DOI link for Applied Statistics
Applied Statistics book
Statistics is a branch of mathematics used to demonstrate research findings, support hypotheses, give credibility to research methodology, and draw conclusions. The objective of the statistics is estimating the parameters and designing the mathematical model from collected or measured data and analyzing the performance of the predicted model. The statistics is categorize as descriptive and inferential statistics, where the descriptive statistics helps in analyzing a data by evaluating frequency of occurrence, its central tendency, coefficient of variation and its positional information and the statistical inference is an estimation theory used to estimate values of parameters such as mean, deviation, variance, or correlation coefficients from randomly empirical data. Thus unknown parameters are estimated using measurement techniques. The automated tools such as STATISTCA and UNICORN are available for performance analysis, uncertainty, and sensitivity analysis of data. This chapter describes and demonstrates the significance and principles of various statistical tools such as regression, estimation, principal component analysis (PCA), support vector machine (SVM), uncertainty, and sensitivity analysis. The selection of statistical methodology includes a selection of suitable measures or parameters, a selection of evaluation methodology, and analyzing data for drawing reliable conclusions by defining appropriate system models. It helps the researcher in understanding how to plan, conduct, and evaluate research.