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Social Science Certificate Program

Certificate Program Tuition and Fees
As a candidate, you are eligible for academic  tuition - type "PASS" when prompted for your academic affiliation during online registration to receive a reduced tuition per course.  If you register online for three courses, an automatic $200 reduction is applied.  

Please note that payment of the tuition does not include the purchase of any required texts or software. 

The total cost of the program varies depending on the electives chosen. Actual fees may differ from the estimate below. Fees are subject to change without prior notice.

Application Fee: $75
Program Registration Fee:$695
Estimated Required Course Tuition: $3004
Estimated Electives Course Tuition: $3681
Estimated Material Cost: $910
Estimated Total Cost: $8365

Social Science Certificate Program

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.

Planning my Program

Most courses are four weeks long, and are scheduled either once or twice a year. Courses start on specific dates, but do not require you to be online at any particular time of the day. Since various courses are available throughout the year, the Program provides flexibility in scheduling.

Course ListExplore elective options, including suggested concentration strands

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TimelineView a typical sequence of courses


FULL PROGRAM LIST

Required Courses (6)

  • Categorical Data Analysis This course will cover the analysis of contingency table data (tabular data in which the cell entries represent counts of subjects or items falling into certain categories). Topics include tests for independence (comparing proportions as well as chi-square), exact methods, and treatment of ordered data. Both 2-way and 3-way tables are covered. Tuition: $549 (5.0 CEUs) New available dates:
    April 10, 2015 to May 08, 2015October 09, 2015 to November 06, 2015April 08, 2016 to May 06, 2016October 07, 2016 to November 04, 2016April 07, 2017 to May 05, 2017October 06, 2017 to November 03, 2017April 06, 2018 to May 04, 2018October 05, 2018 to November 02, 2018
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  • Designing Valid Statistical Studies This course covers the issues you need to address in designing studies to produce statistically valid conclusions.  Topics covered in the course include: overview of validity and bias, selection bias, information bias, and confounding bias. Tuition: $469 (5.0 CEUs) New available dates:
    February 20, 2015 to March 20, 2015July 10, 2015 to August 07, 2015February 19, 2016 to March 18, 2016July 08, 2016 to August 05, 2016February 17, 2017 to March 17, 2017July 07, 2017 to August 04, 2017February 16, 2018 to March 16, 2018July 06, 2018 to August 03, 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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  • 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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  • Sample Size and Power Determination This course shows you how to make sample size determinations for various statistical tests and for confidence intervals, as needed for experimental studies such as comparison studies, as well as for other types of experiments. Tuition: $549 (5.0 CEUs) New available dates:
    April 17, 2015 to May 15, 2015November 20, 2015 to December 18, 2015April 15, 2016 to May 13, 2016November 18, 2016 to December 16, 2016April 14, 2017 to May 12, 2017November 17, 2017 to December 15, 2017April 13, 2018 to May 11, 2018November 16, 2018 to December 14, 2018
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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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Elective Courses (7 required)

  • Advanced Logistic Regression After taking this course, participants will be able to specify, implement and interpret the output of a variety of advanced logistic regression models not covered in the first course, Logistic Regression. Tuition: $549 (5.0 CEUs) New available dates:
    April 24, 2015 to May 22, 2015April 22, 2016 to May 20, 2016
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  • Advanced Structural Equation Modeling This course covers many popular advanced SEM models with practical exercises. Models covered include Multiple Indicator and Multiple Causes models (MIMIC), Multiple Group models, Multilevel (HLM) models, Mixture models, Structured Means models, Multitrait-Multimethod models, Second Order Factor models, Interaction models, and Dynamic Factor models. Tuition: $549 (5.0 CEUs) New available dates:
    January 09, 2015 to February 06, 2015June 26, 2015 to July 24, 2015
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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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  • 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:
    February 20, 2015 to March 20, 2015
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  • Generalized Linear Models

    This course will explain the theory of generalized linear models (GLM), outline the algorithms used for GLM estimation, and explain how to determine which algorithm to use for a given data analysis. GLM allows the modeling of responses, or dependent variables, that take the form of counts, proportions, dichotomies (1/0), positive continuous values, as well as values that follow the normal Gaussian distribution. Logistic, Poisson, and negative binomial regression models are three of the most noteworthy GLM family members.

    Note:  Detailed study of model specification and the interpretation of software output is handled in statistics.com's individual courses on regression, logistic regression, count data modeling, etc.

