Data Analytics Minor
This interdisciplinary minor prepares students to use data analysis within their careers. Students will develop their skills to evaluate and interpret data in order to make better-informed decisions. In addition, students will develop their visualization and communication skills. The minor’s selective elective courses provide an opportunity to apply the data analytic skills in a specific area of related interest.
|Minor Requirements (22 credits)|
|Foundational Statistics Course|
|Select one of the following:||4|
|Data Analytics Core Course|
|IIPHYS-342||Data Analysis for Scientists (a C or higher is required)||4|
|ISMGT-383||Applied Data Analysis & Vis (a C or higher is required)||4|
|Select one from each cluster: (please note some courses have prerequisites)|
|Methods and Tools Cluster:||4|
|These courses develop a deeper understanding of techniques and methodologies used in various disciplines for computational background, data acquisition and preliminary analysis.|
|Population and Community Ecology|
|Quantitative & Qualitative Methods|
|Research Methods in Psychology|
|Sociological Research Methods|
|Active Experimentation Cluster:||4|
|These courses use data analysis techniques to focus on problem solving, interpretation, and implementation of scientific decision making.|
|Research Methods in Human Movt|
|Strategic Digital Marketing|
|Sociological Quantitative Analysis|
|Mechatronics and Automation|
|Portfolio & Career Course|
|MGT-384||Data Analytics Portfolio Plus||2|
Upon completion of the Data Analytics minors students will:
- Gain introductory data analytics skills, including a basic understanding of statistical testing, computer programming and the ability to explore and analyze concepts. The elective courses provide an opportunity to apply the skills in a specific area of interest.
- Analyze data, test claims and draw valid conclusions using appropriate statistical methodology.
- Recognize relationships between data and specific areas of practice such as biology, business, economics, criminal justice, etc.
- Retrieve, organize and visualize data using a variety of analytical tools.
- Recognize patterns, ask intelligent questions and generate insights from different data sets.
- Tell the story with the data - visually, orally, and in writing.
- Develop students’ data analytic identity by creating their data analytics portfolio and experiences using present day tools.