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33 Cards in this Set
- Front
- Back
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POPULATION |
The entire collection of individuals (or objects) about which information is desired |
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SAMPLE |
A subset of the population selected for thestudy |
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VARIABLE |
Any characteristic whose value may change fromindividual or object to the next |
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DATA |
Observations on a single variable,two variables simultaneously, or two or more variables simultaneously |
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UNIVARIATE DATA |
having a single variable |
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BIVARIATE DATA |
having two variables simultaneously |
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MULTIVARIATE DATA |
having two or more variables simultaneously |
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CATEGORICAL VARIABLE |
A variable whose individual observations are numbers counting or measuring some quantity (ex. Zip Codes, State of birth, brand name, price) |
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NUMERICAL VARIABLE |
A variable whose individual observations are numbers counting or measuring some quantity (ex. Weight, height) |
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DISCRETE NUMERICAL |
Possible values represent individual points on the number line (“counting”) |
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CONTINUOUS NUMERICAL |
Possible values represent an interval on the number line (“measuring”) |
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OBSERVATIONAL STUDY |
the investigator observes characteristics of a sample from one or more populations |
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EXPERIMENT |
The investigator observes how a response (dependent) variable behaves when one or more explanatory (independent) variables are manipulated |
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CONFOUNDING VARIABLES |
A variable that affects both the independent and dependent variable that is not accounted for by the investigator. When confounding variables are present, the investigator should not make a cause-and-effect conclusion |
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SELECTION BIAS |
when the sample systematically excludes part of the population being studied |
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RESPONSE/ MEASUREMENT BIAS |
When the method of observation tends to produce responses/ values that differ from what is actually true |
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NONRESPONSE BIAS |
when the individuals selected for the sample don't respond |
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SIMPLE RANDOM SAMPLE |
A sample selected from a population in a way that ensures that every different possible sample of the desired size has the same chance of being selected |
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EXPLANATORY/ INDEPENDENT VARIABLE |
a variable controlled by the experimenter |
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RESPONSE/ DEPENDENT VARIABLE |
A variable not controlled by the experimenterwhose values are measured as part of the experiment |
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EXTRANEOUS VARIABLE |
A variable that may affect the response variablebut is not among the explanatory variables |
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DIRECT CONTROL |
Hold the extraneous variable constant so that itdoes not affect the response variable |
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BLOCKING |
Use the extraneous variable to create blocks, then try each treatment in each block. This is best used for characteristics that divide into a relatively small number of categories |
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RANDOM ASSIGNMENT |
Randomly assign patients into treatment groups. This accounts for person-to-person (or object-to-object) differences that are too difficult to control directly and ensures that the experiment does not systematically favor one treatment |
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PIE CHARTS |
For categorical data with a relatively small number of categories |
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COMPARATIVE BAR GRAPHS |
For categorical data comparing two or moregroups |
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FREQUENCY DISTRIBUTION |
for organizing continuous numerical data |
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HISTOGRAMS |
for continuous numerical data, even for large data sets |
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UNIMODAL |
Single peak present on a histogram |
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BIMODAL |
two peaks present on a histogram |
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MULTIMODAL |
two or more peaks present on a histogram |
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POSITIVELY SKEWED |
the right tail is stretched out farther than the left tail |
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NEGATIVELY SKEWED |
the left tail stretches out farther than the right tail |
