Reclassifying inferential statistics into diagnostic and predictive statistics with an application on gynecologic cancer

Abstract

Statisticians use to classify Statistics into two main parts, namely Descriptive and Inferential Statistics. Here, we suggest reclassifying Inferential Statistics into two parts, namely Diagnostic Statistics and Predictive Statistics. Based on that we will have four levels to analyze data (Descriptive, Diagnostic, Predictive and Perspective Statistics). Descriptive statistics mainly related to Graphs, Frequency tables, Measures of Central Tendency, Measures of Variation and Measures of Shape. Diagnostic statistics mainly related to the effects of the Independent variables (inputs) on the Dependent (Target) variable based on the Tests of Correlation or Association, Tests for Means differences and Tests for Classification. Predictive statistics mainly related to Estimation, Regression techniques and Time series Analysis for the Dependent (Target) variable. Perspective statistics mainly related to the previous three levels and acts as a prescription to how to solve or prevent the problem. In this paper, we will clarify the statistical tests used in each level of statistical analysis and will give an example on a real data related to Gynecologic Cancer