 Welcome to the EME 210 Data Analytics for Energy Systems course. My name is Renee Obringer and I am an instructor for this course. I'm also an assistant professor in the Department of Energy and Mineral Engineering. I'm going to talk about some of my ongoing research and some of the work that I have done that leverages techniques you'll learn in this class. So to give an overview of how I go about my research, I start with data collection and then I use these statistical techniques and data analysis to build models, train and test and figure out what's going on and then if I'm interested in the climate change impacts I'll take that future climate data, simulate it and add it to my model to see what the impact might be to our system. In this class however you'll be focusing on these first two steps where you'll collect the data and then you'll implement some statistical analysis to make an inference or answer a question. For example, one of the research projects that I did was to look at how air conditioning use might change in the future under different climate change scenarios. Here I'm showing these bar plots across the entire US and they represent the average increase in air conditioning use for a household in a given state. If we look at Pennsylvania we can see that after one and a half degrees of warming above pre-industrial levels, the average household could expect to see a 7% increase in their average usage of air conditioning across the summer whereas after two degrees of warming that jumps up to 10.2% increase. And so this is quite a bit if you think about how much you use, how your air conditioning or electricity bill increases in the summer, imagine it getting even higher because it's so much warmer out we're running those systems for longer and longer. And so this is an example of using a complex tree-based method to do a prediction and then later implement climate change data to see how that might change in the future. And you'll learn the introduction to these tree-based methods towards the end of this course. A second analysis that I've done has focused instead of the entire US zooming in to a few select cities, particularly in the Midwest. And so here looking at how water and electricity use might change under climate change. And to give you some examples of the results, here I'm showing Chicago and Indianapolis and we can see that there is an increase in both electricity and water use across both cities due to climate change. And to demonstrate this increase, I've once again used these bar plots, which you'll learn during the visualization portion of this lecture. And so these are just some examples of how to use some of this energy data that you'll be collecting in class and how to implement these complex techniques to answer real-world questions.