Statistical Sciences 1024A/B Lecture Notes - Lecture 11: Design Of Experiments, Dependent And Independent Variables, Marginal Distribution
26 Oct 2018
School
Department
Professor
Document Summary
An association between an explanatory variable x and a response variable y, even if it is very strong, is not by itself good evidence that changes x. Remember= associations become stronger close to -1 and +1. Carry out a designed experiment by manipulating the explanatory variable x to see what happens to the response variable y. Recognize when the correlation/regression is performed on averages. A relationship, however strong, does not itself imply causation. The marginal distribution of one of the categorical variables in a two-way table of counts is the distribution of values of that variable among all individuals described by the table. Marginal distribution is basically the spread of values of all individuals in the table. A conditional distribution of a variable is the distribution of values of that variable among only individuals who have a given value of the other variable. There is a separate conditional distribution for each value of the other variable.
