Main Field of Study and progress level:
Statistics: First cycle, has only upper-secondary level entry requirements
Grading scale: Pass with distinction, Pass, Fail
Responsible department: Department of Statistics
Contents
Module 1: Probability and statistical inference, 7.5 ECTS-credits
Statistical inference can be described as the art of making decisions under uncertainty. It relies on probability theory. Therefore, this module begins with a review of necessary probabilistic concepts such as randomness, random trials, and random variables. Probability distributions are introduced, notably the binomial distribution and the normal distribution.
In the statistical inference part, focus is on estimation and testing, especially of population means and proportions. Methods for comparing two populations with respect to these characteristics are given.
Module 2: Regression analysis, 7.5 ECTS-credits
Regression analysis is a tool for describing and analysing the relationship between a response variable and one or more explanatory variables. The interpretation of regression as a probability model is emphasized. Focus is on simple and multiple linear regression. Suitable transformations of some nonlinear models into linear ones are also discussed. Logistic regression is introduced as a regression model for data with a binary response. Time series models are introduced and used for data collected sequentially in time. The techniques for estimation and hypothesis testing introduced in Module 1 are used in the analysis of these regression models.
The chi-square test is introduced as a tool to test independence between two variables measured on nominal or ordinal scale.
Methodological aspects are important, for example the relationship between the chosen regression model and the theory in which the application lies. One of the important aspects to examine is how the model assumptions affect the statistical analysis. Some techniques to check these assumptions are introduced.
Practical applications are discussed and analysed throughout this module. This is to a large extent done in computer labs.
Expected learning outcomes
After completing the course the student should be able to
- use, understand and explain fundamental concepts related to statistic terminology and methodology,
- use models and data to describe and analyse events in the real world that have random variation,
- use and understand regression analysis,
- be familiar with and understand the different steps in a statistical survey,
- utilize the computer as a tool in applied statistical situations.
Required Knowledge
Basic entrance requirements for higher studies (a successfully completed upper secondary education (post-16)). Specific requirements: English course B at Swedish gymnasium. Mathematics course C at Swedish gymnasium or equivalent. Social science course A at Swedish gymnasium or equivalent.
Form of instruction
The process of learning is based on lectures, tutorials and the students' own work. During the course the students should work independent with practice material. The students are given both written and oral practice in presenting statistical concepts and analyses. During the course the students have access to computers. Teacher guided introductions of software and tutorials are given. Successively the students will receive skills and work independent with the computer as a tool in applied situations.
Examination modes
The grading system consists of the three grades; Fail, Pass and Pass with distinction. All students may receive ECTS grades upon request. Examination will be based on the written examinations and the assignments. To receive the grade Pass on a module the student must present satisfying presentations of the given assignments as well as pass the written examination. For the given assignment special due dates will be given when it should be handed in and the oral presentation should be given.
To receive the grade Pass on the course the students need to pass both modules. To receive the grade Pass with distinction on the course, the student must have received the grade Pass with distinction on both modules, or achieved at least 75% of the points on the written examinations. Grades on the course are awarded when students have passed all examinations and compulsory course elements.
Students who do not pass the ordinary written examination will be offered an opportunity to
do a new written examination at the latest three months after the ordinary written examination. Beyond that, additional examination opportunities normally arise every academic year when the course is given again. In addition there might be opportunity during the week prior to the start of the autumn semester. For more information contact the director of study at the Department of Statistics. An examination is guaranteed to be based on the same syllabus as the ordinary examination during at least two years from the date the student first registered on the course. If a student has failed an examination on two occasions, he or she has a right to have another grading teacher unless special reasons exist. A written request should be handed to the director of studies at the Department of Statistics no later than two weeks before the next examination opportunity. A student who has passed an examination is not allowed to take another examination in order to get a higher grade. All teaching and examination will be in English.
Academic credit transfer
It can be tested whether a (part or a whole) previous course can be credited for. More information about these rules can be found at www.umu.se/studentcentrum/regler_riktlinjer/index.html (Note that the information is only available in Swedish).
Pallant Julie SPSS survival manual : a step by step guide to data analysis using SPSS for Windows senaste upplagan : Maidenhead : Open University Press : ISBN: 0-335-22366-4 (spiralh.) Search the University Library catalogue
