A Statistical Analysis on Climatic Temperature Using Exponential Moving Average
The behaviour of nature is still under the observation of science. Some of the features of the nature are in a pattern, and some are not. So to predict the lunatic behaviour of the nature, scientific algorithms like exponential moving average and methods like basic fundamental of time sequence analyser, i.e. Fibonacci series, are modelled theoretically in this paper to analyse the behaviour of temperature by feeding the temperature data of a certain selected area, collected over a certain period of time.
KeywordsExponential moving average (EMA) Weighted exponential moving average (WEMA) Fibonacci sequence Fahrenheit Celsius Temperature Greenhouse gases
- 1.GILLIAN L. HUGHES, SUHASINI SUBBA RAO AND TATA SUBBA RAO, School of Mathematics, University of Manchester, Manchester M60 1QD, UK 2 Texas A&M University, College Station, TX 77843-3143, USA, School of Mathematics, University of Manchester, Manchester M60 1QD, UK 2 Texas A&M University, College Station, TX 77843-3143, USA.Google Scholar
- 2.Stanley Dash, A Comparative study of moving averages: Simple Weighted and Exponential, Trade Station Labs Analysis Concepts, Issue 38 Wednesday, May 9,2012.Google Scholar
- 3.Lynn D. Newton, Fibonacci and Nature: Mathematics Investigations for Schools, The Mathematical Association, Vol. 16, No. 5 (Nov., 1987), pp. 2–8.Google Scholar
- 4.Omotehinwa T. O, Ramon S.O, Fibonacci Numbers and Golden Ratio in Mathematics and Science, International Journal of Computer and Information Technology (ISSN: 2279 – 0764) Volume 02–Issue 04, July 2013.Google Scholar