STA215H5 Chapter Notes - Chapter 6: Confounding, Scatter Plot, Dependent And Independent Variables
Document Summary
When we plot one quantitative variable versus another quantitative variable, the resultant graph is called a scatterplot. If as x increases, y also increases, the relationship is called a positive association. Lurking variables are hidden variables that lurk or stand behind an analysis but may have an important influence on the relationship being studied. Just looking at scatterplots, you can see patterns, trends, relationships, and even the occasional extraordinary value sitting apart from the others. Scatterplots are the best way to start observing the relationship between two quantitative variables. When you ask questions that relate one quantitative variable to another (ex. ), you"re asking whether there is an association between them scatterplots are the ideal way to picture such associations. When the x-variable is time, the scatterplot becomes a timeplot: timeplots can show quite complex patterns, such as cyclical and seasonal patterns, often requiring time series methods of analysis.
