Basic Statistics, 2nd Course, 15 Credits

Contents

The course consists of four modules.

Module 1. Probability and statistical inference (5 credits)
 
The module begins with an introduction to the role of statistics when acquiring knowledge empirically. This is followed by the basics of probability theory, such as independent events, conditional probability, and some well-known probability distributions. The second part of the module is devoted to basic statistical inference theory to increase the understanding of important methods and concepts that were touched on in the course Statistik A1, 15 credits. An important part is a more in-depth look at the theory behind confidence interval and hypothesis testing, and the importance of the normal distribution for inference of this kind.

Module 2. Applied statistical inference (6 credits)

In this module, statistical inference is applied to the areas of statistical process control and time series analysis. A major part of the module is devoted to generalising the methods described in module 1. Examples include methods of comparing more than two populations and inference without assuming a normal distribution nor requiring a large random sample. The module also includes methods for studying associations between variables where the dependent variable can assume only two possible outcomes.

Module 3. Problem solving with statistical software (1,5 credits)

This module runs somewhat parallel to module 1 and 2 and is based on mandatory written assignments. The module concerns methods that are explained in modules 1 and 2, but require the use of statistical software to be solved. Different statistical software may be used.

Module 4. Written assignment on statistical methods (2,5 credits)

The module consists of conducting a planned study in order to practically apply the knowledge acquired in the earlier modules. Desc¬riptions of official statistics and basic information retrieval are also included during this module. In brief, the task is to

• formulate a purpose and research questions for the planned study
• use information retrieval to find results of previous studies
• collecting data, for example from official statistics
• analyse the collected data
• write a report about the results
• present the results orally during at least one mandatory seminar
• critically review another group's report.

Expected learning outcomes

After passing this course the student should be able to:

• exemplify the role of statistics when acquiring knowledge empirically
• identify probability distributions and calculate the probability of the situations that are used in the course
• explain the theory behind confidence interval and hypothesis testing, assuming  normal distribution, and explain the role of the normal distribution in this context
• apply the methods, explained in the course, which assumes neither a normal distribution nor large random samples
• apply the methods covered in the course where more than two populations are compared
• apply the methods covered in the course in the field of statistical process control and time series analysis
• in writing and orally, present the results of  the  statistical study
• critically review on a statistical report
• use the software included in the course to process, analyse and present data.

Required Knowledge

Univ: Statistics A1 (15 credits) or Statistics for Business and Economics (15 credits) or equivalent.

Form of instruction

The course consists of lectures, practicals, computer practicals, seminars, and tutoring. Mandatory written assignments/seminars are included in modules 3 and 4.

Examination modes

The student's progress on the course is assessed through examination based on the expected learning outcomes.
Examin¬ation is done through written exams in modules 1 and 2. (The written test can be replaced with an oral examination if less than five students have applied for an exam.) Written (or oral) exams are graded Pass with distinction (VG), Pass (G) or Failed (U).

Module 4 are examined through a written report, which is also presented orally during at least one mandatory seminar. Opposition of another group's work is also part of the examination in this module. Module 3 is examined through mandatory written assignments. Report, oral presentations, oppositions, written assignments and seminar attendance are only graded Pass (G) or Failed (U). Deadlines will be set for mandatory written assignments, oppositions and oral presentations. Any supplementation of assignments should be completed within two weeks of the end of the module.

Grades on the course are awarded when students have passed all examinations and mandatory course tasks. The grade is a comprehensive evaluation of the results of the various parts of the examinations and is not granted until all mandatory tasks have been passed.

A student who has passed an examination is not allowed to take another examination in order to get a higher grade. For students who do not pass, an additional test will be held according to a set schedule.

After two failed examinations in one module, the student has the right to request another grading teacher unless special reasons exist. Written requests should be handed to the Director of Studies no later than two weeks before the date of the next examination.

Examinations based on the same course syllabus as the ordinary examination are guaranteed to be offered up to two years after the date of the student's first registration for the course.

Academic credit transfer

Academic credit transfers are according to the University credit transfer regulations.