Titlebook: Introduction to Statistics and Data Analysis; With Exercises, Solu Christian Heumann,Michael Schomaker,Shalabh Textbook 2022Latest edition

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Causalitycteristics of the underlying populations generating the data (Parts II and III). We introduced concepts of association, correlation, dependence and independence, conditional and marginal probabilities, likelihood, odds ratios and other notions to understand the joint behaviour of variables.

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Frequency Measures and Graphical Representation of DataIn Chapter 1, we highlighted that different variables contain different levels of information. When summarizing or visualizing one or more variable(s), it is this information which determines the appropriate statistical methods to use.

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Measures of Central Tendency and DispersionA data set may contain many variables and observations. However, we are not always interested in each of the measured values but rather in a few summary measures of the data. Statistical functions fulfill the purpose of summarizing the data in a meaningful yet concise way.

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Linear RegressionWe learnt about various measures of association in Chap.?.. Such measures are used to understand the degree of .?or .?between two variables.

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Logistic RegressionIn Chap.?., we introduced?the linear regression model to describe the association between a metric response variable . and a metric covariate ., assuming a linear relationship between . and . at first. Note that a random variable is typically denoted in uppercase, say ., and its realization is denoted in lowercase, say ..

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