Statistics With R
A 2-Day Seminar Taught by James Curley, Ph.D.
R is one of the fastest growing programming languages and has quickly become the lingua franca of data science. It is the major statistical software used for the organization, visualization and analysis of data throughout academia in fields such as psychology, economics, statistics, biostatistics, sociology, and education, as well as in the business and technology sectors.
R is a highly flexible and extensible language. It is supported by an enormous and ever-expanding suite of libraries and packages that provide state-of-the-art statistical techniques. R’s graphics and visualization tools are unmatched. The possibilities for data visualization are limited only by one’s imagination.
R is also a fantastic language for generating reproducible research. Users can perform statistical analyses and write reports or journal articles directly in R that can be reproduced by any other researcher. Undeniably, learning R is the most useful skill any researcher can add to their data science toolbox.
This two-day seminar will provide a comprehensive introduction to R. Course participants will learn R from the beginning–no previous experience is necessary. The course will be practical and hands-on consisting of working with real datasets and solving common problems that arise in research analysis.
Throughout, the focus will be on learning tools in R and RStudio that facilitate the management, analysis, and visualization of data as a continuous and reproducible workflow. The course will demonstrate how to import and export data files, how to clean up and work with data, how to make exploratory and publication quality visualizations, and how to do standard parametric and non-parametric statistical analysis.
To participate in the hands-on exercises, you are strongly encouraged to bring a laptop computer with the most recent version of R installed. Participants are also encouraged to download and install RStudio, a front-end for R that makes it easier to work with. This software is free and available for Windows, Mac, and Linux platforms.
Who should attend?
The seminar will appeal to academic and business researchers who seek an accelerated and in-depth introduction to a powerful, widely popular, and flexible statistical software package. The course will focus on developing mastery of R through practical problem solving. Thus, the focus will be on practice rather than underlying statistical theory. While basic familiarity with material covered in a first-year undergraduate statistics course will be assumed–such as common probability distributions, hypothesis testing, t-tests, ANOVA, and regression–this will all be re-examined in the context of R.
Some sample problems will extend beyond the basic level to demonstrate the power of R’s framework in answering seemingly simple yet surprisingly complex questions. While helpful, no prior experience with statistical software will be assumed. The course will be especially useful for individuals who wish to transition to R from using other statistical softwares (e.g., Matlab, SAS, Stata, and SPSS) but have little or experience using R.
LOCAtions, Format, And Materials
The class will meet from 9 am to 5 pm each day with a 1-hour lunch break at Temple University Center City, 1515 Market Street, Philadelphia, PA 19103.
Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking.
Registration and lodging
The fee of $995.00 includes all seminar materials. The early registration fee of $895 is available until May 7.
If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).
Lodging Reservation Instructions
A block of guest rooms has been reserved at the Club Quarters Hotel, 1628 Chestnut Street, Philadelphia, PA at a special rate of $159 per night. This location is about a 5 minute walk to the seminar location. In order to make reservations, call 203-905-2100 during business hours and identify yourself by using group code SH0606 or click here. For guaranteed rate and availability, you must reserve your room no later than Monday, May 7, 2018.
If you make reservations after the cut-off date, ask for the Statistical Horizons room rate (do not use the code) and they will try to accommodate your request.
1. Introduction to R and RStudio
a. Importing and exporting data
b. Working with data in RStudio
c. Data management and cleaning
2. Data Visualization and Descriptive Statistics
a. Introduction to ggplot2 – how to plot distributions, raw and summary data
b. Generating and plotting summary and descriptive statistics
3. Parametric Statistics
a. Testing normality and variances of distributions
b. Paired and unpaired T-tests
c. One-way Analysis of Variance
d. Two-way Analysis of Variance
4. Correlation and Regression
a. Pearson and Spearman Correlations
b. Linear Regression
c. Logistic Regression
5. Generalized Linear Models
a. Poisson Regression
b. Binomial Regression