Special Topics in GIS Lab 10

The lab this week focused on regression and how to analyze data to determine predicted values. The focus this week was in Microsoft Excel rather than ArcGIS. The analysis was formula intensive, but allowed for a better understanding of how to use Excel to gather the data parameters you want for analysis. The Excel program also has a great tool that can be used to accomplish the majority of the regression analysis in one easy step.

This example sums up the processes we used in Excel this week. The goal is to determine if the data points you collect or are given have any correlation and if so how well are the values predictors for each other. In our example two stations reported rainfall annually for a given number of years. One station failed to report for a span of years and it is your job to predict the missing amounts to complete the dataset. In order to do that you perform a regression analysis on the rest of the data to find the slope and intercept value of a "trendline" for the data. This line equation can then be used to enter your x-values from one station and find our y-values for the missing station numbers. The values will not be perfect, but they will be predictions in line with the rest of the data.