PASS

Programs in Analytics and Statistical Studies

Master the software and practical skills
you need to get ahead.

Using R (legacy)

This program is not longer being offered. Those originally in this program may continue with it or choose to transfer to the Analytics for Data Science or Programming for Data Science program.

The Institute offers 100+ courses in statistics and analytics; this particular certificate program focuses on those courses relevant to learning how to program in R and use it for statistical analysis.  Most courses are 4 weeks long, do not require you to be online at specific times during the week, and offer continuing education credits.  The workload for the entire program is the equivalent of 21 credits in the U.S. academic system.

The courses are taught by recognized authorities with whom you share a private discussion forum for the entire course period.

Most PASS candidates choose to take one course at a time.  With courses starting every week of the year, there is considerable scheduling flexibility.  Admission applications are accepted on a rolling basis throughout the year.

 

Using R (legacy)

Program Content

The program consists of courses offered completely online at Statistics.com. There is a small group of required topics, plus a number of electives. Different concentration strands within the program are available, corresponding to different sets of suggested electives. These strands are optional; if you successfully complete the courses in the strand this will be reflected on your PASS transcript. In addition to the concentration electives, students select several additional electives from among the general Program electives.

R Programming:  We suggest R Programming Intermediate, R Programming Advanced, and Wrangling and Munging Data with SQL and R.  If you are experienced with programming languages or statistical computation environments, you can skip over R Programming - Introduction.  If you are new to programming altogether, this strand will not be useful to you unless you build in a couple of years of on-the-job programming experience between the initial courses and R Programming Intermediate.

R for Statistical Analysis:  We suggest Logistic Regression, Introduction to Smoothing and P-spline Techniques Using R, and Wrangling and Munging Data with SQL and R.


Course ListExplore elective options, including suggested concentration strands

Thanks


Required Courses (6)

  • Graphics in R The aim of this course is to teach you how to produce statistical plots of data using the R language and environment for statistical computing and graphics. The creation of standard plots such as scatterplots, bar charts, histograms, and boxplots will be covered and time will be spent on the underlying model used to produce plots in R so that you can extensively customize these plots. Tuition: $469 (5.0 CEUs) New available dates:
    October 10, 2014 to November 07, 2014May 01, 2015 to May 29, 2015October 09, 2015 to November 06, 2015April 29, 2016 to May 27, 2016October 07, 2016 to November 04, 2016May 05, 2017 to June 02, 2017October 06, 2017 to November 03, 2017May 04, 2018 to June 01, 2018October 05, 2018 to November 02, 2018
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  • Modeling in R This course will show you how to use R to create statistical models and use them to analyze data. Tuition: $549 (5.0 CEUs) New available dates:
    February 06, 2015 to March 06, 2015August 21, 2015 to September 18, 2015
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  • R for Statistical Analysis This course covers how to use R for basic statistical procedures. Tuition: $469 (5.0 CEUs) New available dates:
    October 03, 2014 to October 31, 2014January 02, 2015 to January 30, 2015April 03, 2015 to May 01, 2015July 24, 2015 to August 21, 2015October 02, 2015 to October 30, 2015January 01, 2016 to January 29, 2016April 01, 2016 to April 29, 2016July 22, 2016 to August 19, 2016October 07, 2016 to November 04, 2016January 06, 2017 to February 03, 2017March 31, 2017 to April 28, 2017July 21, 2017 to August 18, 2017October 06, 2017 to November 03, 2017
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  • R Programming - Introduction 1

    This course will provide an easy introduction to programming in R.

