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Overview

Professional certificates designed for professionals such as analysts, engineers, scientists, managers and anyone else who has an interest in statistics are offered in the following options:

  • Industrial Statistics
  • Biostatistics
  • Data Mining/Data Analytics

The certificate in Industrial Statistics is designed for professionals working with data from areas such as manufacturing, R&D, government, and finance and who are interested in process development and improvement.

The certificate in Biostatistics is designed for professionals who are interested in the techniques needed to analyze data and draw conclusions in health-rated fields such as clinical trials, health informatics, and epidemiology.

The certificate in Data Mining/Data Analytics is designed to enhance knowledge on how to analyze large data sets coming from fields such as healthcare, banking, retail, government and manufacturing.

Individuals may customize a certificate by working with an advisor to develop a plan that meets their needs.

Each certificate requires completion of four classes, as noted in the following table.

BiostatisticsIndustrial StatisticsData Mining/ Data Analytics
  • Categorical Data Analysis
  • Modeling with Discrete Data
  • Nonparametric Statistics
  • Clinical Trials
  • Regression
  • Analysis of Variance
  • Statistical Process Control
  • Industrial Design of Experiments
  • Data Mining/Data Analytics I
  • Data Mining/Data Analytics II
  • Multivariate Statistics
  • Forecasting

The following additional introductory courses are available and may be necessary for individuals with limited background (course descriptions and topics can be viewed below):

  • Basic Statistics
  • Introduction to R
  • Introduction to SAS

Each course is fifteen hours including online lectures, discussion boards and/or chat sessions taken over a five-week period. Each course may be taken individually and qualify for CEUs.

Cost: $750.00 a course/no charge for fourth course. Total for certificate, $2,250.00

Contact:

       Gregory Evershed

 Director Bus. Dev.
 gmecqa@rit.edu
 585-475-5442
 HLC/2526

 

Basic Statistics

Brief Description: In today’s quality-conscious world, statistical knowledge is essential for planning, decision-making, and process improvement. Many managers, engineers, and even operators are now expected to use statistical methods and/or interpret reports using statistical analyses. What do the results mean? Are they significant? Was the analysis done correctly? In this seminar you will learn the basic skills and knowledge to analyze data and apply statistical methods using Minitab statistical software.

Topics

  • Statistical thinking
  • Sampling methods and data collection
  • Introduction to Minitab
  • Measures of dispersion and central tendency
  • Histograms, box plots, and other statistical plots
  • Hypothesis testing and confidence intervals
  • Inferences about proportions and means

Target participants: Analysts, managers, scientists, engineers, and/or professionals working with data who are interested in learning or reviewing basics of statistics

Prerequisites: No prior experience with statistics or Minitab is required.

The course is recommended for individuals without prior exposure to statistics or for those who need to update their knowledge before taking other courses in our Professional Certificate sequences.

Introduction to R

Brief Description: If you search “R language” on Google, you will get roughly 3.2 billion entries, which is by far the largest number of entries for any mathematical or statistical language. This huge interest in R is due in large part to the fact that R is free and offers great modelling power, but crucially to the fact that R has a huge worldwide community around it that provides state-of=the-art packages for a wide variety of applications. Upon completing this course, you will have a practical working knowledge of the R statistical environment.

Topics:

  • Basic introduction to the R software environment (Basic operations, most basic packages and installation of other packages)
  • Elements of Data Types in R
  • Data Manipulation (Open, Transform and Save)
  • Introduction to functions in R
  • Writing scripts in R
  • Vectorization to speed up
  • Basic Statistics with R
  • High quality graphics with R

Target participants: Analysts, managers, scientists, engineers and/or anyone else interested in gaining deeper insights into R

Prerequisites: No prerequisite.

Introduction to SAS

Brief Description: One of the well-known statistical software packages out there is SAS. SAS that can be used to not only manipulate and analyze data in many ways, but also as a querying language. These are just of the many uses for the SAS computing package. It has been adopted as the package of choice for statistical analysis in disciplines such as medical sciences, biological sciences, and social sciences, just to name a few. This course will give you an introduction into manipulating and analyzing data using the SAS system. This includes reading in data files, manipulating data and creation variables, simple data analysis and generating graphs and reports.

Topics:

  • Reading in raw data using PROC IMPORT
  • Creating data sets with the DATA step
  • Viewing the data set  with PROC PRINT
  • Formatting the data with PROC FORMAT
  • Sorting data with PROC SORT
  • Modifying and combining  data sets using a SET statement
  • Summarizing  continuous data using PROC MEANS
  • Summarizing discrete  data using PROC FREQ
  • Producing tabular reports with PROC TABULATE
  • Producing summary reports with PRC REPORT
  • Generating plots based with PROC GPLOT, GBARLINE, GCHART, etc.

Target participants: Analysts, managers, scientists, engineers and/or anyone else interested in learning more about the proper way to use SAS to build models in situations where the response variable is discrete.

Prerequisites: Participants should have a basic understanding of using a personal computer

This course can be used for the Professional Certificate in Biostatistics or a customized certificate.

 

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