Univariate, Bi-variate and Correlation analysis

In this article, we attempt at formalizing this intuitive approach into few more concrete steps using happiness data, internet usage per population, and mathematics proficiency among the 15 year-old students.

Explanatory Data Analysis with Beautiful Visualization and Interesting Findings. Now I will share recent work in the human resource domain to bring some predictive power to any firm struggling to retain their employees. In this first post, I will focus on exploring datasets for any interesting patterns.

Covid-19: Correlation Between Confirmed Cases and Deaths. After how many days we reach the Maximum Correlation between Confirmed (Covid-19) Cases and Deaths

An analysis of current methods and a proposed solution. In this article, I will be demonstrating the shortcomings of current methods and proposing a possible solution.

Using regression with correlated data. Tutorial (including R code) for using Generalized Estimating Equations and Multilevel Models.

Three Questions You’ve Had About Correlations. What’s good, why yours isn’t good, and how to judge causation.

Using The Predictive Power Score in R: Recently a post about Predictive Power Score attracted the attention of many data scientists. Let’s see what it is and how to use it in R.

False Positives(FP) , False Negatives(FN) , True Positives(TP) and True Negatives(TN) are the kind of evaluation metrics which are used to define difference between the prediction made by Humans.

Almost every person in data science or Machine Learning knows that one of the easiest ways to find relevant features for predicted value y is to find the features that are most correlated with y. However few (if not a mathematician) know that there are many types of correlation. In this article,

Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together. Positive Correlation indicates the extent to which those variable increase.

Variable Selection in Regression Analysis with a Large Feature Space: Feature selection in regression analysis using Fisher z-transformations of correlation coefficients and Euclidian distance.

From the 1st COVID-19 case appears in a country, this virus has penetrated into different communities at a different rate among different countries.

Improve your model’s accuracy with a few lines of code and avoid this common pitfall. You do not need to be a Data Scientist to know this feeling.

In a parallel universe, our wish would be to carry out portfolio management only using patterns hidden in the past to anticipate future price changes.

Statistical features, a popular statistics concept for data science, comes into play during the data exploration phase and includes topics such as bias, variance, mean, median, and percentiles. When looking at the basic box plot below, the minimum and maximum values represent the upper and lower ends of the data range.

This post will show you how to write your own function to tidy the many…

In this article, I’ll talk about the difference between Correlation and Causation and how these two terms are different and what exactly they convey.

Let’s dive right in as I review correlation vs causation psychology and describe the main differences between these two common terms.Are there any other correlation and causation examples you’d like to hear more about on the Troop Messenger blog? Is there correlation vs causation analyses that you’re interested in within the broader realm of digital marketing and search engine optimization? Let us know in the comments.