From external sources. For more articles, click here. The chart below is from the article flagged with a +.

  1. What’s the probability that a significant p-value indicates a true ... - If the p-value is < .05, then the probability of falsely rejecting the null hypothesis is  <5%, right? That means, a maximum of 5% of all significant results is a false-positive (that’s what we control with the α rate).
  2. Installing R packages - Part of the reason R has become so popular is the vast array of packages available at the cran and bioconductor repositories. In the last few years, the number of packages has grown exponentially!
  3. Scatterplots (+) - There are many types of scatterplots in R, here are some examples based on the famous Iris data.
  4. In-depth introduction to machine learning in 15 hours of expert videos - In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR). I found it to be an excellent course in statistical learning (also known as "machine learning"), largely due to the high quality of both the textbook and the video lectures. And as an R user, it was extremely helpful that they included R code to demonstrate most of the techniques described in the book. 
  5. Using apply, sapply, lapply in R - This is an introductory post about using apply, sapply and lapply, best suited for people relatively new to R or unfamiliar with these functions. There is a part 2 coming that will look at density plots with ggplot, but first I thought I would go on a tangent to give some examples of the apply family, as they come up a lot working with R.
  6. Basics of Histograms - Histograms are used very often in public health to show the distributions of your independent and dependent variables.  Although the basic command for histograms (hist()) in R is simple, getting your histogram to look exactly like you want takes getting to know a few options of the plot.  Here I present ways to customize your histogram for your needs.
  7. How to Make a Histogram with Basic R - Knowing how to do graphing in R is important. Over the next week we will cover the basics of how to create your own histogram in R. Three options will be explored: “Histograms in R with basic R”, “Histograms in R with ggplot2“, and “Histograms in R with ggvis“. These posts are aimed at beginning and intermediate R users who need an accessible and easy-to-understand resource. 
  8. A Bayesian Model to Calculate Whether My Wife is Pregnant or Not - On the 21st of February, 2015, my wife had not had her period for 33 days, and as we were trying to conceive, this was good news! An average period is around a month, and if you are a couple trying to go triple, then a missing period is a good sign something is going on. But at 33 days, this was not yet a missing period, just a late one, so how good news was it? Pretty good, really good, or just meh?
  9. Adding a legend to a plot 

DSC Resources

Additional Reading

Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge

Views: 2860


You need to be a member of Data Science Central to add comments!

Join Data Science Central

© 2021   TechTarget, Inc.   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service