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34 Cards in this Set
- Front
- Back
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Individuals
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Objects (people or firms) described by a set of data.
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Variable
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Any characteristic of an individual.
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Categorical Variable
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Places an individual into one of several groups of categories.
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Quantitative Variable
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takes a numerical value for which arithmetic operations make sense
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Distribution
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Tells what values it takes and how often it takes these values
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Outlier
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An individual that falls outside the overall pattern
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Mean
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the most commen measure of center a.k.a the arithmetic average
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Median
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The midpoint of a distribution
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Variance
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the average of the squares of the deviation of the observations from their mean
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Response Variable (dependent variables)
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measures an outcome of a study
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Explanatory Variable (independent variables)
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Explains or influences changes in a response variable
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Scatterplot
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Shows the relationship between two quantitative variables measured on the same individuals.
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Positively Associated
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Two variables when above-average values of one tend to accompany above-average values of the other and below-average values also tend to occur together
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Negatively Associated
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Two variables when above-average values of one tend to accompany below-average values of the other, and vice versa
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Correlation (r)
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Measures the direction and strength of the linear relationship between two quantitative variables
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Least-Squares Regression Line
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line of y on x is the line that makes the sum of the squares of the verrtical distances of the data points from the line as small as possible
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Residual
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The difference between an observed value of the response variable and the value predicted by the regression line.
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Residual Plot
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A scatterplot of the regression residuals against the explanatory variable
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Infuential Observation
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Observation is influentil if removing it would markedly change the result of the calculation
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Extrapolation
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The use of a regression line for prediction for outside the range of values of the explanatory variable x that you used to obtain the line. (Such predictions are often not accurate)
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Lurking Variable
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A variable that is not among the explanatory or response variable in a study and yet may influence the interpretation of relationships among those variables
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Simpson's paradox
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when an association or comparison that holds for all of several groups can reverse direrction when the data are combined to form a single group.
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Sample
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the part of the population from which we actually collect information used to draw conclusions about the whole
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Experiment
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Deliberately imposes some treatment on individuals to observe their responses
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Observational study
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Observes individuals and measures variables of interest but does not attempt to influence the responses
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Confounded Variables
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Variables are confounded when their effects on a response variable cannot be distinguished from each other
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Population
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The entire group of individuals about which we want information
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bias
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a study shows bias if it systematically favors certain outcomes
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Simple Random Sample
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sample of n individuals from the population chosen so every set of n individuals has an equal chance to be the sample actually selected
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Undercoverage
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Occurs when some groups in the population are left out of the process of choosing the sample
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Nonresponse
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occurs when an individual chosen for the sample can't be contacted or refuses to cooperate
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Subjects
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individuals studied in an experiment
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Factors
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explanatory variables in an experiment
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Treatment
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Any specific experimental condition applied to the subject
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