Skip to main content.

Management Quantitative Method (MGQ)

MGQ Courses

  • The Learning Environment

    The Learning Environment

    Courses in the program are delivered by highly qualified faculty using instructional approaches that ensure the learning outcomes of each course. Students take a series of prerequisite courses early in their academic careers that serve as a foundation for the upper-level core curriculum. There are upper-level core requirements that cut across multiple management disciplines providing a comprehensive understanding and application of contemporary management practices. Many courses are project-based integrating case studies. The capstone course offers academic training with real-world exposure through experiential learning.

    Several of the courses are delivered via Digital Access or in lecture halls, while the other half average 45 students. Recitations that accompany core courses are taught by teaching assistants in class sizes of approximately 30 or less. The class size for additional required concentration courses typically average 45 students.

    About Our Facilities

    The Jacobs Management Center and the adjacent Alfiero Center offer a complete home for management students, faculty and staff. Together, they are among only a few buildings at UB that commingle classrooms and offices, creating an interactive community of professionals, students and scholars.

    About Our Faculty

    Nine members of our faculty are recipients of the SUNY Chancellor's Award for Excellence in Teaching, which recognizes outstanding teaching ability through superb classroom performance. These scholars bring to their classes broad interests and current, far-ranging knowledge.

    The faculty of the program consists of ladder faculty and clinical faculty. Both types of faculty have the highest academic degree required for their appointment. Ladder faculty members hold doctoral degrees and maintain an active research record by publishing in the top and leading academic journals in their area of expertise. Clinical faculty members hold one or several professional certificates (e.g., CPA) in addition to academic degrees required for their appointment. Academically qualified clinical faculty also publish in their area of expertise. Our faculty frequently attend conferences, workshops, and other professional meetings to update their knowledge and develop professional networks. Our faculty is actively engaged in mentoring students (e.g., serving as faculty advisor of student clubs and coaching student teams in case competition) and ensuring a high-quality learning environment.

    This expertise enables them to illustrate the theoretical side of business concepts and bring them to life with practical industry examples. Our faculty's commitment to teaching, along with their contacts, availability and friendliness, makes them a powerful and highly approachable resource for our students.

    Faculty List Directory

    Please visit the School of Management faculty and staff directory for additional information about our faculty.

  • MGQ 201LR Introduction to Statistics for Analytics

    This course is designed to introduce students to statistical concepts and applications and cultivate student statistical literacy. Topics that are covered include descriptive statistics, probability distributions, the Central Limit Theorem, applications of the normal distribution, sampling, confidence intervals, and hypothesis testing. In the first part of the course, students will become proficient in using Microsoft Excel to compute and convey information; in the second part of the course, students will use calculators to estimate probabilities, perform statistical functions, and inform decisions.

    Credits: 4
    Grading: Graded (GRD)
    Typically Offered: Fall, Spring, Summer
    Requisites: Pre-Requisite: Sophomore standing
  • MGQ 301LR Statistical Decisions in Management

    Strengthens skills in the use of statistical methods for decision making and in the interpretation of computer output. Topics covered include estimation, hypothesis testing, regression, and analysis of variance.

    Credits: 3
    Grading: Graded (GRD)
    Typically Offered: Fall, Spring
    Requisites: MGQ 201 and junior standing in the School of Management. Students may not repeat upper-level School of Management courses in which they have earned passing grades without consulting with an academic advisor.
  • MGQ 408LEC Business Analytics and Data Science

    The goal of this course is for students to cultivate analytical and technical skills that enable them to extract meaning from large amounts of data. Students will think about how to use data to address different types of business problems and will employ techniques from analytics and data science to harvest and mine data, identify patterns, create predictive models, and put forth data-driven recommendations. Students need to have proficiency in Excel and basic statistics, and will be expected to learn and use R as a data manipulation tool. MGQ 201 and MGQ 301 are pre-requisite courses.

    Credits: 3
    Grading: Graded (GRD)
    Typically Offered: Fall, Spring
    Requisites: Pre-Requisite: MGQ 201 and MGQ 301; junior or senior standing in the School of Management.
  • MGQ 496TUT Data Analytics Internship

    Provides students with an opportunity to apply classroom theories to hands-on, project based learning in real world, professional work environments (employer sites), and then reflect upon those experiences through assignments as detailed in the corresponding syllabus. To secure these learning opportunities, students apply to appropriate postings vetted by the Internships and Experiential Learning (IEL) team, in an on-line database, and are eligible to be selected by employers for interviews. Students are also allowed to locate internships outside of this database and report them to the IEL team for review and approval. Each employer site assigns a specific project to the student to be completed within the 150 hours during the course of a semester. Students participate in these opportunities under the supervision and mentorship of an on-site professional with expertise related to the curriculum, and receive exposure to and practice in day-to-day operations. In this specific course, these opportunities are based in the area of Data Analytics.

    Credits: 1 - 3
    Grading: Pass/Not Pass (PNP)
    Typically Offered: Varies
  • MGQ 499TUT Independent Study

    Credits: 1 - 8
    Grading: Graded (GRD)
    Typically Offered: Fall, Spring, Summer
Visit the Office of the Registrar’s Class Schedules page for more detailed and updated information.
Published: Jun 21, 2022 10:20:39