Principle of Business Analytics

Question: Discuss about thePrinciple of Business Analytics. Answer: Introduction The present task involves an analysis of the different descriptive techniques used for business analytics. The business analytics process uses different types of descriptive statistical techniques. Some of the techniques are discussed as follows: Univariate Methods Numerical Techniques Technique : Median Purpose : the median divides the set of data points into two equal halves, such that half of the data points are above the value and half are below the value. Functionality : Arrange all the number in ascending order. If the total number of data in the data set is odd then the median is the middle number. When the total number of data in the data set is even then the median is the mean of the middle two numbers Assumptions : It is assumed that the data is normally distributed. Method of Validation : the data is plotted on a histogram and checked for normality of the data. The median point would divide the normal histogram into two equal halves. Sample use case : find the median in family income (Ackerman, Fries and Windle 2012). Technique : Standard Deviation Purpose : To find the dispersion of the data points from the mean Functionality : Find the mean. Subtract the data point from the mean. Square the results of the subtract. Find the mean of the squared result. Assumptions : It is assumed that the data is normally distributed. Method of Validation : find the standard deviation to predict the dispersion of the data points. Sample Use Case : find the dispersion in service time at hospitals (Gijo and Antony 2014). Graphical Method Technique : Box Plot Purpose :For the purpose of comparing of two or more data sets. Functionality : calculate the five numbered summary. Create a line plot of the five numbered summary. Create a box from the 25th to the 75 percentile summaries. Mark a vertical line at the median summary. Assumptions : It is assumed that the data is normally distributed Method of Validation : create the box plots and compare the five numbered summaries Sample Use Case : compare the median values of release of CO2 and NOx based on date of manufacture (Carslaw et al. 2013). Bivariate Methods Technique : Regression Analysis Purpose : to formulate the relationship between the independent variables and the dependent variables. Functionality :find the product of the dependent variable and independent variable. Find the square of the dependent variable and independent variables. Calculate the intercept and the slope of the regression line. Assumptions : the data is normally distributed. Method of Validation : find the regression equation and predict the dependent variable. Sample Use Case : to predict the future energy consumptions in a supermarket (Braun, Altan and Beck 2014). References Ackerman, R.A., Fries, G. and Windle, R.A., 2012. Changes in US family finances from 2007 to 2010: Evidence from the Survey of Consumer Finances. Federal Reserve Bulletin, 100, pp.1-80. Braun, M.R., Altan, H. and Beck, S.B.M., 2014. Using regression analysis to predict the future energy consumption of a supermarket in the UK. Applied Energy, 130, pp.305-313. Carslaw, D.C., Williams, M.L., Tate, J.E. and Beevers, S.D., 2013. The importance of high vehicle power for passenger car emissions. Atmospheric Environment, 68, pp.8-16. Gijo, E.V. and Antony, J., 2014. Reducing patient waiting time in outpatient department using lean six sigma methodology. Quality and Reliability Engineering International, 30(8), pp.1481-1491.