STAT 35000 Lecture Notes - Lecture 1: Univariate, Unimodality, Skewness

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Introduction chapter 1: statistics vs probability: Probability: we know about the sample size, and want to find out about population. Statistics: we know about the population and we want to know about the sample size: types of variables: Variables are characterized by: number of observations: Numeric(quantitative): ex: age: type, continuous- discrete variables are finite or are countable. Continuous variables are measured: discrete- continuous variables consist of intervals. Discrete variables are counted: interpretation of histograms, shape number of peaks in the graph, unimodal, bimodal, multimodal, skewness unimodal graphs can look different depending on the location of the peak: Skewed: variability (spread) how broad the range of data is, outliers: Any deviations in the data is called an outlier. It may be tempting to want to remove the outlier to show the pattern in the rest of the data but we must never do so. The outlier here is the last bar that is far away from the rest of the graphs.

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