Following the interest in our Twitter Tongues map for L

The yhat blog lists 10 R packages they wish they'd known about earlier. Drew Conway calls them "10 reasons to always start your analysis in R". They're all very useful R packages that every data scientist should be aware of. They are: sqldf (for selecting from data frames using SQL) forecast (for easy forecasting of time series) plyr (data...

Does what it says on the tin. DOWNLOAD THE CODE #------------------------------ #-------- INFORMATION --------- #------------------------------ # Plotting points from Hugh # Rallinson's "Using Geochemical # Data" book. Code compiled by # Darren J. Wilkinson, # Grant Inst. Earth Science # The University of Edinburgh # [email protected] #------------------------------ # -------- CONTROLS ---------- y.max = 16 x.min

This post will describe linear regression as from the book Veterinary Epidemiologic Research, describing the examples provided with R. Regression analysis is used for modeling the relationship between a single variable Y (the outcome, or dependent variable) measured on a continuous or near-continuous scale and one or more predictor (independent or explanatory variable), X. If

We take on a reader question of whether the stadium / home team matters for making a field goal. We pulled up the data on every field goal since 2002 (over 10,000) of them and plotted the probability of scoring as a function of the stadium in which the field goal was kicked. The post Stadium / home...

This semester I’m taking the live version of the Data Analysis class by Jeff Leek. His more popular version of the course is available through Coursera. One of the things that Jeff promotes is reproducibility and sharing code. I share that tendency and thus created a Git repository for my homework and code for the class: lcollado753. I’m...

The R package PApages is a great start towards addressing the very common problem of internal and external reporting in the money management industry. Advent's APX, Axys, and Black Diamond and the up and coming extremely well-connected and well-f...

A common criticism of R, especially from data scientists who are new to R but proficient in multiple programming languages, is that R is “quirky” and annoying because there is almost always more than one way to do simple things. I usually counter that they are trying to say that R is “flexible” and “rich”, but by the time...