This is a repo for the GWU Intro to Data Science Project 2 that looks at climate change data using R statistical programming. In this analysis of climate change, we investigate the linear relationship between global average temperature and time. We use linear regression to establish this relationship.

We gathered climate data from Berkeley Earth, and focused on global land temperatures for the analysis. Data are available from 1750-2013. In preparing the data, we transformed from Celsius to Fahrenheit. There were 12 missing data points in years 1750 and 1751; these years were omitted from analysis.

Data is hosted in a Google Cloud Platform at the following links as well as can be found in our repo:

• GlobalLandTemerpaturesByCity.csv: https://storage.googleapis.com/global_land_temperatures/GlobalLandTemperaturesByCity.csv
• GlobalLandTemerpaturesByCountry.csv: https://storage.googleapis.com/global_land_temperatures/GlobalLandTemperaturesByCountry.csv
• GlobalLandTemerpaturesByMajorCity.csv: https://storage.googleapis.com/global_land_temperatures/GlobalLandTemperaturesByMajorCity.csv
• GlobalLandTemerpaturesByState.csv: https://storage.googleapis.com/global_land_temperatures/GlobalLandTemperaturesByState.csv
• GlobalLandTemerpatures.csv: https://storage.googleapis.com/global_land_temperatures/GlobalTemperatures.csv