    Tuition: $469 (5.0 CEUs) New available dates:
    November 07, 2014 to December 05, 2014March 06, 2015 to April 03, 2015May 08, 2015 to June 05, 2015August 07, 2015 to September 04, 2015November 06, 2015 to December 04, 2015March 04, 2016 to April 01, 2016May 06, 2016 to June 03, 2016July 29, 2016 to August 26, 2016November 04, 2016 to December 02, 2016March 03, 2017 to March 31, 2017May 05, 2017 to June 02, 2017August 04, 2017 to September 01, 2017November 03, 2017 to December 01, 2017March 02, 2018 to March 30, 2018May 04, 2018 to June 01, 2018August 03, 2018 to August 31, 2018November 02, 2018 to November 30, 2018
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  • R Programming - Introduction 2 This course continues the introduction to R programming. Tuition: $469 (5.0 CEUs) New available dates:
    September 05, 2014 to October 03, 2014January 30, 2015 to February 27, 2015April 10, 2015 to May 08, 2015June 12, 2015 to July 10, 2015September 11, 2015 to October 09, 2015January 29, 2016 to February 26, 2016April 08, 2016 to May 06, 2016June 10, 2016 to July 08, 2016September 09, 2016 to October 07, 2016January 27, 2017 to February 24, 2017April 07, 2017 to May 05, 2017June 09, 2017 to July 07, 2017September 08, 2017 to October 06, 2017January 26, 2018 to February 23, 2018April 06, 2018 to May 04, 2018June 08, 2018 to July 06, 2018September 07, 2018 to October 05, 2018
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  • Visualization in R with ggplot2

    ggplot, created by Hadley Wickham, is an implementation of the grammar of graphics in R.  It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, while maintaining the ability to build up a plot step by step from multiple data sources. It also implements a more sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes.

    ggplot won the 2006 John Chambers Award for Statistical Computing.

    Tuition: $469 (5.0 CEUs) New available dates:
    January 16, 2015 to February 13, 2015July 24, 2015 to August 21, 2015July 22, 2016 to August 19, 2016January 13, 2017 to February 10, 2017January 12, 2018 to February 09, 2018July 20, 2018 to August 17, 2018
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Elective Courses (8 required)

  • Bayesian Statistics in R Using R and the associated R package JAGS, you will learn how to specify and run Bayesian modeling procedures using regression models for continuous, count and categorical data. Tuition: $549 (5.0 CEUs) New available dates:
    September 26, 2014 to October 24, 2014March 27, 2015 to April 24, 2015September 25, 2015 to October 23, 2015March 25, 2016 to April 22, 2016September 23, 2016 to October 21, 2016March 24, 2017 to April 21, 2017September 22, 2017 to October 20, 2017March 23, 2018 to April 20, 2018September 21, 2018 to October 19, 2018
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  • Biostatistics in R: Clinical Trial Applications This course covers the implementation in R of statistical procedures important for the clinical trial statistician. Tuition: $549 (5.0 CEUs) New available dates:
    May 22, 2015 to June 19, 2015
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  • Bootstrap Methods This course covers the basic theory and application of the bootstrap family of procedures, with the emphasis on applications. Tuition: $549 (5.0 CEUs) New available dates:
    September 19, 2014 to October 17, 2014February 20, 2015 to March 20, 2015
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  • Data Mining - R The main goal of this course is to teach users how to perform data mining tasks using R. Tuition: $469 (5.0 CEUs) New available dates:
    February 06, 2015 to March 06, 2015June 26, 2015 to July 24, 2015October 09, 2015 to November 06, 2015February 03, 2016 to March 02, 2016June 23, 2016 to July 21, 2016October 13, 2016 to November 10, 2016January 06, 2017 to February 03, 2017June 23, 2017 to July 21, 2017October 13, 2017 to November 10, 2017January 05, 2018 to February 02, 2018June 22, 2018 to July 20, 2018October 12, 2018 to November 09, 2018
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  • Introduction to Smoothing and P-spline Techniques using R Splines are combinations of different functions that are used to describe and model data differentially in a smooth fashion over different ranges.  In this course, you will learn how to use R software to develop splines for data smoothing. Tuition: $549 (5.0 CEUs) New available dates:
    June 19, 2015 to July 17, 2015
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  • Logistic Regression Logistic regression extends ordinary least squares (OLS) methods to model data with binary (yes/no, success/failure) outcomes. Rather than directly estimating the value of the outcome, logistic regression allows you to estimate the probability of a success or failure. Tuition: $549 (5.0 CEUs) New available dates:
    September 05, 2014 to October 03, 2014March 13, 2015 to April 10, 2015September 04, 2015 to October 02, 2015March 11, 2016 to April 08, 2016September 02, 2016 to September 30, 2016
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  • R Programming - Advanced

