Program Overview

Course Overview

Introduction to Managerial Economics and Data Analytics

The course is obligatory in the first semester of the INGLOG study program (Program Basic Course), and consists of two modules: Basic managerial economics (50%), and Basic data analysis (50%).

Course Details

• Course Code: TLOG1015
• Credits: 7.5
• Level: Foundation courses, level I
• Course Start: Autumn 2025
• Duration: 1 semester
• Language of Instruction: Norwegian
• Location: Trondheim
• Examination Arrangement: School exam

Course Content

Module 1: Basic Industrial Economics

• Introduction to economics, with focus on business economics
• Analysis of costs, revenue, and profit
• Financial accounting
• Product costing
• Investment analysis
• Transport economics

Module 2: Basic Data Analysis

• Introduction to data analysis
• Descriptive analysis - basic statistics
• Spreadsheet modeling
• Applied data analysis for logistics (Inventory management, transportation, material handling, and quality improvement)
• Effective data reporting and presentation (dashboards)

Learning Outcome

Knowledge

By the end of the course, the student will obtain fundamental knowledge about:

• Economics, business economics, and transport economics
• Financial accounting
• Cost behavior, cost calculations, and product costing
• Investment analysis
• Key concepts in data analysis and their applications in Logistics Engineering
• Summarizing and interpreting data using descriptive methods
• Spreadsheet modeling and basic statistical analysis
• Data visualization and effective presentation of data analysis findings

Skills

By the end of the course, the student will be able to:

• Calculate profit-maximizing and cost-minimizing production quantities under monopoly and perfect competition
• Conduct investment analyses using the net present value (NPV) method and calculate common depreciation methods
• Perform accounting analyses by calculating various profitability-, liquidity-, and solvency-measures
• Identify trends, patterns, and outliers in data sets, and use Excel for data manipulation, analysis, and visualization
• Create structured spreadsheet models and make data-driven decisions based on quantitative modeling
• Visualize and present analytical findings effectively with various types of charts

General Skills

• Problem-solving - Understanding, formulating, and solving problems systematically
• Critical Thinking - Evaluate, make informed assumptions in analysis, and elaborate on results
• Collaboration and Communication - Work effectively in team settings, presenting data and discussing insights
• Digital Proficiency - Understand the importance of quantitative analysis and digital tools in creating sustainable solutions

Learning Methods and Activities

• Lectures and assignments

Compulsory Assignments

• Exercise

Evaluation

• 6 exercises, with at least 5 required to be passed to sit for the exam
• Compulsory activity from previous semesters can be approved by the course coordinator
• The re-sit exam can be changed to an oral exam

Recommended and Required Previous Knowledge

• None

Course Materials

To be specified by the start of semester

Subject Areas

• Engineering

Examination

• Examination Arrangement: School exam
• Grade: Letter grades
• Ordinary Examination - Autumn 2025:
  • School exam
  • Weighting: 100/100
  • Date and Time: 15:00
  • Duration: 4 hours
  • Exam System: Inspera Assessment
• Re-sit Examination - Summer 2026:
  • School exam
  • Weighting: 100/100
  • Duration: 4 hours
  • Exam System: Inspera Assessment
  • Place and Room: Not specified yet