data table
categorical variables
non-numerical information such as names or labels which describe the possible attributes
what are the two types of categorical variables
nominal or ordinal
nominal variables
no inherent ordering of values
ordinal variables
information about ordering or rank
quantitative variables
provide numerical information
what are the two types of quantitative variables
discrete or continuous
discrete variables
can only take values from a certain set of distinct numbers
continuous variables
take any value in an interval of numbers
