LOG708 Applied Statistics (Autumn 2019)
- ECTS Credits:
- 7.5
- Responsible faculty:
- Avdeling for logistikk
- Campus:
- Molde
- Course Leader:
- Halvard Arntzen
- Teaching language:
- English
- Study level:
- {code=HN, name=Second degree level}
- Duration:
- ½ year
Table of contents
Contents
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.
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 in Logistics
- Experience-based Master in Logistics
- Master in Economics and Business Administration
- Master in Sustainable Energy Logistics
- Exchange programme - Master's level
Recommended knowledge
A standard bachelor's level course in statistics is a highly recommended prerequisite.
Reduction of Credits
This course’s contents overlap with the following courses. A reduction of credits will occur if one of these courses is taken in addition:
| Course | Reduction of Credits |
|---|---|
| MAT785 – Applied Statistics for Professional Practice. | 7.5 |
The student's learning outcomes after passing the exam
After finishing the course, the students should have knowledge and skills enabling them to do simple practical empirical work, using software tools, e.g. SPSS. Specifically, the students should be able to
- 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
- compute confidence intervals for central population parameters such as means, variances and proportions
- perform tests of statistical hypotheses regarding central population parameters
- perform simple and multiple regression analysis with statistical software
- give practical interpretations and present the results of statistical analyses in nontechnical terms
Forms of teaching and learning
Two hours of lectures per week, two hours of exercises per week
Coursework requirements - conditions for taking the exam
- Mandatory coursework: Assignment(s)
- Courseworks given: 3
- Courseworks required: 3
- Presence: Not required
- Comment:
Exam
- Form of assessment: Written school assessment
- Proportion: 100%
- Duration: 4 Hours
- Grouping: Individual
- Grading scale: Letter (A - F)
- Support material: All printed and written supporting material + calculator that may contain data
Pensum
Last updated from FS (Felles studentsystem)
Oct. 14, 2026 4:31:57 AM