title: CAN'T MISS--conquer any number task by making important statistics simple. Part 1. Types of variables, mean, median, variance, and standard deviation.
abstract: Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 1, presents basic information about data including a classification system that describes the four major types of variables: continuous quantitative variable, discrete quantitative variable, ordinal categorical variable (including the binomial variable), and nominal categorical variable. A histogram is a graph that displays the frequency distribution for a continuous variable. The article also demonstrates how to calculate the mean, median, standard deviation, and variance for a continuous variable.
authors: Group Health Cooperative of South Central, Wisconsin, Madison, WI, USA. john_hansen@ghc-hmo.com
authors: John P
authors: JP
authors: Hansen
mesh_terms: D000704:Analysis of Variance; D001795:Blood Pressure Determination / Q000706:statistics & numerical data; D003625:Data Collection; D003626:Data Display; D003627:Data Interpretation, Statistical; D003710:Demography; D003920:Diabetes Mellitus / Q000097:blood; D006442:Glycated Hemoglobin / Q000032:analysis; D006302:Health Services Research / Q000706:statistics & numerical data*; D006801:Humans; D016008:Statistical Distributions; D017749:Total Quality Management / Q000706:statistics & numerical data*
chemical_list: D006442:Glycated Hemoglobin