Statisticians often come across outliers when working with datasets and it is important to deal with them because of how significantly they can distort a statistical model. Your dataset may have values that are distinguishably … The post How to Remove Outliers in R appeared first on ProgrammingR. [Read more...]

In statistics, it is often necessary to not only model data but test that model as well. To do this, you need to randomly separate the data into two groups ensuring even samples regardless of … The post Validate Me! Simple Test vs. Holdout Samples in R appeared first on ProgrammingR. ... [Read more...]

In statistics, it is often necessary to not only model data but test that model as well. To do this, you need to randomly separate the data into two groups ensuring even samples regardless of … The post Validate Me! Simple Test vs. Holdout Samples in R appeared first on ProgrammingR. [Read more...]

In 2018 I restarted with the Johns Hopkins University Data Science Specialization of Coursera with certificates. In May 2019 I finished the 10 course program that covers the Data Science process from data collection to the production of Data Science products and all done in R. The 10 cources are: Course 1: The Data Scientist’... [Read more...]

Executive Summary This is the Milestone Report for the Coursera Data Science Capstone project. The goal of the capstone project is to create a predictive text model using a large text corpus of documents as training data. Natural language processing techniques will be used to perform the analysis and build ... [Read more...]

I had to develop an RStudio shiny application as a part of final project in the Developing Data Products course in the Coursera Data Science Specialization track. The Shiny application calculates your maximum Heart Rate and the target Heart Rate zones for the chosen age. It includes: Its build with ... [Read more...]

“I appreciate your ambition, but we’re looking for an MBA…” My senior manager smiled and indicated the topic was closed. Despite the fact I was effectively running our direct mail program in the absence of … The post Zen and The Art of Competing Against MBA’s appeared first on ... [Read more...]

“I appreciate your ambition, but we’re looking for an MBA…” My senior manager smiled and indicated the topic was closed. Despite the fact I was [...] The post Zen and The Art of Competing Against MBA’s appeared first on ProgrammingR. [Read more...]

The First Date with your Data in R So you have your data, now what? With a little R code, you can quickly get to [...] The post The First Date with your Data in R appeared first on ProgrammingR. [Read more...]

To the typical reader, most technical resumes sound alike and share none of the unique personality behind the paper. For example, you may know that [...] The post How To Make Your Data Analyst Resume Stand Out appeared first on ProgrammingR. [Read more...]

One of my early programming projects in Python was a word game solver (example: word jumble solver) – the early version was a simple script, which grew [...] The post Simple Anagram Finder Using R appeared first on ProgrammingR. [Read more...]

This is the fourth installment in our series about web scraping with R. This includes practical examples for the leading R web scraping packages, including: RCurl package [...] The post Webscraping with rvest: So Easy Even An MBA Can Do It! appeared first on ProgrammingR. [Read more...]

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Building a Shiny App to explore the model and the data About the Shiny App In my previous post I built several models to try to predict the amount of residential solar installed per county by quarter as a function of solar insolation, price of solar electricity, county population and ... [Read more...]

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This program takes a data set of drug utilisation of 4 fictional drugs in 10 fictional hospitals and plots each time-series with a locally weighted regression (Lowess) trend line. It also places an time-series trend of the usage for each … Continue reading → [Read more...]

Here is the code that fixed up the World Bank data export for use in Tableau. The databank spits out everything in an untidy format for grouping and aggregating. The reshape2 and plyr packages  make it easy to manipulate the whole set … Continue reading → [Read more...]