ISDS 2000 Lecture Notes - Lecture 1: Categorical Variable, Standardized Test, Contingency Table
22 Oct 2014
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Document Summary
Qualitative or categorical data date that is places into categories, can be answered with a yes or no question. Numerical or quantitative data- represents quatities: discrete- counted data, continuous measured date. Nominal scale classifies data with no ranking: example: internet provider, type of stock owned. Ordinal scale classifies due to ranking: example: faculty ranking, bond rating. Interval scale the difference between measurements is relevant but has no true zero point: example: temperature, standardized test scores. Ratio scale the difference between measurements is relevant and has a true zero point: example: age, weight, height. Primary sources the data collector is the one using the data: example: political survey, data collected from an experiment. Secondary sources the data being used was collected by someone else: example: analyzing census data or anything found on the internet. Data falls into five categories: data from a survey, observational study, designed experiment, distributed by an organization or individual, collected from ongoing business.
