- Collection of methods for planning experiments, obtaining data, and then organizing,
summarizing, presenting, analyzing, interpreting, and drawing conclusions.
- Characteristic or attribute that can assume different values
- Random Variable
- A variable whose values are determined by chance.
- All subjects possessing a common characteristic that is being studied.
- A subgroup or subset of the population.
- Characteristic or measure obtained from a population.
- Statistic (not to be confused with Statistics)
- Characteristic or measure obtained from a sample.
- Descriptive Statistics
- Collection, organization, summarization, and presentation of data.
- Inferential Statistics
- Generalizing from samples to populations using probabilities. Performing hypothesis
testing, determining relationships between variables, and making predictions.
- Qualitative Variables
- Variables which assume non-numerical values.
- Quantitative Variables
- Variables which assume numerical values.
- Discrete Variables
- Variables which assume a finite or countable number of possible values. Usually
obtained by counting.
- Continuous Variables
- Variables which assume an infinite number of possible values. Usually obtained by
- Nominal Level
- Level of measurement which classifies data into mutually exclusive, all inclusive
categories in which no order or ranking can be imposed on the data.
- Ordinal Level
- Level of measurement which classifies data into categories that can be ranked.
Differences between the ranks do not exist.
- Interval Level
- Level of measurement which classifies data that can be ranked and differences are
meaningful. However, there is no meaningful zero, so ratios are meaningless.
- Ratio Level
- Level of measurement which classifies data that can be ranked, differences are
meaningful, and there is a true zero. True ratios exist between the different units of
- Random Sampling
- Sampling in which the data is collected using chance methods or random numbers.
- Systematic Sampling
- Sampling in which data is obtained by selecting every kth object.
- Convenience Sampling
- Sampling in which data is which is readily available is used.
- Stratified Sampling
- Sampling in which the population is divided into groups (called strata) according to
some characteristic. Each of these strata is then sampled using one of the other
- Cluster Sampling
- Sampling in which the population is divided into groups (usually geographically). Some
of these groups are randomly selected, and then all of the elements in those groups are
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