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37 Cards in this Set
- Front
- Back
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statistics
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a collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on data
*also: uncertainty in interpreting and drawing conclusions |
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data
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observations (such as measurements, genders, survey responses) that have been collected
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population
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the complete collection of all elements (scores, measurements, and so on) to be studied; the collection is complete in the sense that it includes all subjects to be studied
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census
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the collection of data from every member of the population
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sample
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a subcollection of data from members selected from a population
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parameter
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a numerical measurement describing some characteristic of a population
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statistic
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a numerical measurement describing some characteristic of a sample
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quantitative data
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numbers representing counts or measurements
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qualitative data
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data that can be separated into different categories that are distinguished by some nonnumerical characteristic
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discrete data
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when the number of possible values is either a finite number or a "countable" number
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continuous data
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when there are infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps or interruptions
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nominal level of measurement
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data that consist of names, labels, or categories only; the data cannot be arranged in an ordering scheme (such as low to high)
ex) yes/no/undecided |
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ordinal level of measurement
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data that can be arranged in some order, but differences between data values either cannot be determined or are meaningless
ex) A, B, C, D, E |
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interval level of measurement
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like the ordinal level with the addition property that the difference between any two data values is meaningful; however data at this value do not have a natural zero starting point
ex) years (time did not begin at 0 A.D.) |
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ratio level of measurement
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similar to the interval level or measurement except it has a natural zero starting point where at zero, none of the quantity is present
ex) weight |
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variable
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something we make observation on
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confounding variable
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one that affects the response variable and is related to the explanatory variable; variable that correlates to the dependent and independent variables to make it seem cause/effect
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lurking variable
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other variable that was considered as a cause but don't have data for
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observation studies
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measurements of specific characteristics with no attempt to modify the subjects being studied
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types of observational studies
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1) cross-sectional study
2) retrospective (case-control) study 3) prospective (longitudinal/cohort) study |
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cross-sectional study
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data are observed, measured, and collected at one point in time
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retrospective (case-control) study
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data are collected from the past by going back in time (through examination of records, interviews, etc.)
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prospective (longitudinal or cohort) study
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data are collected in the future from groups sharing common factors (called cohorts)
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experiments
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we apply some treatment and then proceed to observe its effects on the subjects
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key elements for an experimental design
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1) control for effects of variables
2) use replication 3) use randomization |
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blinding
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the researcher doesn't know which treatment is which
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placebo effect
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use imitation pill with no drugs in it but looks like the actual pill
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double dummy
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example) have pills & lotion treatment: give half of the group the placebo pill and treatment lotion; give other half placebo lotion and treatment pill
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double blind
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if no body knows (especially person giving the treatment) which are placebos and which are real
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random sampling
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each individual has an equal chance of being selected
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simple-random sampling
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each sample of the same size n has an equal chance of being chosen
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probability sample
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each member has a known chance of being selected
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systematic sampling
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select starting point and then select every kth element in population
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stratified sampling
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subdivide the population into at least two different subgroups (or strata) so that subjects within the same subgroup share the same characteristics (such as gender or age bracket), then draw a sample from each subgroup
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cluster sampling
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divide the population area into sections (clusters), then randomly select some of those clusters, and chose all the members from those selected clusters
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convenience sampling
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using results that are very easy to get
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multi-stage sampling
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combination of other types of sampling
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