Data
observations (such as measurements, genders, survey responses) that have been collected
Parameter
a numerical measurement describing some characteristic of a population.
Statistic
a numerical measurement describing some characteristic of a sample.
Quantitative (or numerical) data
numbers representing counts or measurements.
Categorical (or qualitative or attribute) data
can be separated into different categories that are distinguished by some nonnumeric characteristic
Discrete data
result when the number of possible values is either a finite number or a 'countable' number
(i.e. the number of possible values is
0, 1, 2, 3, . . .)
Continuous (numerical) data
result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps
Nominal Level of measurement
characterized by data that consist of names, labels, or categories only, and the data cannot be arranged in an ordering scheme (such as low to high)
ordinal level of measurement
involves data that can be arranged in some order, but differences between data values either cannot be determined or are meaningless
Interval level of measurement
like the ordinal level, but the difference between any two data values is meaningful, however, there is no natural zero starting point
Ratio level of measurement
differences and a natural starting point
Nominal - categories only
Ordinal - categories with some order
Interval - differences but no natural starting point
Ratio - differences and a natural starting point
Nominal - categories only
Ordinal - categories with some order
Interval - differences but no natural starting point
Ratio - differences and a natural starting point
Observational study
observing and measuring specific characteristics without attempting to modify the subjects being studied
Experiment
apply some treatment and then observe its effects on the subjects; (subjects in experiments are called experimental units)
Simple Random Sample
of n subjects selected in such a way that every possible sample of the same size n has the same chance of being chosen
Random Sample
members from the population are selected in such a way that each individual member in the population has an equal chance of being selected
Systematic Sampling
Select some starting point and then
select every k th element in the population
Convenience Sampling
use results that are easy to get
Stratified Sampling
subdivide the population into at
least two different subgroups that share the same characteristics, then draw a sample from each subgroup (or stratum)
Cluster Sampling
divide the population into sections
; randomly select some; choose all members from selected sections
Randomization
randomly selecting into groups
Replication
is the repetition of an experiment on more than one subject. Samples should be large enough so that the erratic behavior that is characteristic of very small samples will not disguise the true effects of different treatments. It is used effectively when t
Blinding
is a technique in which the subject doesn't know whether he or she is receiving a treatment or a placebo.
Double-Blind
1) The subject doesn't know whether he or she is receiving the treatment or a placebo
2) The experimenter does not know whether he or she is administering the treatment or placebo
Confounding
occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors.
Sampling error
the difference between a sample result and the true population result; such an error results from chance sample fluctuations
Nonsampling error
sample data incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or copying the data incorrectly)
Statistics
a collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data
Population
The complete collection of all elements
(scores, people, measurements, and so on)
to be studied;
The collection is complete in the sense that it includes all subjects to be studied
Census
Collection of data from every member of a population
Sample
Subcollection of members selected from a population