Statistics; Theory and Application in Biology, 6 credits

Statistik; teori och tillämpning i biologi, 6 hp

NDAB02

Course starting semester

The course is disused. Offered for the last time Spring semester 2023. Replaced by NBIB53.

Main field of study

Mathematics

Course level

First cycle

Course type

Programme course

Examiner

Bertil Wegmann

Director of studies or equivalent

Lotta Hallberg

Education components

Preliminary scheduled hours: 48 h
Recommended self-study hours: 112 h

Possible deviation from course syllabus/programme syllabus

ECV = Elective / Compulsory / Voluntary

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

Mathematics

Course level

First cycle

Advancement level

G1X

Course 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, 5

Department

Institutionen för datavetenskap

Director of Studies or equivalent

Lotta Hallberg

Examiner

Bertil Wegmann

Education components

Preliminary scheduled hours: 48 h
Recommended 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.

Student rights and obligations (login required)
Linköping University common rules and regulations (in Swedish)

Additional literature

Books

Zar, Biostatistical analysis,

ISBN: 0-13-206502-9

Download

Download course literature list as PDF

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize

		I	U	A	Modules	Comment
1. DISCIPLINARY KNOWLEDGE AND REASONING
	1.1 Knowledge of underlying mathematics and science (G1X level)
	1.2 Fundamental engineering knowledge (G1X level)
	1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
	1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)
	1.5 Insight into current research and development work
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
	2.1 Analytical reasoning and problem solving
	2.2 Experimentation, investigation, and knowledge discovery
	2.3 System thinking
	2.4 Attitudes, thought, and learning
	2.5 Ethics, equity, and other responsibilities
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
	3.1 Teamwork
	3.2 Communications
	3.3 Communication in foreign languages
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
	4.1 External, societal, and environmental context
	4.2 Enterprise and business context
	4.3 Conceiving, system engineering and management
	4.4 Designing
	4.5 Implementing
	4.6 Operating
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
	5.2 Economic conditions for knowledge development
	5.3 Identification of needs, structuring and planning of research or development projects
	5.4 Execution of research or development projects
	5.5 Presentation and evaluation of research or development projects

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