PASS

Programs in Analytics and Statistical Studies

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Data Analytics (legacy)

This program is not longer being offered.  Please see Analytics for Data Science or Programming for Data Science.

The Institute offers 100+ courses in statistics and analytics; this particular certificate program focuses on those courses relevant for the study of topics in data analytics (data mining, predictive modeling, forecasting and more).  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.

 

Data Analytics (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. Students may select a concentration strand (see below) to guide their choice of electives.  This PASS is no longer being offered, although 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.

Concentration Strands (optional) and Electives

The program offers a set of core courses that are required, as well as a set of electives from which you can choose those of interest. 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.

  • Predictive Analytics and Data Mining: We suggest Data Mining - Unsupervised Learning, then choosing among Decision Trees, Cluster Analysis, Data Mining in R, or SQL and R - Introduction to Database Queries.
  • Risk Assessment and Forecasting: We suggest Financial Risk Modeling and Introduction to Quantitative Risk Management or Risk Simulation and Queuing.
  • Market Research and Consumer Behavior: We suggest Survey Design, Survey Analysis, Multivariate Statistics, Cluster Analysis, and Discrete Choice Modeling and Conjoint Analysis
  • Reliability Statistics: We suggest Design of Experiments, Engineering Statistics, Statistical Process Control, Probability Distributions
  • Optimization: We suggest Optimization (Advanced), Risk Simulation and Queuing*
  • Text Analytics: We suggest Natural Language Processing and Sentiment Analysis

*Risk Simulation and Queuing may be substituted for the required course Quantitative Risk Analysis.

Course ListExplore elective options, including suggested concentration strands

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Required Courses (6)

  • Forecasting Analytics This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting. Tuition: $499 (5.0 CEUs) New available dates:
    March 27, 2015 to April 24, 2015July 31, 2015 to August 28, 2015November 27, 2015 to December 25, 2015March 25, 2016 to April 22, 2016July 29, 2016 to August 26, 2016November 25, 2016 to December 23, 2016March 24, 2017 to April 21, 2017July 28, 2017 to August 25, 2017November 24, 2017 to December 22, 2017March 23, 2018 to April 20, 2018July 27, 2018 to August 24, 2018November 23, 2018 to December 21, 2018
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  • Interactive Data Visualization This course covers the principles of the visual display of data, both for presentation and analysis. Tuition: $499 (5.0 CEUs) New available dates:
    February 13, 2015 to March 13, 2015June 12, 2015 to July 10, 2015October 30, 2015 to November 27, 2015February 12, 2016 to March 11, 2016June 10, 2016 to July 08, 2016October 28, 2016 to November 25, 2016February 10, 2017 to March 10, 2017June 09, 2017 to July 07, 2017October 27, 2017 to November 24, 2017February 09, 2018 to March 09, 2018June 08, 2018 to July 06, 2018October 26, 2018 to November 30, 2018
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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:
    March 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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  • Predictive Analytics 1 - Machine Learning Tools This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Tuition: $469 (5.0 CEUs) New available dates:
    January 23, 2015 to February 20, 2015May 29, 2015 to June 26, 2015September 25, 2015 to October 23, 2015January 22, 2016 to February 19, 2016May 27, 2016 to June 24, 2016September 23, 2016 to October 21, 2016January 20, 2017 to February 17, 2017May 26, 2017 to June 23, 2017September 29, 2017 to October 27, 2017January 19, 2018 to February 16, 2018May 25, 2018 to June 22, 2018September 28, 2018 to October 26, 2018
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  • Predictive Analytics 2 - Neural Nets and Regression This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel. Tuition: $469 (5.0 CEUs) New available dates:
    February 27, 2015 to March 27, 2015July 03, 2015 to July 31, 2015October 30, 2015 to November 27, 2015February 26, 2016 to March 25, 2016July 01, 2016 to July 29, 2016October 28, 2016 to November 25, 2016February 24, 2017 to March 24, 2017June 30, 2017 to July 28, 2017October 27, 2017 to November 24, 2017February 23, 2018 to March 23, 2018June 29, 2018 to July 27, 2018October 26, 2018 to November 23, 2018
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  • Regression Analysis In this course you will learn how multiple linear regression models are derived, use software to implement them, learn what assumptions underlie the models, learn how to test whether your data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models. Tuition: $499 (5.0 CEUs) New available dates:
    January 23, 2015 to February 20, 2015May 15, 2015 to June 12, 2015October 02, 2015 to October 30, 2015January 22, 2016 to February 19, 2016May 13, 2016 to June 10, 2016September 30, 2016 to October 28, 2016January 20, 2017 to February 17, 2017May 12, 2017 to June 09, 2017September 29, 2017 to October 27, 2017January 19, 2018 to February 16, 2018May 11, 2018 to June 08, 2018October 05, 2018 to November 02, 2018
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Elective Courses (8 required)

