About the Course
In this project-based course, you will have the opportunity to answer a question that you feel passionately about through independent research based on existing data. Students will have the opportunity to develop skills in generating testable hypotheses, preparing data for analysis, conducting descriptive and inferential statistical analyses, and presenting research findings.
About the Instructor(s)
Lisa Dierker is a Professor of Psychology at Wesleyan University with training in chronic disease epidemiology. With expertise in the application of innovative statistical methods, she has spent her career developing collaborative relationships with leading experts across multiple disciplines (e.g. public health, statistics, medicine, engineering, pharmacology and neuroscience). She has also shown an extremely strong commitment to teaching undergraduate courses in the areas of statistics and research methods, and with funding from the National Science Foundation, has spent the last three years developing an original project-based curriculum specifically aimed at increasing the number of students exposed to applied statistics.Course Syllabus
- Data, data sets and data documentation
- Statistical software; Review of software specific code for data management
- Descriptive statistics and data visualization
- Comparing means (ANOVA), tests of categorical independence (Chi Square) and Pearson Correlation (r)
- Post hoc tests and Moderation
- Presenting statistical results
Activities include:Exploring data documentation
Running a basic program
Data management
Graphing
Testing and interpreting bivariate associations
Testing and interpreting further bivariate associations and post hoc paired comparisons
Writing models
Recommended Background
No background required. All are welcome.
Course Format
We will provide students with a selection of data sets with which to work (from studies focused on topics as diverse as caterpillar ecology, adolescent health, and social and economic development). Based on the student’s choice of data, each generates testable hypotheses, prepares data for analysis (i.e. data management), selects and conducts descriptive and inferential statistical analyses; and evaluates, interprets and presents research findings. Evaluations will include quizzes, applied data assignments and a final written presentation of results. Supporting materials will be presented as text, video, and interactive content.
SOFTWARE
SOFTWARE
In supporting you in answering questions with data, we are going to be using SAS Enterprise Guide through the OnDemand educational platform. SAS OnDemand for Academics provides a no-cost on-line delivery model to students for learning data management and statistics.
SYSTEM REQUIREMENTS
Check the following guidelines to ensure you can access the software. Your system must meet these requirements for SAS OnDemand for Academics to be fully supported.
Operating systems:- Microsoft Windows 7 Home Premium and above (32-bit or 64 bit).
- Microsoft Windows Vista Home Premium (32-bit or 64 bit).
- Microsoft Windows XP Professional.
(Other versions of Microsoft Windows Vista might work, but have not been fully tested and are not supported by SAS.)
MACINTOSH OPERATING SYSTEMS ARE NOT SUPPORTED.
***If missing, then Microsoft .NET Framework version 3.5 Service Pack 1 will be installed for users of Microsoft Windows XP Professional. Depending on the files required, installation could take from 5 to 90 minutes.
Internet browser:
Microsoft Internet Explorer 8 or earlier. Other Internet browsers might work but have not been fully tested and are not supported by SAS.
Hard disk space:
Approximately 80 MB of free hard disk space. You will be prompted to install Microsoft .NET if it is not on your machine. This requires additional disk space.
FAQ
Will I get a Statement of Accomplishment after completing this class?
Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor.
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