Davenport University

What you'll study

The programme develops advanced skills in quantitative analysis, decision support and managerial applications. Core topics typically include multivariate statistics, predictive analytics, forecasting, optimisation and operations research, simulation modelling, and data visualisation. Students also study subjects in database design, programming for analytics (commonly using tools such as R or Python), and applied econometrics.

Courses are usually delivered through a mix of lectures, computer lab work and project-based assignments. Many students complete a capstone project or practicum in which they work with real organisational data to solve a clearly defined management problem; some pathways may offer a thesis option for those considering research or further academic study.

• Advanced Statistical Methods and Inference
• Predictive Analytics and Machine Learning for Management
• Optimisation and Operations Research
• Forecasting and Time Series Analysis
• Simulation Modeling and Decision Analysis
• Database Management and Data Warehousing
• Visualisation and Communications for Decision Makers
• Capstone Project or Research Thesis

Structure and delivery

The degree is typically modular and can be taken full-time or part-time. Courses blend quantitative theory with applied case work and often use industry-standard software. Delivery options may include on-campus, evening classes and online or hybrid formats to accommodate working professionals.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree or equivalent. A background in quantitative coursework such as introductory statistics, calculus and/or introductory programming is often required; applicants without this preparation may be asked to complete bridge modules before progressing.

Typical admissions materials include an academic transcript, a current résumé or CV, a personal statement outlining goals and relevant experience, and one or more professional or academic references. Some applicants may be invited to interview. Standardised tests (such as the GRE or GMAT) may be optional or considered on a case-by-case basis depending on prior academic record and professional experience.

Relevant professional experience in analytics, operations, finance or related fields is beneficial for part-time candidates and may strengthen an application.

Career prospects

Graduates move into roles that require rigorous quantitative reasoning and the ability to communicate analytical results to managers and stakeholders. Common career paths include:

• Business or Data Analyst
• Operations Research Analyst / Operations Analyst
• Supply Chain and Logistics Analyst
• Business Intelligence or Analytics Specialist
• Risk Analyst in finance or insurance
• Healthcare Analyst / Healthcare Operations Analyst
• Management Consultant with a focus on analytics-driven improvement

The skills gained also provide a foundation for progression into leadership roles that combine technical analysis with strategic decision making, or for further study such as doctoral work in management science, operations research or applied statistics.

Why study at Davenport University

Davenport emphasises applied learning and workforce readiness, pairing quantitative training with practical projects and opportunities to work with organisations on real problems. Class sizes tend to be relatively small, allowing for direct faculty engagement and tailored feedback on analytical work.

The university’s links to regional businesses and professional networks help students secure practicum placements and employment connections. In addition, Davenport offers flexible delivery modes suited to working professionals, and career services that support résumé development, interview preparation and employer outreach.

Overall, the programme is designed for those who want to convert quantitative skills into actionable business solutions, with an emphasis on tools and methods that are immediately applicable in industry settings.