2011/2012 BA-PSTA Statistics and Research Methods
English Title | |
Statistics and Research Methods |
Course Information | |
Language | English |
Point | 10 ECTS (300 SAT) |
Type | Mandatory |
Level | Bachelor |
Duration | One Semester |
Course Period | Autumn |
Time Table | Please see course schedule at e-Campus |
Study Board |
Study Board for BSc/MSc i International Business and Politics |
Course Coordinator | |
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Main Category of the Course | |
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Last updated on 29 maj 2012 |
Learning Objectives | |||||||||||||||
The major goal of the statistics course is to produce statistically educated students which mean that students should develop statistical literacy and the ability to think and reason statistically. The student should be able to:
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Examination | |||||||||||||||
Written group synopsis (10-15 pages) followed by an individual oral exam (20 minutes per student), graded by teacher and internal censor on the 7-point scale. The group consists of 3-5 students. The grade is based entirely on the oral exam. Make-up/re-exam when ill at the oral exam and when the ordinary exam is failed, is an individual oral exam (20 minutes per student) based upon the same synopsis. The re-exam is in February. Make-up exam when ill during the writing of the synopsis is a 20 minutes oral exam with 20 minutes open book preparation in the entire curriculum. | |||||||||||||||
Course Content | |||||||||||||||
Statistics is very important for upon it depend the practical application of every other science; it only gives the results of our experience. The course stress conceptual understanding rather than mere knowledge of statistically procedures. The emphasize is on interpretation and understanding of simple statistical methods as applied in social science, business economy as well as political economy. The major parts of the curriculum are: · Descriptive statistics, both numerical and graphical. · The basic laws of probability, and the most important probability distributions. · Statistical inference; confidence intervals and significance tests about hypotheses. · Analysis of categorical variables using contingency tables. · Regression analysis; simple, multiple and logistic. · One-way and two-way analysis of variance. · Non-parametric statistics. | |||||||||||||||
Teaching Methods | |||||||||||||||
Lectures w/ discussions, computer labs, groupwork for synopsis | |||||||||||||||
Literature | |||||||||||||||
Book: Agresti A., C. Franklin (2008): “Statistics: The Art and Science of Learning from Data”, Prentice Hall. Agresti A. (1996): “An Introduction to Categorical Data Analysis”, Wiley. Chapter 2: p. 16-32, Chapter 3: p. 53-60, Chapter 4: p. 71-77, Chapter 5: p. 103-114 and p. 118-119. Software Package: JMP |