Course code STAT210

STAT210 Design of Experiments and Analysis of Variance

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Showing course contents for the educational year 2022 - 2023 .

Course responsible: Lars Erik Gangsei
Teachers: Thore Egeland
ECTS credits: 5
Faculty: Faculty of Chemistry, Biotechnology and Food Science
Teaching language: EN
(NO=norsk, EN=Engelsk)
Limits of class size:
1000
Teaching exam periods:
This course starts in the August block. This course has teaching/evaluation in August block.
Course frequency: Annually
First time: Study year 2011-2012
Course contents:
Advanced course in statistical method. Applicable for students at both bachelor and master's level, and all study programs. Throughout the course, students will gain knowledge of general principles in planning and analyzing trials, including repetition, randomization and block sharing. Keywords: 'Randomized designs', 'Variance analysis', Block designs ',' Contrasts ',' Factorial designs ', ‘Interaction', ‘Nested designs’, 'Fixed and random effects', 'Variance components'. The teaching is based on three main elements; 1) Two hours daily lectures, 2) Exercises, individually or in groups with teacher assistants present and 3) Submission of a compulsory assignment. STAT210 is a course that emphasizes traditional and well-proven statistical models and methods. These methods have constituted and still constitute a central basis for analyzes and models applied in most disciplines taught and researched at NMBU, including sustainability and climate analysis.
Learning outcome:

KNOWLEDGE: The students will learn to use fundamental statistical principles when they design experiments, to compare different groups or treatments, and to analyse data from such experiments by means of analysis of variance.

SKILLS: The students should be able to perform statistical analyzes with the methods mentioned in Knowledge. They should be able to interpret the results of the analyzes and convey what has been done, the results and the weaknesses and limitations of the analyzes and models. They should understand the importance of having good data (e.g. representativeness, independence) in order to draw useful and correct conclusions from a survey.

COMPETENCE: The students should be able to apply what they have learned to problems in their studies and later in their professional life and perform analyzes on their own data. At the same time, they should be able to ask critical questions about statistical results that they generate or are presented to them and assess the quality of these results.

Learning activities:
Lectures and exercises with access to teaching assistants.
Teaching support:
Teacher is available via contact on Canvas. Teaching assistants are available every day 4 hours .
Syllabus:

Curriculum is announced in the first lecture. Links to teaching material online will be announced on Canvas prior to course start.

The textbook for the course is: 

Montgomery, D.C. 2019. Design and Analysis of Experiments, 9th Edition, EMEA Edition. John Wiley & Sons UK.

Prerequisites:

Students are required to:

Be able to perform descriptive statistics and draw conclusions from this.Know basic concepts and principles in probability theory with emphasis on stochastic variables and their properties.Be familiar with some common probability distributions, including the normal distribution, binomial distribution, Student’s t-distribution, F-distribution and the chi-square distribution.Understand basic estimation theory, including what is meant by confidence intervals, point estimates, expectation accuracy and standard error for an estimator.Reformulate simple situation descriptions and problem(s) to a relevant statistical model, and interpret the parameters in this. This applies to situations that can be covered by simple linear regression models, one-way analysis of variance or bivariate analyzes.Test relevant cases using formal hypotheses, including setting up relevant hypotheses, testing these and interpreting the result.Basic skills in R/RStudio.

 

The requirements listed above are covered by STAT100 or a similar course.

Recommended prerequisites:
Mandatory activity:
One compulsory assignment which is approved during the teaching period. 
Assessment:

Written examination (3.5 hours), counts 100 %.

The exam is in given English only. The students may answer using Norwegian, Danish, Swedish or English.

The exam or parts of the exam might be given as multiple choice questions.

Nominal workload:

Lectures: 28 hours.

Exercises: 26 hours.

Individual study: 71 hours.

Entrance requirements:
Special requirements in Science.
Type of course:
2 hour lectures and 2 hours exercises daily during the August block (three weeks).
Examiner:
An external examiner approves the exam in advance. If the exam is a regular written exam the external examiner evaluates a selection of 25 of the exams.
Allowed examination aids: C2 All types of calculators, all other written aids
Examination details: Written exam: Letter grades