    Tuition: $549 (5.0 CEUs) New available dates:
    April 03, 2015 to May 01, 2015April 01, 2016 to April 29, 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 Resampling Methods The course introduces the basic concepts and methods of resampling methods, including bootstrap procedures and permutation (randomization) tests, with little or no complex theory or confusing notation. Tuition: $389 (3.75 CEUs) New available dates:
    January 23, 2015 to February 13, 2015July 03, 2015 to July 24, 2015
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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 Structural Equation Modeling This course covers the fundamental concepts and theory of Structural Equation Modeling:  model specification, model identification, model estimation, model testing, and model modification.  Reading assignments, examples and exercises are included using the LISREL software package. Tuition: $549 (5.0 CEUs) New available dates:
    May 15, 2015 to June 12, 2015November 06, 2015 to December 04, 2015May 13, 2016 to June 10, 2016November 04, 2016 to December 02, 2016May 12, 2017 to June 09, 2017November 03, 2017 to December 01, 2017May 11, 2018 to June 01, 2018November 02, 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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  • Many-Facet Rasch Measurement This course will cover the analysis and interpretation of judge-intermediated ratings, like essay grading, Olympic ice-skating, therapist ratings of patient behavior, etc. Tuition: $549 (5.0 CEUs) New available dates:
    August 14, 2015 to September 11, 2015August 12, 2016 to September 09, 2016August 11, 2017 to September 08, 2017August 10, 2018 to September 07, 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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  • Maximum Likelihood Estimation This course will cover the derivation of maximum likelihood estimates, and their properties. Tuition: $249 (2.5 CEUs) New available dates:
    April 17, 2015 to May 01, 2015November 27, 2015 to December 11, 2015
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  • Meta Analysis This course will explain meta analysis - the methods that are used to assess multiple statistical studies on the same subject and draw conclusions. Dr. Rothstein will be the primary discussion leader for this course. Tuition: $629 (5.0 CEUs) New available dates:
    April 03, 2015 to May 01, 2015July 24, 2015 to August 21, 2015April 01, 2016 to April 29, 2016July 22, 2016 to August 19, 2016April 07, 2017 to May 05, 2017July 21, 2017 to August 18, 2017
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  • Meta Analysis 2 Meta-Analysis refers to the statistical analyses that are used to synthesize summary data from a series of studies.  This course covers some advanced issues in meta-analysis.  Participants should have completed the basic course in meta-analysis or an equivalent. Tuition: $549 (5.0 CEUs) New available dates:
    August 28, 2015 to September 25, 2015August 26, 2016 to September 23, 2016August 25, 2017 to September 22, 2017
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  • Mixed and Hierarchical Linear Models This course will explain the basic theory of linear and non-linear mixed effects models, including hierarchical linear models. It will outline the algorithms used for estimation, primarily for models involving normally distributed errors, and will provide examples of data analysis. The course aims at providing a basic understanding and knowledge of the mixed effect models that will allow you to use them in practice. Tuition: $549 (5.0 CEUs) New available dates:
    May 08, 2015 to June 05, 2015May 06, 2016 to June 03, 2016May 05, 2017 to June 02, 2017May 04, 2018 to June 01, 2018
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  • Modeling Count Data This course deals with regression models for count data; i.e. models with a response or dependent variable data in the form of a count or rate. The course will cover Poisson regression, the foundation for modeling counts, as well as extensions and modifications to the basic model. Tuition: $549 (5.0 CEUs) New available dates:
    May 22, 2015 to June 19, 2015October 30, 2015 to November 27, 2015May 20, 2016 to June 17, 2016October 27, 2017 to November 24, 2017
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  • Modeling Longitudinal and Panel Data This course covers the extension of Generalized Linear Models (GLM) to model varieties of longitudinal and clustered data, called panel data. Tuition: $549 (5.0 CEUs) New available dates:
    July 17, 2015 to August 14, 2015July 15, 2016 to August 12, 2016July 14, 2017 to August 11, 2017
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  • Multivariate Statistics This course covers key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis and classification. Tuition: $549 (5.0 CEUs) New available dates:
    February 06, 2015 to March 06, 2015July 10, 2015 to August 07, 2015
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  • Political Analytics and Microtargeting This course will teach you how to apply predictive modeling methods to target voters in political campaigns. Tuition: $549 (5.0 CEUs) New available dates:
    March 06, 2015 to April 03, 2015August 28, 2015 to September 25, 2015March 04, 2016 to April 01, 2016August 26, 2016 to September 23, 2016March 03, 2017 to March 31, 2017August 25, 2017 to September 22, 2017March 02, 2018 to March 30, 2018August 24, 2018 to September 21, 2018
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  • Practical Rasch Measurement - Core Topics Rasch analysis constructs linear measures from scored observations, such as responses to multiple-choice questions, Likert scales and quality-of-life assessments. This course covers the practical aspects of data setup, analysis, output interpretation, fit analysis, differential item functioning, dimensionality and reporting. Tuition: $549 (5.0 CEUs) New available dates:
    January 02, 2015 to January 30, 2015May 29, 2015 to June 26, 2015October 16, 2015 to November 13, 2015
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  • Practical Rasch Measurement - Further Topics Continues the exploration of Rasch theory and its application in the Winsteps software begun in Practical Rasch Measurement-Core Topics. The visual step-by-step tutorial propels you along the road to success. This course introduces exciting new topics and delves into earlier topics more deeply. Tuition: $549 (5.0 CEUs) New available dates:
    July 03, 2015 to July 31, 2015
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  • Principal Components and Factor Analysis In this course, you will learn how to make decisions in building a factor analysis model - including what model to use, the number of factors to retain, and the rotation method to use. Tuition: $549 (5.0 CEUs) New available dates:
    May 22, 2015 to June 19, 2015May 20, 2016 to June 17, 2016May 19, 2017 to June 16, 2017May 18, 2018 to June 15, 2018
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  • Rasch Applications, Part 1: How to Construct a Rasch Scale This course is a practicum.  You will learn how to construct a scale for a test or survey that is likely to produce data fitting dichotomous or polytomous Rasch models, and you will deploy it in an actual survey or test. Tuition: $549 (5.0 CEUs) New available dates:
    September 04, 2015 to October 16, 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 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:
    March 20, 2015 to April 17, 2015March 18, 2016 to April 15, 2016March 17, 2017 to April 14, 2017March 16, 2018 to April 13, 2018
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Earn a Certificate

