Thank you all for the positive responses to Basics of JavaScript and D3 for R Users! Quick update: last time we had to dabble in a tiny bit of Python to start a local server, in order to actually run JavaScript … Continue reading →

Thank you all for the positive responses to Basics of JavaScript and D3 for R Users! Quick update: last time we had to dabble in a tiny bit of Python to start a local server, in order to actually run JavaScript … Continue reading →

Bayesian analysis has been growing in popularity among ecologists recently, largely due to accessible books such as Models for Ecological Data: An Introduction, Introduction to WinBUGS for Ecologists, and Bayesian Methods for Ecology. Most ecologists with limited programming background have … Continue reading →

Welcome to the last part of the series on predicting user’s revisit to the website. In the first part of series, I generated the logistic regression model for prediction problem whether a user will come back on website in next 24 hours. In the second part, I discussed about model improvement and seen the model accuracy.

Classes and objects in R Welcome back! In this blog post I'm going to try to tackle the concept of objects in R. R is said to be an “object oriented” language. I touched on this in my last post when we discussed the concatenate function c() and I'll go a bit beyond that this time. Speaking of the c() function, I'll begin this...

I was creating a dataset this last week in which I had to partition the observed responses to show how the ANOVA model partitions the variability. I had the observed Y (in this case prices for 113 bottles of wine), … Continue reading →

In business "Correlation" is generically used as a mutual relationship or connection between two or more things; statistically speaking correlation is the interdependence of variable quantities. I overhear many end users request information on the correlation of variables for prediction use, what they are referring to is actually simple linear regression. I don't mean to outline all

Today I want to show a simple example of how we can value a company using Discounted Cash Flow (DCF) analysis. The idea is to compute the company’s Intrinsic Value based on the discounted future cash-flows. To compute future cash-flows I will use the historical Free Cash Flow growth rate. To compute present value of

A common task using R is the investigation of one particular dataset. Usually we have a mixture of numerical and categorial data and are interested in some statistics (e.g. means and so on). And there are a lot of threads, blogs etc around that. Sorry for adding another one, but so I remember myself. Let’s

e-mails with the latest R posts.

(You will not see this message again.)