Real World Analytics - Assignment Sample

Added on - 14 Jun 2021

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Running head: REAL WORLD ANALYTICSREAL WORLD ANALYTICSName of StudentName of University
REAL WORLD ANALYTICS1Table of ContentsPart A:..............................................................................................................................................2Description...................................................................................................................................2Task 1...........................................................................................................................................2Task 2...........................................................................................................................................8Task 3...........................................................................................................................................8Task 4...........................................................................................................................................9Part B.............................................................................................................................................101.................................................................................................................................................10
REAL WORLD ANALYTICS2Part A:DescriptionHeating load and cooling load serve to guide the specifications of equipment for heatingand cooling that are installed buildings. Therefore they are key variables to consider whiledesigning energy efficient buildings when considering how to optimize energy consumption.The variables Heating load (Y1 or HL) and cooling load (Y2 or CL) are two variablesbeing considered to be of interest in this paper. The independent variables, viz., relativecompactness(X1) in percentage(in decimals),the surface area(X2) ,expressed in squared meter,the wall area(X3) in square meter, the roof area(X4) in squared meter and finally the overallheight(X5) in meters are being considered as potential influences on the chosen response. Theanalysis was done in R using a sample of size of 300.Task 1Following instructions, the data fileENB18data.txtwas downloaded from CloudDeakininto the R. Cooling Load or Y2 was selected as the variable of interest. The influence of thevariables X1, X2, X3, X4 and X5 on Y2 and their individual natures were analyzed on the basisof the chosen sample and hence discussed.The graphical descriptive summary of the variables and the relationships between thecooling load and the variables X1, X2, X3, X4 and X5 are given as follows.The histogram of the variable cooling load measured in the unit KWh per square meterper annum is seen to have distribution which is skewed right with most values are seen to betowards the left tail or the lower side of the X-axis making its left tail more steep and right tailflatter and elongated than its left. The values lie between 10 to 50 KWh per square meter withmode being between 15 - 20KWh per square meter.
REAL WORLD ANALYTICS3Figure 1The relative compactness values are observed to be between 0.6 and 1. The distribution ispositively or right skewed.Figure 2
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