Academics >  IC BLUEprint >  Statistical Literacy Embedded Experience > 

First-Year Seminar
First-Year Seminar Fundamentals
Creative Expressions
Cultures and Worldview
Science in Society
Social, Spiritual, and Philosophical Issues
Senior Capstone Experience
Course Criteria
Outcomes & Definitions
Connected Courses
Writing Extensive Embedded Experiences
Speaking Extensive Embedded Experiences
U. S. Diversity/Global Awareness Embedded Experience
Community/Civic Engagement Embedded Experience
Ethical and Responsible Action Embedded Experience
Information Literacy Embedded Experience
Statistical Literacy Embedded Experience
Graduation Requirements for the IC BLUEprint General Education Program
The IC BLUEprint General Education Program
Policies for Transfer Students

Statistical Literacy Embedded Experience

Statistical Literacy Embedded Experiences are those which are intentionally designed for students to develop the ability to appropriately collect and analyze quantitative data as well as critically evaluate and present data-based arguments that address important questions about our world.

Intended Learning Outcome

Upon completion of the Statistical Literacy Embedded Experience requirement, students will have learned to collect and analyze quantitative data and critically interpret and present results.

• To understand data collection means to
1. identify target populations and form appropriate samples;
2. address methods and ethical issues of obtaining data;
3. identify appropriate scales of measurement;
4. identify common sources of bias in data.

• To analyze data means to
1. describe a data set using graphical, verbal, and numerical summaries;
2. appropriately use inferential statistics to interpret a data set to address questions about a population;
3. distinguish statistical vs. practical significance and correlation vs. causation;
4. know when to consult a statistician.

• To critically interpret data means to
1. identify what arguments are being made with the data;
2. understand the context and motivation of the argument;
3. recognize limitations of the use of data and statistical inference;
4. understand how to critique arguments presented via popular and professional media.

• To critically present data means to
1. describe the nature of the data being used;
2. explain a given problem in context;
3. create texts to convey statistical information in a logical and ethical manner;
4. communicate the limitations of the statistical procedures employed.
For faculty seeking course guidelines, click on the link below to "read more." 

search login