Some common questions that every datascience enthusiast should know. … More Top 15 Questions to test a Datascience Enthusiast
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As the world is getting more tech savvy and advancements made in the information technology especially in the healthcare industry has opened areas in data mining and machine learning. Within the area of data mining one technique which has gained a lot of popularity as well as skepticism amongst the auditors and fraud detectives is … More Health Care Industry’s Savior: Benford’s Law “The Law of the First Digit”
Linear Model better known as linear regression is one of the most common and flexible analysis framework to identify relationship between two or more variables. The widely used linear model is represented by drawing the best fit line through a series of data points represented on a scatter plot. For any budding business analyst this … More Deducer Tutorial: Creating a Linear Model using R Deducer Package
Multicollinearity (Collinearity) is not a new term especially when dealing with multiple regression models. This phenomenon of relationship in between one response variable with the set of predictor variables also include models like classification and regression trees as well as neural networks. Collinearity is infamously famous for inflating the variance of at least one estimated … More How to Deal with Multicolinearity
As we all know CRISP DM stands for Cross Industry Standard Process for Data Mining is a process model that outlines the most common approach to tackle data driven problems. Per the poll conducted by KDNuggets in 2014 this was and “is” one of the most popular and widest used methodology. This method of gleaning … More Useful R Packages That aligns with the CRISP DM Methodology
Selecting the right statistical test can prove to be a daunting task for anyone. This infographic presents a step by step approach for the test selection process. This way of looking at various conditions to pick the appropriate tests will allow the audience to visualize and remember the process easily. However, it is also very … More Simple Guide for Selecting Statistical Tests When Comparing Groups
It is not only about understanding about statistics, it is also about implementing the correct statistical approach or method. In this brief article I will showcase some common statistical blunders that we generally make and how to avoid them. To make this information simple and consumable I have divided these errors into two parts: Data … More The Most Common Analytical and Statistical Mistakes
Best Subset Regression method can be used to create a best-fitting regression model. This technique of model building helps to identify which predictor (independent) variables should be included in a multiple regression model(MLR). This method comprises of scrutinizing all of the models created from all possible permutation combination of predictor variables. This technique uses the … More How to create a best-fitting regression model?