This course focuses on using the most common business analytics tools in the industry. You'll build foundational skills in SQL and Tableau to extract, analyze, and visualize data. You'll also dive into database design, hypothesis testing, and the nuances of big data in the business landscape.
Prerequisite: DATA 1350 Introduction To Data Analytics with a grade of C- or better and MATH 1300 Statistics or BUSAD 2100 Business and Economic Statistics.
This course is offered online through a consortium of accredited colleges and universities. Instruction is provided by faculty employed by partner institutions within the consortium, with technology and administrative support provided by Rize Education. Oversight of courses offered through the consortium are reviewed and approved by Nebraska Wesleyan University. Students register through Nebraska Wesleyan University and receive academic credit from Nebraska Wesleyan University
DATA 1350 Introduction To Data Analytics (4 hours)
An introduction to data analytics from three perspectives: inferential thinking, computational thinking and real-world relevance. Topics include, but are not limited to: organizing real-world data by filtering, sorting, and using pivot tables; exploring data; visualizing data; using programming tools to analyze data through a statistical lens. Statistical topics include: center and spread of data, descriptive statistics, inferential statistics, regression, causality, classification and prediction.
(Normally offered every fall semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving
MATH 1300 Statistics (3 hours)
An introduction to statistics concepts with an emphasis on applications. Topics include descriptive statistics, discrete and continuous probability distributions, the central limit theorem, confidence intervals, hypothesis testing, and linear regression.
(Normally offered every semester.)
Archway Curriculum: Foundational Literacies: Mathematical Problem Solving
BUSAD 2100 Business and Economic Statistics (3 hours)
An introduction to descriptive and inferential statistics. Topics include gathering, organizing, interpreting, and presenting data with emphasis on hypothesis testing as a method for decision making in the fields of business and economics. Procedures include z-tests, t-tests, ANOVAs, correlation, and simple regression.
Prerequisite(s): Demonstrated proficiency in high school algebra or permission of the instructor.