Social Science Statistics

Online Certificate Program

Social Science Certificate Program

Program Content

The Social Science Certificate Program consists of thirteen, 4-week courses offered completely online at Statistics.com. There is a small group of required topics, plus a number of electives.  The workload for the entire program is the equivalent of 19.5 credits in the U.S. academic system.  At the completion of the program you will have learned how to:

  • 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)

 

Planning my Program

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) Next three dates:
    October 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) Next three dates:
    February 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) Next three dates:
    January 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) Next three dates:
    October 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) Next three dates:
    November 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) Next three dates:
    March 18, 2016 to April 15, 2016August 12, 2016 to September 09, 2016March 17, 2017 to April 14, 2017August 11, 2017 to September 08, 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) Next three dates:
    April 22, 2016 to May 20, 2016April 21, 2017 to May 19, 2017April 20, 2018 to May 18, 2018
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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) Next three dates:
    To be scheduled.
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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) Next three 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) Next three dates:
    October 23, 2015 to November 20, 2015April 22, 2016 to May 20, 2016April 21, 2017 to May 19, 2017April 20, 2018 to May 18, 2018
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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) Next three dates:
    September 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) Next three dates:
    September 18, 2015 to October 16, 2015February 19, 2016 to March 18, 2016September 16, 2016 to October 14, 2016February 17, 2017 to March 17, 2017September 15, 2017 to October 13, 2017February 16, 2018 to March 16, 2018September 14, 2018 to October 12, 2018
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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) Next three dates:
    April 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) Next three dates:
    August 28, 2015 to September 25, 2015February 26, 2016 to March 25, 2016August 26, 2016 to September 23, 2016February 24, 2017 to March 24, 2017August 25, 2017 to September 22, 2017February 23, 2018 to March 23, 2018August 24, 2018 to September 21, 2018
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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) Next three dates:
    May 20, 2016 to June 17, 2016May 19, 2017 to June 16, 2017May 18, 2018 to June 15, 2018
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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) Next three dates:
    January 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) Next three dates:
    July 08, 2016 to July 29, 2016July 14, 2017 to August 04, 2017July 13, 2018 to August 03, 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) Next three dates:
    February 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) Next three dates:
    November 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) Next three dates:
    September 04, 2015 to October 02, 2015November 13, 2015 to December 11, 2015March 11, 2016 to April 08, 2016September 02, 2016 to September 30, 2016March 10, 2017 to April 07, 2017September 01, 2017 to September 29, 2017March 02, 2018 to March 30, 2018August 31, 2018 to September 28, 2018
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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) Next three dates:
    August 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) Next three dates:
    March 18, 2016 to April 15, 2016June 24, 2016 to July 22, 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) Next three dates:
    November 27, 2015 to December 11, 2015April 22, 2016 to May 06, 2016November 25, 2016 to December 09, 2016April 21, 2017 to May 05, 2017November 24, 2017 to December 08, 2017April 20, 2018 to May 04, 2018November 23, 2018 to December 07, 2018
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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) Next three dates:
    April 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) Next three 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) Next three dates:
    April 29, 2016 to May 27, 2016April 28, 2017 to May 26, 2017April 27, 2018 to May 25, 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) Next three dates:
    October 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) Next three dates:
    July 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) Next three dates:
    February 05, 2016 to March 04, 2016July 08, 2016 to August 05, 2016February 03, 2017 to March 03, 2017July 07, 2017 to August 04, 2017February 02, 2018 to March 02, 2018July 06, 2018 to August 03, 2018
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  • Persuasion Analytics and Targeting
    This course will teach you how to apply predictive modeling methods to identify persuadable individuals, and to target voters in political campaigns. Tuition: $549 (5.0 CEUs) Next three dates:
    August 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) Next three dates:
    October 16, 2015 to November 13, 2015January 01, 2016 to January 29, 2016May 27, 2016 to June 24, 2016October 14, 2016 to November 11, 2016January 06, 2017 to February 03, 2017May 26, 2017 to June 23, 2017October 13, 2017 to November 10, 2017January 05, 2018 to February 02, 2018May 25, 2018 to June 22, 2018October 12, 2018 to November 09, 2018
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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) Next three dates:
    July 01, 2016 to July 29, 2016June 30, 2017 to July 28, 2017June 29, 2018 to July 27, 2018
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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) Next three dates:
    May 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) Next three 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) Next three dates:
    September 11, 2015 to October 09, 2015September 16, 2016 to October 14, 2016September 15, 2017 to October 13, 2017
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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:$595
Estimated Required Course Tuition: $3004
Estimated Electives Course Tuition: $3681
Estimated Material Cost: $910
Estimated Total Cost: $8265

Is there an application deadline?

No - applications are accepted and students are enrolled year round on a rolling basis. See the timeline tool in the "Program" tab to see the recommended sequence of courses starting in any given month.

 

Are there admission requirements?

We'd like you to have a Bachelor's degree from an accredited college or university.

Also, you should have recently had introductory statistics, equivalent to Statistics.com's Statistics 1 and Statistics 2 . If you haven't, or if you'd like to go over that ground again, no worries. We'll put you in Statistics 1 and 2 at no charge once we accept your application! Statistics 1 starts at the beginning of each month.

 

What are the fees?

The application fee is $75, which you can pay here. The enrollment fee is $595, which includes free enrollment in Statistics.com's Statistics 1 and Statistics 2 courses if needed. Once you are enrolled, you pay course tuition fees "as you go," at the discounted academic rate.

 

Is there any particular way I should schedule my courses?

Not really, no.  Scheduling is quite flexible with various courses offered all throughout the year and a class format that does not require you to be online at any specific times.  Most PASS students choose to take one course at a time, but we encourage you to plan your program in a way that fits your schedule and helps you personally learn best.

 

Can I get credit for courses I have already taken at Statistics.com?

Yes. You can apply up to three prior courses to your program, provided you got adequate marks.

 

If I have already mastered a topic from my work or prior academic experience, do I need to repeat it?

No. We do not want to waste your time. Just share with us how you covered the topic and we'll swap out that course for something else.

 

The courses in the PASS programs don't exactly match what I need. Can I craft a custom program?

Maybe. Contact us so we can review what you want to do, and work together to create a program that makes sense!

 

How long do I have to complete the PASS certificate?

Five years.

 

Are the certificate programs accredited?

Most of the individual courses in the Data Science certificate programs have been approved for academic credit recommendation by the American Council on Education (ACE), which makes it relatively easy to transfer academic credit for these courses to another educational institution. Those same courses have also been approved as recognized professional development courses by INFORMS, the Operations Research Society. The Institute for Statistics Education is not itself accredited as an academic institution.

 

Still have questions?

Contact the registrar (ourcourses [at] statistics.com) and we'll try to answer them as well as possible.

 

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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.

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