BAB310 - Quantitative Decision Making

Subject Title
Quantitative Decision Making

Subject Description
This course builds on ?Business Statistics? BAB210. Students will complete hypothesis tests for two populations, apply the multiple regression model, compute posterior probabilities, and use other advanced statistical techniques to make management decisions. Learners will utilize software to present and analyze data.

Credit Status
One degree level credit

Learning Outcomes
Upon successful completion of this subject the student will be able to:

1.       Carry out hypothesis tests for the parameters of two populations to identify the population differences;
2.       Apply a multiple linear regression model to predict the behavior of business processes;
3.       Use software to build an ANOVA table to assess the relationship between business data;
4.       Perform a chi-square test for independence to determine whether there is an association between two variables in a contingency table;
5.       Construct the payoff and opportunity loss tables to recommend the best decision;
6.       Calculate posterior probabilities to update business expectations based on new evidence;
7.       Demonstrate the use of software to carry out hypothesis tests and multiple regressions.
8.       Evaluate statistical approaches to inform management decision making.

Essential Employability Skills

    •  Communicate clearly, concisely and correctly in the written, spoken and visual form that fulfils the purpose and meets the needs of the audience.

    •  Respond to written, spoken, or visual messages in a manner that ensures effective communication.

    •  Apply a systematic approach to solve problems.

    •  Use a variety of thinking skills to anticipate and solve problems.

    •  Analyze, evaluate, and apply relevant information from a variety of sources.

    •  Show respect for diverse opinions, values, belief systems, and contributions of others.

    •  Interact with others in groups or teams in ways that contribute to effective working relationships and the achievement of goals.

    •  Manage the use of time and other resources to complete projects.

    •  Take responsibility for one's own actions, decisions, and consequences.

Academic Integrity
Seneca upholds a learning community that values academic integrity, honesty, fairness, trust, respect, responsibility and courage. These values enhance Seneca's commitment to deliver high-quality education and teaching excellence, while supporting a positive learning environment. Ensure that you are aware of Seneca's Academic Integrity Policy which can be found at: http://www.senecapolytechnic.ca/about/policies/academic-integrity-policy.html Review section 2 of the policy for details regarding approaches to supporting integrity. Section 2.3 and Appendix B of the policy describe various sanctions that can be applied, if there is suspected academic misconduct (e.g., contract cheating, cheating, falsification, impersonation or plagiarism).

Please visit the Academic Integrity website http://open2.senecac.on.ca/sites/academic-integrity/for-students to understand and learn more about how to prepare and submit work so that it supports academic integrity, and to avoid academic misconduct.

Discrimination/Harassment
All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at student.conduct@senecapolytechnic.ca.

Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Accessibility Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.

Camera Use and Recordings - Synchronous (Live) Classes
Synchronous (live) classes may be delivered in person, in a Flexible Learning space, or online through a Seneca web conferencing platform such as MS Teams or Zoom. Flexible Learning spaces are equipped with cameras, microphones, monitors and speakers that capture and stream instructor and student interactions, providing an in-person experience for students choosing to study online.

Students joining a live class online may be required to have a working camera in order to participate, or for certain activities (e.g. group work, assessments), and high-speed broadband access (e.g. Cable, DSL) is highly recommended. In the event students encounter circumstances that impact their ability to join the platform with their camera on, they should reach out to the professor to discuss. Live classes may be recorded and made available to students to support access to course content and promote student learning and success.

By attending live classes, students are consenting to the collection and use of their personal information for the purposes of administering the class and associated coursework. To learn more about Seneca's privacy practices, visit Privacy Notice.

The instructor, in both a traditional classroom and lab environment, assists the learner in developing advanced statistical analysis skills through the presentation of critical concepts relating to the business fields.  Learners will develop quantitative decision making skills through the completion of facilitated lab exercises.  Concepts and skills will be reinforced through self-directed lab exercises.  Interpretive and analysis skills will be fine-tuned through collaborative discussions.