Basic Statistical Concepts

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Instrument evaluation and construction course
Donna Myers
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Donna Myers
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Zusammenfassung der Ressource

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Variable Anything that can be measured and can differ across entities or across time.
Construct The idea associated with a label given to a concept or variable.
Nominal Variable A categorical variable with two or more categories without an intrinsic order. Examples: gender (male/female) and race (White/Black / Asian, etc.)
Ordinal Variable A categorical variable with two or more categories that can be ranked into a meaningful order, but no equal distance between categories. Example: Rating (poor, good, very good, excellent).
Dichotomous Variable A categorical variable with only two categories. Examples: Yes / No or Good / Bad
Interval Variable A continuous variable measuring a construct along a continuum with equal distance between points, but without a true zero. Example: IQ test score
Ratio Variable A continuous variable measuring a construct along a continuum with equal distance between points with a true zero. Example: Weight
Independent Variable Variable of interest (predictor variable) that influences the dependent (outcome) variable.
Dependent Variable Variable of interest (outcome variable) that is influenced by the independent (predictor) variable.
Covariate Variable A variable that is not the focus of a study, but that is included in the study because it influences either the dependent or independent variable.
Population Total set of individuals, groups, objects or events being studied.
Sample Subset of people, objects, groups or events selected from a population.
Descriptive Statistics Statistics used to describe characteristics of a sample or population.
Inferential Statistics Statistics used to make predictions about a population based on the observations made from the sample.
Parametric Statistics Group of statistical tests used to analyze data that make certain assumptions about data, e.g. normal distribution of scores.
Non-Parametric Statistics Group of statistical tests used to analyze data that make fewer assumptions about data, e.g. non-normal distribution of scores.
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