MANSCI1000E Introduction to management science

    • Number of credits
      7,5
    • Teaching semester
      2022 Autumn
    • Language of instruction
      English
    • Campus
      Rena
    • Required prerequisite knowledge

      None. Recommended prerequisites: Basic corporate finance, accounting, calculus/mathematics, and statistics.

Course content

The course introduces quantitative models that can be used to solve decision problems within various businesses. Spreadsheets (Microsoft Excel) will be actively used both in teaching and in mandatory assignments. The course is divided into five modules. These are:

  • Introduction and Basic spreadsheet models
  • Linear- and Non-linear Programming Models
  • Simulation Models
  • Forecasting Models
  • Inventory Models  

The workload is approximately the same for all five.

Learning Outcome

Learning outcomes upon completion of the course:

Knowledge

The student

  • can present cases where various management science techniques are heavily uses both within the Public and private sector
  • can refer to important research results within specific areas covered in the course
  • can translate practical problems into quantitative models that are solvable With spreadsheets
  • can explain and justify the choice of various models based on specific criteria
  • can describe strenghts and weaknesses of using quantitative models for decision support in practice
Skills

The student

  • is able to derive optimal solutions for linear Programming models by graphical solutions, calculations, and using spreadsheets 
  • is able to interpret the results and important concepts from solution reports from such linear programming models 
  • is able to calculate optimal solution for simple non-linear programming models
  • is able to replicate real business situations using Monte Carlo simulation
  • is able to analyze uncertainty in various Projects based on the results from from Monte Carlo simulations 
  • is able to choose appropriate forecasting models for time-series data with various properties
  • is able to make forecasts for time series varables in a spreadsheet using appropriate modelling techniques
  • is able to calculate the accuracy of forecasts using several accuracy measures
  • is able to evaluate the performance of various  forecasting techniques based on the accuracy meaures
  • is able to calculate optimal order quantity, total costs, and reorder point given several different assumptions
General competence

The student:

  • can assess the needs various businesses might have for management science techniques
  • can assist in the Development and use of appropriate management science techniques to improve the general performance of various businesses
  • can communicate about Management Science in English 
Teaching and working methods

Online videos of relevant course topics, self-study of course Readings, problem solving and quizzes, online discussion forums.  

Required coursework

Mandatory assignments:

  • A True/False test consisting of 10 questions after each module
  • A longer multiple test after each module

All mandatory assignments must be passed to be allowed to take the exam.

Form of assessment

A 24 hour individual, digital home exam. The exam will be given in English, but the candidate can choose to do the exam in English or Norwegian. The exam will be given as a combination of quizzes, multiple choice tests, practical implementation of relevant analysis, and/or writing a report. Grades: Pass/fail. 

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Home exam
Passed - not passed
Individual
24 Hour(s)
  • No support materials
Faculty
Inland School of Business and Social Sciences
Department
Department of Business Administration