Data Analysis and Inductive Modeling is a wonderful tool to use for anybody involved with statistics and predicting upcoming events. With data analysis skills anybody can take a seeming random set of data and turn it into something with real meaning. For example, the 1st set of data we received for Lab 9, may have just seemed like a weird array of sea level changes, but after using data analysis and figuring out the linear regression, the data showed that the sea level is increasing at an alarming rate and will continue to grow at this rate in the foreseeable future. With data analysis, people can actually predict future problems and attempt to stop them before they actually occur. Although it's not a perfect science, using data analysis can find out trends that will help solve problems that some may have never seen coming, which is an extremely valuable tool in today's world.
In Lab 9, I learned several methods that can be used for data analysis, the main method being Linear Regression. This method allows you to take a set of data and actually put a line of best fit to a seemingly random scatter plot, so that you can infer any growing trends that the specific data is telling you. There is some error, but by using the Analysis Tools in Microsoft Excel, you can see how much error occurs and whether or not this is a viable trend or not. This skill will be very valuable in the future if I need to analyze any other sets of seemingly random data.
Shannon's measure of Entropy is the average shortest average message in bits that a certain amount of information can be conveyed with out any information loss. The Entropy measures how much information is lost in data compression and uses specific Algorithms to measure this.