GIS5935 - Lab 10 - Introductory Statistics, Correlation and Bivariate Regression

This weeks lab had us focus on reviewing fundamental statistics and how to perform linear regression analysis.  The lab was divided into three parts where we performed various statistical analysis tasks on provided data sets.  In part C of the assignment we determined the relationship between the annual precipitation amounts collected at two different stations over a series of years (1931-2004).  Initially, we are provided with precipitation amounts for both stations from 1950-2004.  Using this data we are able to perform linear regression analysis to determine the slope and intercept.  For years 1931-1949 we only are provided with precipitation amounts for Station B.  Using the information gathered from the linear regression analysis we are able to predict the precipitation amounts for Station A for the years 1931-2004.

Bivariate Linear Regression To Predict Annual Rainfall Amounts At Station A From Values Obtained At Station B

Using bivariate linear regression analysis to predict the value of one variable from the value of another, assumes that all data is continuous and normally distributed.  "The relationship is assumed to be linear and for now only uses two variables and does not consider any spatial effects."