In today's data-driven world, statistical analysis plays a critical role in uncovering insights, validating hypotheses, and driving decision-making across industries. R, a powerful programming ...

The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

R is hot. Whether measured by more than 10,000 add-on packages, the 95,000+ members of LinkedIn’s R group or the more than 400 R Meetup groups currently in existence, there can be little doubt that ...

Predictive analysis refers to the use of historical data and analyzing it using statistics to predict future events. It takes place in seven steps, and these are: defining the project, data collection ...

Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

This workshop is hands-on and intended for beginners; no previous knowledge of data analysis and/or R is required. This session will cover the following topics for R: data preparation, descriptive ...

The RNA-seq platform 1,2 addresses a multitude of applications, including relative expression analyses, alternative splicing, discovery of novel transcripts and isoforms, RNA editing, allele-specific ...

Equal Opportunity and Non-discrimination at Princeton University: Princeton University believes that commitment to equal opportunity for all is favorable to the free and open exchange of ideas, and ...