When To Apply

Applications are accepted and students are enrolled year round on a rolling basis. You pay an application fee and submit it with your application form. You may pay the fee online here, or enclose a check (USD drawn on a US bank) with your application. NOTE: The application is your opportunity to specifically outline your past education and experience, and provide any other information you want us to consider during our review. The value of this background and experience is the ability to place the statistical methods covered in the Program in an appropriate application context. Once we have accepted your application, we will be happy to assist you with more specific questions about PASS.


Admission Criteria and Prerequisites

  1. A Bachelor's degree from an accredited college or university.
  2. The successful recent completion of an introductory statistics course equivalent to Statistics.com's Statistics 1 and Statistics 2,* (please provide proof in your PASS application).

*If you do not meet this requirement, you may still enroll in PASS. Upon review of your application, we will determine whether you need to take Statistics.com's Statistics 1 and 2. If you do require these foundational courses, we will register you for them and waive the entire tuition fee for these two courses.


Procedure for Enrollment and Matriculation in PASS

  1. Complete and submit the application, your photograph, and the payment of the application fee. Notification of approval is sent usually within one week.
  2. After your application is approved, enroll in the PASS of your choice here and pay the enrollment fee.
  3. If you have NOT already met the introductory statistics requirement, you will be registered for the Institute's Statistics 1 and 2 courses. Full tuition is waived for matriculated PASS candidates.
  4. After you submit your application and receive approval, pay the enrollment fee, and meet the introductory statistics requirement, you will be matriculated into the program and are considered a PASS candidate. You may now register for classes as a PASS candidate and receive our academic tuition deduction - specify PASS as your academic affiliation during the online registration process.

Rules and Policies

  • Once you are matriculated in PASS, you are considered a student at the Institute for Statistics Education at Statistics.com.
  • You must be a fully-matriculated PASS candidate to be eligible to receive the academic tuition deduction provided during online registration, and to receive PASS credit for courses.
  • The Program enrollment fee is a required one-time charge in addition to tuition for individual courses.
  • You are expected to complete all the courses in your Program within 5 years of your matriculation into the program. Any exceptions must be approved in writing by the Institute prior to that 5-year deadline.
  • Upon completion of your PASS, you will receive a Certificate and your official transcript.
  • Up to three Institute courses may be taken prior to enrolling in PASS; credit for these courses may be applied to your PASS transcript once you are a matriculated PASS candidate, provided that adequate marks are earned.

Description

Since its founding in 2002, the Institute has been the global pioneer and leader in statistics and analytics education.  The Institute now offers 100+ online courses in statistics and analytics, plus four certificate programs. 

This Social Science certificate program focuses on those courses which include the statistical methods needed for designing and analyzing studies (including Bayesian analysis), conducting surveys and analyzing the data they yield, and a unique concentration strand devoted to Rasch methods .  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 19.5 credits in the U.S. academic system.

Program Objectives

The program consists of thirteen 4-week courses.  You will learn:

  • The design and analysis principles for research studies
  • The fundamental concepts behind statistical modeling
  • How to fit linear and logistic regression models, interpret output, and conduct diagnostics
  • Appropriate designs and sampling plans for surveys
  • How to determine sample size for a study, and how to calculate power
  • Techniques for analyzing categorical data (electives)
  • Bayesian methods for analyzing data (electives)


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.

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From a Student Profile:

I realized one of my work projects would benefit from deeper statistical analysis, including functions I had a good background in and knew at one time, but I needed to dust the cobwebs off and catch up to changes in the field.

Douglas D. Reimel, Jr.

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