Managing energy costs in schools
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Added on 2020-01-23
Managing energy costs in schools
Added on 2020-01-23
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Table of ContentsINTRODUCTION...........................................................................................................................3a. Descriptive statistics of school size, age of buildings, energy efficiency and expenditure onenergy saving capital across all schools......................................................................................3b. Analyzing the extent to which energy efficiency, expenditure on energy saving capital andthe age of the main boiler differs by type of school....................................................................7c. Analyzing the relationship between energy efficiency and to total expenditure on savingcost...............................................................................................................................................9d. Analyzing the extent to which two variables are related with each through the means of chi-square test..................................................................................................................................10CONCLUSION..............................................................................................................................11REFERENCES..............................................................................................................................12APPENDIX....................................................................................................................................14APPENDIX 1.............................................................................................................................14b.................................................................................................................................................14Appendix 2.................................................................................................................................14b. 2nd Hypothesis........................................................................................................................14Appendix 3: 3rd Hypothesis........................................................................................................15Appendix table 4: Computation of chi-square test....................................................................16
INTRODUCTIONData analysis may be defined as a process which in turn provideshigh level of assistancein determining suitable solution from the given data set. Statistical and non-statistical are themain tools that are undertaken by researcher for assessing the research issue more effectively andefficiently. In the present study, data in relation to theenergy aspect ofinfant to nursery, primaryand secondary school has been evaluated by the scholar through the means of excel. Hence, thepresent report will shed light on the manner through which large amount of data can be analyzedin a highly structured way. Further, it will also provide deeper insight about themanner throughwhich excel tools facilitate effective decision making. Report will highlight the extent to whichexcel options help in simplifying the large data set in a highly structured way. It also depicts howstatistical tool such as correlation assists in testing hypothesis. a. Descriptive statistics of school size, age of buildings, energy efficiency and expenditure onenergy saving capital across all schoolsDescriptive statistics: It is one of the most effectual tools which provide deeper insightabout the mean, mode, median, minimum and maximum value. Hence, descriptive statistics toolhelps in summarizing the data set in the best possible way (Shirakawa, Abe and Ito, 2016). Bytaking into consideration such tool researcher can also assess the extent to which data set willdeviate in the future. In this way, descriptive statistics tool renders information about thevariabilityas well as mean and middlevalue. In order to provide school manager with highly effective solution for decision makingsample of 84 has been undertaken by the scholar.Hence, data in relation to the various aspectshave been gathered such as age of building, boiler, average building efficiency, energy savingexpense etc. Thus, by evaluating allquantitative data set researcher can provide personnel witheffectual framework for decision making. In this, by making assessment of data through themeans of excel researcher can present fair outcome of issue which is going is to be investigated.The rationale behind the selection and use of excel is to arrange and determine suitable solutionfrom the given data set (Holcomb, 2016).
Calculation of descriptive statistics Elements ofdescriptivestatistics SchooltypeAge ofbuildingTotalexpenditureon energysavingcapital since2011Mean1.9052.957485.81Standard Error0.073.26806.20Median2.0049.006207.00Mode2.0039.000.00StandardDeviation0.6429.677344.86Skewness0.080.780.91Range2.00132.0028202.00Minimum1.005.000.00Maximum3.00137.0028202.00Sum158.004395.00621322.00Count83.0083.0083.00Table 1: Calculation of descriptive statistics School type
Infant & NurseryPrimarySecondary0102030405060Frequency on the basis of Type of school Frequency School Type Graph 1: School typeThe above depicted graphical presentation shows that frequency of primary school washigher such as 49. Out of the number of 84, frequency of infant and secondary school accountsfor 21 and 13. Thus, it can be stated that in survey, most of the participants belonged fromprimary school rather than others. Age of building 5-1415-2425-3435-4445-5455-6465-7475-8485-9495-104105-114115-124125-134135-144024681012141618Frequency Frequency Age FrequencyGraph 2: Age of building
Graph clearly shows that age of 14 building was approximately within the range of 35-44years. On the other side, 17 buildings were in the age of 55-64 years at the time of 2015. Thus,buildings which were undertaken for the purpose of study considered as too old approximately31. Total expenditure on energy saving 04178972,7303,9924,5516,2077,3277,9038,80210,21012,15613,50316,50618,64023,30028,202024681012141618frequency frequency In £FrequencyGraph 3: Total expenditure on energy savingBy doing assessment of data set, it has been found that mean expenses incurred on savingtotal energy accounts for £7485.81 respectively. On the other side, middle level expenditureimplies for £6207 significantly. Further, amount of standard deviation accounts for £7344.86which entails that in the near future expenses related to total energy saving will deviate fromsuch aspect. Building energy efficiency Particulars2014201320122011Mean195.095213.758194.243201.375
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