ME1316 Quantitative Business and Operations Analytics 6.0 credits

See the course syllabus.

The ability to analyze and draw conclusions from quantitative data, and to critically review analyses performed by others, plays a central role in many professional roles. This course aims to develop students' understanding of how quantitative analyses can be used in business. The course focuses on the application of statistical methods to perform business and operational analyses based on large datasets.

During the first half of the course, principles for drawing conclusions from data are discussed, with examples taken from important forms of analytical work. The course includes two project assignments, through which students will develop their ability to analyze and present data in an industrial context. All teaching elements are designed to support the development of the ability to critically review both one's own and others' analyses through discussions of limitations and assumptions in both methods and data.

To provide the course participants applied knowledge of quantitative data analysis in different types of industrial activities. The aim is that the course participants should be prepared on completion of the course to both carry out analyses, interpret the results of these analyses and to critically review analyses completed by others.

After passing the course, the students should be able to:

1. Give an account of why and in what ways quantitative analyses are used in business operations.
2. Apply quantitative analytical methods on operational data such as production data, customer data and product data.
3. Interpret result of statistical analysis in an business context.
4. Critically review fundamental methodological choices, data quality, and assumptions in a completed analysis and explain how these affect the reliability of the conclusions drawn.

45 first cycle higher education credits,

6 higher education credits in basic industrial engineering and management or in business administration,

Knowledge in probability theory and statistics equivalent to at least 6 higher education credits, for example by having participated in SF1918 Probability Theory and Statistics.

None in addition to the specific prerequisites.

• SEM1 - Seminar assignment, 1.0 credits, grading scale: P, F
• INL1 - Assignment, 3.0 credits, grading scale: A, B, C, D, E, FX, F
• TEN1 - Exam, 2.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.