    This course covers key concepts for writing advanced R code, emphasizing the design of functional and efficient code.  It will set students down the road to mastering the intricacies of R.  After completing the course, students should be able to read, understand, modify, and create complex functions to perform a variety of tasks.

    Tuition: $489 (5.0 CEUs) New available dates:
    January 09, 2015 to February 06, 2015May 22, 2015 to June 19, 2015January 08, 2016 to February 05, 2016May 20, 2016 to June 17, 2016January 06, 2017 to February 03, 2017May 19, 2017 to June 16, 2017January 05, 2018 to February 02, 2018May 18, 2018 to June 15, 2018
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  • R Programming - Intermediate

    This course is intended for experienced data analysts looking to unlock the power of R.  It provides a systematic overview of R as a programming language, emphasizing good programming practices and the development of clear, concise code.  After completing the course, students should be able to manipulate data programmatically using R functions of their own design.

    Tuition: $489 (5.0 CEUs) New available dates:
    September 26, 2014 to October 24, 2014April 03, 2015 to May 01, 2015September 25, 2015 to October 23, 2015April 01, 2016 to April 29, 2016September 23, 2016 to October 21, 2016March 31, 2017 to April 28, 2017September 22, 2017 to October 20, 2017March 30, 2018 to April 27, 2018September 21, 2018 to October 19, 2018
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  • Spatial Analysis Techniques in R This course will teach users how to implement spatial statistical analysis procedures using R software. Tuition: $549 (5.0 CEUs) New available dates:
    December 12, 2014 to January 09, 2015December 11, 2015 to January 08, 2016December 09, 2016 to January 06, 2017December 08, 2017 to January 05, 2018December 07, 2018 to January 04, 2019
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  • SQL and R - Introduction to Database Queries The purpose of this course is to teach you how to extract data from a relational database using SQL, and merge it into a single file in R, so that you can perform statistical operations. Tuition: $469 (5.0 CEUs) New available dates:
    March 20, 2015 to April 17, 2015August 07, 2015 to September 04, 2015November 13, 2015 to December 11, 2015March 18, 2016 to April 15, 2016August 05, 2016 to September 02, 2016November 11, 2016 to December 09, 2016March 17, 2017 to April 14, 2017August 04, 2017 to September 01, 2017November 10, 2017 to December 08, 2017March 16, 2018 to April 13, 2018August 03, 2018 to August 31, 2018November 09, 2018 to December 07, 2018
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  • Statistical Analysis of Microarray Data with R

    This course will acquaint you with the process of analysis of microarray data. You will learn how to preprocess the data, short list the differentially expressed genes, carryout principal component analysis to reduce the dimensionality and to detect interesting gene expression patterns, and clustering of genes and samples. Illustrations of the statistical issues involved at the various stages of the analysis will use real data sets from DNA microarray experiments; background will be provided on the use of Bioconductor.

    Tuition: $549 (5.0 CEUs) New available dates:
    April 17, 2015 to May 15, 2015April 15, 2016 to May 13, 2016
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  • Survey Analysis in R The purpose of this course is to teach survey researchers who are familiar with R how to use it in survey research. Tuition: $499 (5.0 CEUs) New available dates:
    To be scheduled.
    show more dates >> more >>

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From a Student Profile:

I hear IT people commenting that they’re always needing to learn new technology because things in their field evolve and change quickly. The same thing is true in analytics. New techniques are developing rapidly.

Robert Wood
Director, Advanced Analytics Group, Merkle

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