This course covers descriptive and inferential techniques for business and economic decision-making. Topics which are included in this course are the collection, description and analysis and summarization of data; probability; discrete and continuous random variables; the binomial and normal distributions; tests of hypotheses; estimation and confidence intervals; linear regression; and correlational analysis. Microsoft Excel will be used to analyze data throughout the course.

Introduction to the quantitative methods of analysis to business problems. Topics of study include collection of data, statistical description, probability theory, probability distributions, sampling theory, estimation of parameters and testing hypothesis.

This course will provide the student the opportunity to learn about data analytics as it applies to business. Data Analytics is a topic of increasing importance for many organizations as the need for data-driven insights and recommendations grows throughout the business industry. This course gives students an overview of data literacy and quantitative skills. This provides students practical experience with different types of data and the tools that are used to analyze it. These skills are essential for success in data-driven fields of study and in the workplace. Various software tools will be introduced to enhance students' hands-on capabilities.

This course promotes tools for effective decision-making using a variety of techniques. Students learn to apply analytical methods to the processes of data collection, presentation, assessment and interpretation. The course emphasizes quantitative and statistical methods and includes topics such as correlation, regression analysis, data mining and model optimization.