Variable
any characteristic of an individual, can take different value for each individual
Quantitative variable
takes numerical values for which being able to do arithmetic
Categorical variable
places and individual into one of several different categories or groups
Observational study
observe individuals to measure variables of
interest, without attempting to influence a response
Experiment
deliberately imposes some treatment on individuals in
order to observe their responses
Population
The entire group of individuals about which we want
information
Sample
A part of the population that we actually examine to gather
information, for the purpose of drawing conclusions about the whole population
Census
A "sample" that attempts to get information from every
member of the population
Parameter
A number that describes the population
Statistics
A number that describes a sample
Convenience sample
Made up of individuals that are easiest to reach
Voluntary response sample
People who choose to be in the sample
themselves by responding to a general appeal
Random sample
Every individual in the population has an equal
chance of being chosen
Simple random sample
Each individual has an equal chance
of being chosen
Stratified random sample
Individuals in the same group have an
equal chance of being chosen
Bias
Consistent, repeated deviation of the sample statistic from the population parameter (true value) in the same direction when taking many samples
Variability
How spread out the values of the sample statistics are when we take many samples
Margin of Error
Tells how close the estimate (sample statistic) is
to the truth (population parameter)
Level of Confidence
The percent of all possible samples of the population
whose statistic differs from the parameter by no more than the MOE
Sampling error
Errors caused by the act of taking a sample
Nonsampling error
Errors not caused by the act of taking a sample
Undercoverage
Occurs when some groups in the population are left
out of the sample selection process
Sampling frame
The list of individuals that a sample is drawn from
Processing error
Someone makes a manual error (like misrecording
a response or making a math error)
Response error
Occurs when subject gives incorrect response (by
lying, remembering incorrectly, not understanding the question, etc.)
Nonresponse error
Failure to obtain data from an individual
selected for the sample
Explanatory variable
Explains or causes changes in the response
variable
Response variable
Measures outcome or result of study
Treatment
Any specific experimental condition applied to the
subjects
Lurking Variable
Has an important effect on relationship among the
variables in a study but is not included as an explanatory variable
Placebo
a dummy treatment with no active ingredients
Double blind experiment
when neither the subjects nor the people who work with them know which treatment each subject receives
Replication
using many individuals in each group
Statistical significance
An observed treatment effect of a size that
would rarely occur by chance
Generalizability
Can we generalize results from an experiment to the
whole population we are studying?
Nonadherance
Individuals who participate in an experiment but
don't do what is told
Dropouts
Individuals who begin the experiment but don't finish the
experiment
Matched pairs designs
A design used to compare two different treatments
Completely randomized design
...
Randomized block design
...
Validity
A measure of a property that is relevant or appropriate as a
representation of that property
Random error
If repeated measurements on the same individual
give different results
Reliability
A measurement where the random error is small
Distribution of variable
Tells us what values the variable takes and
how often it takes these values
Shape
Used to describe histograms, make sure you consider the peaks and the tail
Center
Where is it located along the horizontal axis? What seems to be the midpoint of the data?
Spread
How variable does the data seem to be from the center? Or, what is the overall range of data?
Mean
Average of all indeviduals
Mode
The biggest peak, the most common number(s)
Median
M, the middle number in the data set
Standard deviation
This tells us
how data values disperse or deviate from
the mean.