  • Advanced Optimization This course covers a number of advanced topics in optimization.  You will learn: 1) how to formulate and solve network flow problems, 2) how to model and solve optimization problems where some or all of the decision variables must be integers, 3) how to deal with multiple objectives in optimization problems, and 4) techniques for handling optimization problems where the objective function or constraints are not linear functions of the decision variables. Tuition: $549 (5.0 CEUs) New available dates:
    September 25, 2015 to October 23, 2015September 23, 2016 to October 21, 2016September 22, 2017 to October 20, 2017September 21, 2018 to October 19, 2018
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  • Analysis of Survey Data from Complex Sample Designs This course teaches you how to estimate variances for complex surveys, and also how to model the results using linear and logistic regression, and other generalized linear models. Tuition: $549 (5.0 CEUs) New available dates:
    October 16, 2015 to November 13, 2015October 14, 2016 to November 11, 2016
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  • Bayesian Regression Modeling via MCMC Techniques This course covers the application of Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software. Tuition: $549 (5.0 CEUs) New available dates:
    April 24, 2015 to May 22, 2015October 23, 2015 to November 20, 2015
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  • 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:
    March 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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  • Cluster Analysis In this online course, “Cluster Analysis,” you will learn how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables. Tuition: $549 (5.0 CEUs) New available dates:
    June 05, 2015 to July 03, 2015June 03, 2016 to July 01, 2016June 02, 2017 to June 30, 2017June 01, 2018 to June 29, 2018
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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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  • Decision Trees and Rule-Based Segmentation Rule induction is an important component of data mining, and this course covers two main styles of generating rules. Tuition: $549 (5.0 CEUs) New available dates:
    January 16, 2015 to February 13, 2015January 15, 2016 to February 12, 2016January 13, 2017 to February 10, 2017January 12, 2018 to February 09, 2018
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  • Discrete Choice Modeling and Conjoint Analysis After taking this course, participants will be able to design appropriate conjoint and choice studies, using surveys, panels, and designed experiments. They will also be able to analyze and interpret the resulting data. Tuition: $549 (5.0 CEUs) New available dates:
    April 10, 2015 to May 08, 2015April 08, 2016 to May 06, 2016April 07, 2017 to May 05, 2017April 06, 2018 to May 04, 2018
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  • Financial Risk Modeling This course teaches participants how to model financial events that have uncertainties associated with them. Tuition: $549 (5.0 CEUs) New available dates:
    May 15, 2015 to June 12, 2015May 13, 2016 to June 10, 2016
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  • Introduction to Bayesian Computing and Techniques Participants in this course will learn why Bayesian computing has gained wide popularity, and how to apply Markov Chain Monte Carlo techniques (MCMC) to Bayesian statistical modeling using WinBUGS software. Tuition: $549 (5.0 CEUs) New available dates:
    February 27, 2015 to March 27, 2015August 28, 2015 to September 25, 2015
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  • Introduction to Bayesian Hierarchical and Multi-level Models This course extends the Bayesian modeling framework to cover hierarchical models, and to add flexibility to standard Bayesian modeling problems. Tuition: $549 (5.0 CEUs) New available dates:
    May 22, 2015 to June 19, 2015
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  • Introduction to Bayesian Statistics This course will introduce you to the basic ideas of Bayesian Statistics. You will learn how to perform Bayesian analysis for a binomial proportion, a normal mean, the difference between normal means, the difference between proportions, and for a simple linear regression model. Tuition: $549 (5.0 CEUs) New available dates:
    January 16, 2015 to February 13, 2015July 03, 2015 to July 31, 2015January 15, 2016 to February 12, 2016July 01, 2016 to July 29, 2016January 13, 2017 to February 10, 2017
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  • Introduction to Design of Experiments This course will stress the application of DOE rather than statistical theory. With a 12-step checklist, it covers full and fractional factorial designs, Plackett-Burman, Box-Behnken, Box-Wilson and Taguchi designs. Tuition: $549 (5.0 CEUs) New available dates:
    February 13, 2015 to March 13, 2015February 12, 2016 to March 11, 2016
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  • Introduction to Optimization The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems. Tuition: $549 (5.0 CEUs) New available dates:
    January 09, 2015 to February 06, 2015August 21, 2015 to September 18, 2015January 08, 2016 to February 05, 2016August 19, 2016 to September 16, 2016January 06, 2017 to February 03, 2017August 18, 2017 to September 15, 2017January 05, 2018 to February 02, 2018August 17, 2018 to September 14, 2018
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  • Introduction to Social Network Analysis (SNA) This course will teach a mix of quantitative and qualitative methods for describing, measuring and analyzing social networks. Tuition: $469 (5.0 CEUs) New available dates:
    February 27, 2015 to March 27, 2015August 14, 2015 to September 11, 2015February 26, 2016 to March 25, 2016August 12, 2016 to September 09, 2016February 24, 2017 to March 24, 2017August 11, 2017 to September 08, 2017February 23, 2018 to March 23, 2018August 10, 2018 to September 07, 2018
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  • Introduction to Statistical Modeling This course provides a solid introduction to the ideas and techniques of statistical modeling. Tuition: $469 (5.0 CEUs) New available dates:
    January 02, 2015 to January 30, 2015June 12, 2015 to July 10, 2015January 01, 2016 to January 29, 2016June 10, 2016 to July 08, 2016January 06, 2017 to February 03, 2017June 09, 2017 to July 07, 2017January 05, 2018 to February 02, 2018June 08, 2018 to June 08, 2018
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  • Matrix Algebra Review This course will provide the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors. After successfully completing this course, you will be able to use and understand vector and matrix operations and equations, find and use a matrix inverse, and use and understand the eigenset of a symmetric matrix. Tuition: $469 (5.0 CEUs) New available dates:
    March 20, 2015 to April 17, 2015June 26, 2015 to July 24, 2015November 13, 2015 to December 11, 2015March 18, 2016 to April 15, 2016June 24, 2016 to July 22, 2016November 11, 2016 to December 09, 2016
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  • Natural Language Processing This course is designed to give you an introduction to the algorithms, techniques and software used in natural language processing (NLP). Tuition: $469 (5.0 CEUs) New available dates:
    March 06, 2015 to April 03, 2015July 17, 2015 to August 14, 2015March 04, 2016 to April 01, 2016July 15, 2016 to August 12, 2016March 03, 2017 to March 31, 2017July 14, 2017 to August 11, 2017March 02, 2018 to March 30, 2018July 13, 2018 to August 10, 2018
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  • Prediction & Tolerance Intervals; Measurement and Reliability The topics covered in this course include prediction intervals, tolerance intervals, calibration intervals, measurement error, accelerated life testing, measurement system appraisal, reliability and lifetime testing. Tuition: $549 (5.0 CEUs) New available dates:
    May 29, 2015 to June 26, 2015
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  • Predictive Analytics 3: Dimension Reduction, Clustering and Association Rules This course covers key unsupervised learning techniques - association rules, principal components analysis, and clustering. The course will include an integration of supervised and unsupervised learning techniques. Tuition: $499 (5.0 CEUs) New available dates:
    January 02, 2015 to January 30, 2015April 17, 2015 to May 15, 2015August 07, 2015 to September 04, 2015January 01, 2016 to January 29, 2016April 15, 2016 to May 13, 2016August 05, 2016 to September 02, 2016January 06, 2017 to February 03, 2017April 14, 2017 to May 12, 2017August 04, 2017 to September 01, 2017January 05, 2018 to February 02, 2018April 13, 2018 to May 11, 2018August 03, 2018 to August 31, 2018
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  • Probability Distributions This course cover statistical probability distributions. Participants will learn how to identify which distribution(s) reasonably fit given data, and to evaluate the fit. Tuition: $549 (5.0 CEUs) New available dates:
    January 23, 2015 to February 20, 2015June 19, 2015 to July 17, 2015
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  • Risk Simulation and Queuing This course covers modeling technique making decisions in the presence of risk or uncertainty.  Specific topics include risk analysis using Monte Carlo simulation for risk simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.
     
