Descriptive Statistics Analysis Of The Variable In The Data Of Toothbrushing Simulator System Modelling

The controller of a system can be designed by constructing the model from the known the input and output. Modelling the dynamic of the system can help to visualize the real behavior of the system to develop the suitable controller parameter. The measured data from the real system need to be analyzed statistically to support that the current system needs a controller to improve the system performance. This study analyzed the normality and linearity of the variables in the research data of Toothbrushing Simulator System Modelling which are Speed (RPM) as the output(Y) and Voltage (V) as the input (X). There were five different data sets with 1000 observations respectively. All the data had been analyzed by using IBM SPSS Statistics 23 in which it will be explained by graphical method of histogram, scatter plot and descriptive measures of coefficient f determination between variables. The results for this study turn out that all the data sets were not normally distributed and not linear. Hence, the result from this statistical analysis has proven that the controller development is very crucial for the toothbrushing simulator system to improvise the system performance.