Statistics and Data Interpretation

Statistics and Data Interpretation

Advanced Data Processing and Statistical Analysis

The Research Computing Center (RCC) offers advanced data processing consultations and statistical analysis services to the UNH research community.  Examples of completed projects

Statistical Consulting Service -- UNH Department of Mathematics and Statistics       UNH Math Dept Statistics Consulting Service flyer

This statistical consulting service provides assistance with experimental design, data collection design, data display and statistical analysis, and interpretation of findings.

UNH Internal Requests: Requests may be for assistance in preparing research grants, writing papers for publication, preparing conference presentations, assistance in research for theses and dissertations.

Consulting Limitations:  We provide advice, but not analysis of data.  We do not review completed theses. No service will be provided for homework and project assignments in regular courses. 

External Request: Services may also be provided to external clients, such as to local/regional industries that request assistance for experimentation, clinical trials, and data analysis. 

Fees: Service is free of charge for smaller projects and will typically involve an initial meeting and a concluding follow-up meeting.  Larger projects will be fee-based; fees will be negotiated. 

Appointments:    Please contact

Graduate Assistant:  Beth Ziniti   elo4@wildcats.unh.edu  OR
Director:  Ernst Linder  elinder@unh.edu 603 862 2687 

Application Form:  Please fill out a request application form: http://goo.gl/forms/MQetva4CtL    

 

Web and Print Resources
 

This series of 31 video modules by the U.S. Dept. of Education's Institute of Educational Sciences (US ED/IES) provides opportunities for researchers to learn more about how to design scientifically valid single-case design research studies and appropriately analyze single-case data.

 

Translating the Statistical Representation of the Effects of Education Interventions into More Readily Interpretable Forms

This 2012 report from the US Dept. of Education, Institute of Education Sciences (US ED/IES) provides "suggestions to researchers about ways to present statistical findings about the effects of educational interventions that might make the nature and magnitude of those effects easier to understand.

These suggestions and the related discussion are framed within the context of studies that use experimental designs to compare measured outcomes for two groups of participants, one in an intervention condition and the other in a control condition"

Its purpose is to stimulate and guide researchers who conduct and report these kinds of education intervention studies "to go a step beyond reporting the statistics that emerge from their analysis of the differences between experimental groups on the respective outcome variables. With what is often very minimal additional effort, those statistical representations can be translated into forms that allow their magnitude and practical significance to be more readily understood by the practitioners, policymakers, and even other researchers who are interested in the intervention that was evaluated."

 

Video Training Modules Pre-Elementary Education Longitudinal Study (PEELS)

These PEELS data training modules produced by the National Center for Special Education Research are intended to be a resource to researchers who would like to use the PEELS dataset to conduct research addressing students with disabilities.

The modules provide opportunities for researchers to learn more about:

  • the background of the PEELS study
  • the study design and sampling
  • the assessments and instruments used to collect PEELS data,
  • how to access and manipulate PEELS data in SPSS and WesVar
  • how to conduct longitudinal and regression analyses with PEELS data
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