    Tuition: $549 (5.0 CEUs) New available dates:
    May 01, 2015 to May 29, 2015November 20, 2015 to December 18, 2015May 06, 2016 to June 03, 2016November 18, 2016 to December 16, 2016May 05, 2017 to June 02, 2017November 17, 2017 to December 15, 2017May 04, 2018 to June 01, 2018November 16, 2018 to December 14, 2018
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  • Sentiment Analysis Sentiment Analysis refers to the process of identifying, extracting and classifying opinions in text segments. With the rise of social media and the ability of end-users to express and share their personal views easily, the need to automatically gauge user-sentiment has become increasingly important for CRM, online advertising and brand analysis. Tuition: $389 (3.75 CEUs) New available dates:
    May 08, 2015 to May 29, 2015August 21, 2015 to September 11, 2015May 06, 2016 to May 27, 2016August 19, 2016 to September 09, 2016May 05, 2017 to May 26, 2017August 18, 2017 to September 08, 2017May 04, 2018 to May 25, 2018August 17, 2018 to September 07, 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 11, 2015 to January 15, 2016December 09, 2016 to January 13, 2017December 08, 2017 to January 12, 2018December 07, 2018 to January 11, 2019
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  • Spatial Statistics with Geographic Information Systems Spatial statistical analysis uses methods adapted from conventional statistics to address problems in which spatial location is the most important explanatory variable. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo. Tuition: $549 (5.0 CEUs) New available dates:
    May 08, 2015 to June 05, 2015October 30, 2015 to November 27, 2015April 08, 2016 to May 06, 2016October 28, 2016 to November 25, 2016April 07, 2017 to May 05, 2017October 27, 2017 to November 24, 2017April 06, 2018 to May 04, 2018November 02, 2018 to November 30, 2018
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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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  • Statistical Process Control This course will will go beyond the basics of SPC and present some improved control chart methods, with better ways of determining control limits. Tuition: $469 (5.0 CEUs) New available dates:
    March 13, 2015 to April 10, 2015
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  • Survey Analysis This course covers the analysis of data gathered in surveys. Tuition: $549 (5.0 CEUs) New available dates:
    September 11, 2015 to October 09, 2015September 09, 2016 to October 07, 2016September 08, 2017 to October 06, 2017
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  • Survey Design and Sampling Procedures This course covers the crafting of survey questions, the design of surveys, and different sampling procedures that are used in practice. Longstanding basic principles of survey design are covered, and the impact of the trend toward increased respondent resistance is discussed. Tuition: $469 (5.0 CEUs) New available dates:
    March 20, 2015 to April 17, 2015August 07, 2015 to September 04, 2015March 18, 2016 to April 15, 2016August 05, 2016 to September 02, 2016March 17, 2017 to April 14, 2017August 04, 2017 to September 01, 2017March 16, 2018 to April 13, 2018August 03, 2018 to August 31, 2018
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  • Survival Analysis The course describes the various methods used for modeling and evaluating survival data, or time-to event data. Tuition: $549 (5.0 CEUs) New available dates:
    March 13, 2015 to April 10, 2015September 18, 2015 to October 16, 2015March 11, 2016 to April 08, 2016September 16, 2016 to October 14, 2016March 10, 2017 to April 07, 2017September 15, 2017 to October 13, 2017March 09, 2018 to April 06, 2018September 14, 2018 to October 12, 2018
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  • Text Mining This course will introduce the essential techniques of text mining, understood here as the extension of data mining's standard predictive methods to unstructured text. Tuition: $469 (5.0 CEUs) New available dates:
    February 06, 2015 to March 06, 2015June 05, 2015 to July 03, 2015February 05, 2016 to March 04, 2016June 10, 2016 to July 08, 2016February 03, 2017 to March 03, 2017June 09, 2017 to July 07, 2017February 02, 2018 to March 02, 2018June 08, 2018 to July 06, 2018
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From a Student Profile:

We’re trying to make it easier for patients to get their prosthetic arms to do exactly what they want them to do. I’ve applied what I’ve learned through my statistics.com courses, such as Baysian statistics, computing techniques, biostatistics, clinical trials, analysis and sensitivity software, bioavailability, probability distributions, data mining, and designing experiments to map brain impulses to muscle movement, which ultimately will help make prosthetics work on thought impulses.

Dr. Patricia A. Shewokis
Drexel University

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