Rotimi-Williams Bello et al, International Journal of Computer Science and Mobile Computing, Vol.7 Issue.5, May- 2018, pg. 83-93 © 2018, IJCSMC All Rights Reserved 83 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 6.017 IJCSMC, Vol. 7, Issue. 5, May 2018, pg.83 – 93 PREDICTING DIFFERENCES IN TEMPERATURE DATA BY MODELING AND SIMULATION 1 Rotimi-Williams Bello, 2 Firstman Noah Otobo 1,2 Department of Mathematical Sciences, University of Africa, Toru-Orua, Bayelsa State, Nigeria 1 sirbrw@yahoo.com, 2 otobofirstman@yahoo.com Abstract: Temperature is defined as the degree of hotness or coldness of a body or environment (corresponding to its molecular activity). Therefore, the importance of temperature to man, agriculture, and aquatic life cannot be overemphasized. It is in this regard that we attempted to model two consecutive years minimum and maximum temperature differences of randomly selected locations in Niger state (case study) whose observations were available so that we could gain understanding of their effects on the environment and use this information for prediction purposes. This was achieved by setting up the model using regression analysis, graphs, gathered data, and simulation approach using C++ programming language. Having put into consideration all the necessary conditions that can affect variation in temperature data and the effect of such variation, we are sure that the temperatures differences model through the graph representations has successfully ease temperature prediction purposes, provided the data collected is accurately analyzed with the explanatory variables accurately applied. Though, this paper was able to fulfill its objectives, but due to some limitations that were certainly errors associated with the used data set among which are instrumental errors that can be systematic or random, we cannot totally guarantee accuracy. Keywords: Temperature; Modeling; Graphs; Regression analysis; and Data. I. INTRODUCTION While simulation is the technique of representing the real world by a computer program modeling means setting up a mathematical model of a physical or other system. The model may be a function to be evaluated or plotted or a differential or other equation to be solved. Some types of model like iconic model visually represent an idea or object, for example, illustration, picture and chart. Analogue model abstractly or concretely represent an idea or object, for example, public opinion poll that swings left and right. Symbolic model depends on the use of symbols by way of variables and functions etc. Function model consists of (1) descriptive model (2) normative model and (3) prescriptive model. Empirical modeling is based on data and formulated on data. Empirical models are not derived from assumptions or based on physical laws or principles, and it has the following steps when designing: i. Plot the data on a graph ii. Looking at the graph, the model can be derived. If the data is subject to measurement error and points seem to lie on a straight line, the line of best fit can be drawn.