About this course

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. Binomial distribution and normal distribution. Covariance, correlation, and independence. Estimation, confidence intervals, and hypothesis testing. Z-tests, T-tests and non-parametric test. 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

    Since 2016, "flipped classroom" teaching has been practiced in STAT100 as a total or partly replacement for lectures. Students are then expected to watch educational videos at home, and work actively with discussion exercises in groups while at campus, under supervision of teachers.

    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.

  • Teaching support

    A Canvas-page will always be updated.Any questions about the course must be sent to the course e-mail address: stat.100@nmbu.no. The course responsible is available by phone, or by Teams.

    In the colloquium sessions one responisble teacher, as well as up to four colloquium teachers, present. Assistant teachers are available during group sessions.

  • Syllabus

    Will be announced on Canvas before the semester.

  • Prerequisites

    MATH100 (or ECN102) or MATH111 (may be taken in the same semester).

    The following knowledge is essential:

    Algebraic notation, knowledge and experience with the notation of sums, fundamental calculations, the logarithmic function, solving equations and inequalities, writing numbers in standard form, general mathematical reasoning.

  • Assessment method

    A final 3.5 hours written exam, A-F, potentially containing multiple choice tests. The final exam counts 100 %.

    Written exam

    Karakterregel: Letter grades

    Hjelpemiddel: C1 All types of calculators, other aids as specified

  • About use of AI

    For the mandatory submissions in the course, K2 applies, 'a certain degree of AI use.' The permissible use of AI will be further specified at the start of the course.

    Descriptions of AI-category codes.

  • Examiner scheme

    An internal examiner evaluates all exam question and the grade scale. The external sensor will also grade a minimum of 25 examination papers as calibration of the evaluation, if other excercises than multiple choice are given at the final exam.

    An external examiner must approve the evaluation arrangements for the course.

  • Mandatory activity

    There will be weekly online assignments of which a specified number must be approved throughout the course. In order to get each assignment approved 50 % of the exercises must be correctly answered. Any adjustments of these requirements will be announced on the course pages on Canvas.

    Students must also submit weekly, written assignments, either with a group, or on their own.

    Students who has fulfilled the compulsory activity in the course earlier, need not attend the compulsory activities listed above.

  • Notes

    The course is offered twice a year, both in the spring and autumn parallel.

  • Teaching hours

    The course will entirely or partly follow a so-called "flipped classroom" style for 2 or 4 hours a week. Flipped classroom means that the students watch lecture-videos (2-4 hours homework per week) as preparation for colloquium groups. During the colloquium group work the course responsible and teacher-assistants will circulate the groups and discuss problems and exercises. In addition to colloquium groups, regular lectures may be given. Information about the amount of lectures and group teaching will be given in the beginning of the course.

    Attendance at exercise groups is voluntary, but the work load is normed to 4 hours a week.

  • