library(swirl)
swirl()
Showing posts with label data scientist. Show all posts
Showing posts with label data scientist. Show all posts
Monday, August 6, 2018
I'm learning R, in R
I've recently discovered an amazing package for R called Swirl. I realize it's been around for some time now, but it's new to me, and I love it. Swirl() is a straight-forward, user-friendly approach to diving right into R. Each lesson is delivered interactively and in short bursts. The lessons are succinct and detailed, and leave the user feeling informed. For anyone looking to get started with R, I strong recommend Swirl().
library(swirl)
swirl()
library(swirl)
swirl()
Wednesday, July 4, 2018
At a minimum, a data scientist should...
I wish I could remember where I copied and pasted this from, but alas, I cannot. Just the same, here's a great overview of what a data scientist would benefit from understanding.
At a minimum, a data scientist needs to be proficient with concepts such as probability, correlation, variables, distributions, regression, null hypothesis significance tests, confidence intervals, t-test, ANOVA, and chi-square. At an advanced stage, data scientists need concepts and algorithms such as logistic regression, support vector machines (SVMs) and Bayesian methods. Common statistical analysis tools such as Excel, R and SAS are very famous among data scientists.
At a minimum, a data scientist needs to be proficient with concepts such as probability, correlation, variables, distributions, regression, null hypothesis significance tests, confidence intervals, t-test, ANOVA, and chi-square. At an advanced stage, data scientists need concepts and algorithms such as logistic regression, support vector machines (SVMs) and Bayesian methods. Common statistical analysis tools such as Excel, R and SAS are very famous among data scientists.
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