Facts about the course
- ECTS Credits:
- 7.5
- Responsible department:
- Faculty of Logistics
- Course Leader:
- Halvard Arntzen
- Lecture Semester:
- Autumn
- Teaching language:
- English
- Duration:
- ½ year
LOG708 Applied Statistics (Autumn 2022)
About the course
Descriptive Statistics. Random variables and probability distributions. Samples and populations, estimation and inference. Confidence intervals. Testing of statistical hypotheses. Significance levels and P - values.
Methods: T – tests, Z – test for proportions, basic regression analysis, dummy variables in regression, nonlinear regression models, simple forecasting. Other statistical methods may also be discussed.
Gaining familiarity with a statistical package (e.g. Stata, SPSS or R) will be a central part of the course.
The course is connected to the following study programs
- Master of Science in Logistics
- Experience-based Master in Logistics
- Master of Science in Economics and Business Administration
- Master of Science in Sustainable Energy Logistics
- Exchange programme - Master's level
- Master of Science in Sustainable Transport and Urban Mobility
Recommended requirements
A standard bachelor's level course in statistics is a highly recommended prerequisite. An intensive introduction (or fresh-up) course will be offered at the start of the semester.
The student's learning outcomes after completing the course
After finishing the course, the students should achieve the following learning outcomes
- Skills:
- use basic probability distributions for simple modeling and to find probabilities and moments
- use statistical software to effectively organize and present information extracted from data
- perform simple and multiple regression analysis with statistical software
- Knowledge
- about the theory of random variables, probability distributions and their use in statistical analysis
- about the theory of statistical hypothesis testing
- about basic regression analysis
- General competence
- give practical interpretations and present the results of statistical analyses in nontechnical terms
- understand the role of statistics as a tool for gaining scientific knowledge, and as a tool for planning and decision support
Forms of teaching and learning
Two hours of lectures per week, two hours of exercises per week.(Optional)
Coursework requirements - conditions for taking the exam
-
Mandatory coursework: Assignment(s)
-
Courseworks given: 3
-
Courseworks required: 3
-
Comment:
Examination
-
Form of assessment: School assessment
-
Proportion: 100%
-
Duration: 4 hours
-
Grouping: Individual
-
Grading scale: Letter (A - F)
-
Supported material: All printed and written supporting material + calculator that may contain data
Syllabus
Pensumoversikt