Levels of Measurement & Frequency Distributions PDF
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Uploaded by TransparentMusicalSaw1414
Hamilton College
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Summary
This document discusses various levels of measurements, such as nominal, ordinal, interval, and ratio scales, and explains how frequency distributions are used to describe data. It provides an overview of population,sample and how variables are described. It's suitable for introductory studies in statistics.
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Levels of Measurement & Frequency Distributions Population — set of all individuals of interest in a particular study ○ Describe using a parameter Types: frequency counts, means, standard deviations Sample — set of indiv...
Levels of Measurement & Frequency Distributions Population — set of all individuals of interest in a particular study ○ Describe using a parameter Types: frequency counts, means, standard deviations Sample — set of individuals selected from a population, usually intended to represent the population in a study — for lab experiments, generally NOT a random sample (usually a convenience sample) ○ Describe using a statistic correlations, t tests, ANOVAs, chi-square tests Because it’s usually impossible to study entire populations, we estimate population parameters using sample statistics Review of how variables are described ualitative: Interpretation-based, descriptive, relating to language Q Quantitative data: Numbers-based, countable or measurable Categorical: A variable that is not numerical - instead it is based on a qualitative property, such as color, breed, or gender, among others Numeric variables: Have values that describe a measurable quantity as a number such as “how many” or “how much” Discrete: A finite number that can be counted (12 naps) Continuous variables: an infinite number of possible values that can be measured (145.5 pages) What Can We Do to Reduce the Amount of Error in our Inferences? 1. Strive for a representative sample (i.e., as much like the broader population as possible). Hard to do this for experiments! Often have to rely on convenience samples. 2. Use relatively large samples BUT: Representativeness is more important than size! Better U.S. election estimate with representative sample of 200 voters than with unrepresentative sample of 1 million voters Four Levels of Measurement Nominal Use numbers merely as labels for categories (No = 1, Yes = 2) (apples = 10, oranges = 11, grapes = 12) Ordinal Categories are ranked in terms of size or magnitude (sml, med, jumbo) You cannot tell if the distance (amount) between categories is equal. Interval Has ordinal properties, PLUS: all categories form intervals that are exactly the same size. No absolute zero point, so ratios of scores aren’t meaningful. Ratio Has interval properties, PLUS: a “true” zero point, ratios of scores are meaningful.
