Dataset comprised of seven variables describing different aspects of energy use associated with buildings in a different Chicago community. The variables are: • Area = The total interior floor space (ft2), not including any interior space used for parking. • Water = Annual water use in thousands of gallons. • EScore = A rating (1 100) to assess a property's overall energy performance; it's based on national data that controls for differences in climate, building uses, and operations. • Electricity = Annual electricity use (kBtu), including electricity purchased from the grid and generated by onsite renewable systems. ⚫NG = Annual utility-supplied natural gas consumed on-site (kBtu). ⚫ EUI = Energy Use Intensity (kBtu/ft2); the annual energy used at the property, including losses from generation, transmission, and distribution, normalized to the area. • GHG = Annual greenhouse gas emissions (metric tons CO2), including carbon dioxide, methane, and nitrous oxide gases released into the atmosphere as a result of energy consumption at the property. The case study has three parts: • Part 1 - Each member of the team should create a statistical summary for one of the following variables: Water, Electricity, NG, GHG, or EUI. Only one team member should create a statistical summary for each of those variables. The statistical summary should include:/nThe case study has three parts: • Part 1 - Each member of the team should create a statistical summary for one of the following variables: Water, Electricity, NG, GHG, or EUI. Only one team member should create a statistical summary for each of those variables. The statistical summary should include: o A table showing minimum, median, mean, standard deviation, and maximum o A histogram o A boxplot o A recommended parametric distribution model for the variable, including parameters for that model, and statistical and graphical information that explains why that model is appropriate. o A simple linear regression model describing the relationship between their variable and the Area variable. Summarize results from that model by describing: Model parameter values; statistics used to assess the quality of the fit; and analysis of the residuals. o Each team member should turn in a summary (≤ 4 pages)

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