2010/2011 BA-PSTA Statistics
English Title | |
Statistics |
Course Information | |
Language | English |
Point | 10 ECTS (300 SAT) |
Type | Mandatory |
Level | Bachelor |
Course Period | |
Time Table | Please see course schedule at e-Campus |
Study Board |
Study Board for BSc in Service Management |
Course Coordinator | |
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Main Category of the Course | |
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Taught under Open University-Taught under open university. | |
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: • Analyze a problem to identify the given information and produce data that can provide answers to properly posed questions. • Use graphical and numerical methods for exploring and summarizing data on a single categorical or quantitative variable. • Describe basic probability and how probability helps us understand randomness in our lives, as well as grasp the crucial concept of a sampling distribution and how it relates to inference methods. • Choose and justify appropriate descriptive and inferential methods for examining and analyzing data and drawing conclusions. • Analysis of the association between variables, categorical, continuous and both, using contingency tables, correlation, regressions, and analysis of variance. • Communication of the conclusions of statistical analysis clearly and effectively, i.e identify connections between basic statistics and the real world. | |||||
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Examination | |||||
Prerequisites for Attending the Exam | |||||
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, class discussions | |||||
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 |