ST 260 Lecture Notes - Lecture 3: Interquartile Range, Variance, Quartile
9 May 2017
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Document Summary
Introduction: population of interest: things we wish to learn about, key characteristics: typical value of variation, parameters: true values for a population. Key features of data distributions: shape, typical value, spread, outliers. First principles: numerical summaries should quantify key characteristics of a data set. Measures of location/center: mean: works best with symmetric distributions. Sum of the data values divided by the number of data values: median: skewed distributions or distributions with outliers. Middle value in the ordered data set: mode: categorical variables. The most frequently occurring value: trimmed mean: skewed distributions or distributions with outliers. Average of data values omitting the extremes. Key concepts: relationship between statistics and parameters, select appropriate numerical methods, calculate common numerical summaries of data. Objectives: calculate common numerical summaries of data, select appropriate numerical methods, describe the relationship between statistics and parameters. Measures of variance: sample standard deviation: symmetric distributions, sample variance: symmetric distributions.
