Statistics; Theory and Application in Biology, 6 credits
Statistik; teori och tillämpning i biologi, 6 hp
NDAB02
Main field of study
MathematicsCourse level
First cycleCourse type
Programme courseExaminer
Bertil WegmannDirector of studies or equivalent
Lotta HallbergEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Course offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
---|---|---|---|---|---|---|---|
6KBIO | Biology | 4 (Spring 2017) | 1, 2 | 1, 3 | Swedish | Linköping, Valla | C |
6KKEB | Chemical Biology | 4 (Spring 2017) | 1, 2 | 1, 3 | Swedish | Linköping, Valla | E |
6MPRO | Protein Science, Master's programme (Internal) | 2 (Spring 2017) | 1, 2 | 1, 3 | Swedish | Linköping, Valla | E |
Main field of study
MathematicsCourse level
First cycleAdvancement level
G1XCourse offered for
- Biology
- Chemical Biology
- Protein Science, Master's programme
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Courses in biology corresponding to at least 60 ECTS.
Intended learning outcomes
The students shall understand and use basic probability theory and statistics. The theory and methods are primarily focused on such that apply in biology. By the end of the course the student should be able to:
- Explain basic statistical concepts, such as population, sample, significance level and confidence interval.
- Choose designs and statistical models for basic types of experiments in which the outcome is influenced by random variation.
- Apply statistical software packages for descriptive analyses of the collected data and inference about populations, treatment effects and relationships between variables.
- Articulate and critically assess the conclusions from a statistical analysis
Course content
The course treats basic methods to describe and analyze data from biological experiments. Descriptive statistics. Regression analysis. One- and two-way ANOVA. Non parametric tests. Experimental design.
Teaching and working methods
Lectures, seminars and computer sessions to apply statistical methods on biological data and experiments.
The course runs over the entire spring semester.
Examination
LAB1 | Computer based laboratory work | 1.5 credits | U, G |
TEN1 | Written Examination | 4.5 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för datavetenskapDirector of Studies or equivalent
Lotta HallbergExaminer
Bertil WegmannEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Course literature
Additional literature
Books
- Zar, Biostatistical analysis,
ISBN: 0-13-206502-9
Code | Name | Scope | Grading scale |
---|---|---|---|
LAB1 | Computer based laboratory work | 1.5 credits | U, G |
TEN1 | Written Examination | 4.5 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Additional literature
Books
ISBN: 0-13-206502-9
Note: The course matrix might contain more information in Swedish.
I | U | A | Modules | Comment | ||
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1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
1.1 Knowledge of underlying mathematics and science (G1X level) |
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1.2 Fundamental engineering knowledge (G1X level) |
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1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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1.5 Insight into current research and development work |
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2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
2.1 Analytical reasoning and problem solving |
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2.2 Experimentation, investigation, and knowledge discovery |
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2.3 System thinking |
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2.4 Attitudes, thought, and learning |
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2.5 Ethics, equity, and other responsibilities |
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3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
3.1 Teamwork |
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3.2 Communications |
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3.3 Communication in foreign languages |
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4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
4.1 External, societal, and environmental context |
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4.2 Enterprise and business context |
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4.3 Conceiving, system engineering and management |
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4.4 Designing |
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4.5 Implementing |
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4.6 Operating |
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5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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5.2 Economic conditions for knowledge development |
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5.3 Identification of needs, structuring and planning of research or development projects |
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5.4 Execution of research or development projects |
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5.5 Presentation and evaluation of research or development projects |
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