# STAT101 Project based introduction to statistics

### Search for other courses here

#### Showing course contents for the educational year 2021 - 2022 .

Course responsible: Kathrine Frey Frøslie
Teachers: Hilde Vinje
ECTS credits: 10
Faculty: Faculty of Chemistry, Biotechnology and Food Science
Teaching language: NO
(NO=norsk, EN=Engelsk)
Limits of class size:
24
Teaching exam periods:
The course takes place in the spring, parallel to STAT100.
Course frequency: Spring semester,  if resources and sufficient interest
First time: Study year 2018-2019
Course contents:

Numerical literacy and a basic understanding of quantitative research methods are cornerstones of scientific knowledge and communication within the fields of science and medicine. Therefore, in almost all educations in these fields, there is a mandatory course in introductory statistics, often at the bachelor level.

Topics that are addressed in this course: Descriptive statistics. Basic probability, conditional probability, discrete and continuous variables, expectation and variance. Covariance, correlation, and independence. Estimation, confidence intervals, and hypothesis testing. Z-tests and T-tests. Simple linear regression. One-way analysis of variance. Chi square tests. Application of simple statistical software (R).

Learning outcome:

KNOWLEDGE:  The students will learn the basic concepts in probability theory and statistics. They will get familiar with the assumptions and the applications of the most commonly used statistical methods applied in science and everyday life.

SKILLS: The students should be able to carry out simple statistical analyzes. They should be able to interpret the results of the analyzes and pass on what has been done, the results and the weaknesses and limitations of the analyzes. They should understand the importance of having good data (e.g. representativeness, independence) in order to draw useful and correct conclusions from a survey.

GENERAL COMPETENCE: The students should be able to apply what they have learned to simple problems in their studies and later in the professional life and perform simple analyzes on their own data. They should also be able to ask critical questions about the statistical results presented to them (e.g. in the media or in reasearch) and assess the sustainability of these.

Learning activities:

The course will be project-based. The first 3 weeks, as an introduction, the course will follow STAT100 lectures, as well as assignments.

The rest of the course will be based on up to three project assignments that will be presented and evaluated. Lecture videos that go through key concepts of the curriculum and some basic methods for statistical analysis, as well as exercises corresponding to STAT100 will be available throughout the course. The students will, in small groups, be assigned major projects where they themselves are responsible for learning the necessary methods to solve these tasks. This is a way to introduce the students to the culture and idiosyncrasies of statistical reasoning, i.e. scientific thinking, early in their studies. Such knowledge is central in the perspective of lifelong learning, and is in accordance with UNESCO’s recent recommendations to high quality education on sustainable development at all levels and in all social contexts.

There will be up to four compulsory meetings between the students where they present the projects for each other and the course responsible. At these gatherings they will comment and discuss the results and the progress they have had as well as guidance for further work.

Teaching support:
The course responsible is available (by direct contact, by phone, or by e-mail). There are group exercises twice a week where the course coordinator is present for discussion and supervision. Web pages will always be updated. In addition the course responsible will be available during the compulsory sessions to control, guide and join the discussion that arise. STAT101 students can also use STAT100 exercises and exercise classes with questions they may have.
Syllabus:
Will be announced on the course website before the semester.
Prerequisites:
MATH100 or MATH111 (may be taken in the same semester).
Recommended prerequisites:
Mandatory activity:
It will throughout the semester be up to four mandatory meetings where the projects they are working on are presented, discussed and further worked on.  Ecxept for these, the students themselves are responsible for their own progress on their projects.
Assessment:

Up to three major projects will be completed during the semester. These will, together with an oral consultation based on the projects, count 50% of the final grade.

A multiple choice exam will count the remaining 50% of the final grade.

An individual hearing at the end with questions about the project will count the remaining 50% of the grade.

300 hours
Entrance requirements:

MATRS - General admission requirements or prior experiential learning, and R1 or (S1+S2) or similar mathematical skills

An application letter must be written for those who wish to join where they write something about motivation and background to want to follow this course.

Reduction of credits:

STAT100 - full reduction

DAT110 (MATH-INF110) - 5 credits reduction.

Type of course:

Most of the course will be self-study and the student will be responsible for finishing their projects.

There will be no teaching in addition to the group exercises and the compulsory sessions mentioned in Learning activities, but students will be able to access lecture videos and exercises that are strongly recommended to work with to complete their projects. They can also participate on STAT100 groups.

Note:

The course overlap completely with STAT100 in syllabus and credits.

This is a new course, created for those who like to work and acquire knowledge through the ability to run a project.The assignments can be real, simplifies research projects, entrepreneurs who want a simple data analysis or a simulated dataset designed to reflect a real scenario.

The final result should reflect the course contents and learning outcome corresponding to STAT100.

Examiner:
An external sensor is used in the course for review of project assignments and the hearings.
Examination details: Combined assessment: Letter grades