STAT 2230 Lecture Notes - Lecture 10: Dependent And Independent Variables, Scatter Plot, Standard Deviation
17 Dec 2015
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May explain or influence changes in a response variable. The goal in most studies is to show that changes in one or more explanatory variables cause changes in a response variable. Study looking at age and sex and ethnicity (independent variables) to determine height (dependent variable) Most useful way to display a relationship between two quantitative variables is a scatterplot. Response variable on vertical axis (usually called y) Described by direction, form and strength of relationship. Important deviation is an outlier which falls outside the overall pattern of relationship. Strength: how closely the points follow a clear form. Can plot two or more relationships on the same scatterplot using a different plot colour or symbol. Can allow visual interpretation of the effect a third variable can have on the relationship between x and y. Measures strength and direction of the linear relationship between two quantitative variables. We have data on variables x and y for n individuals.
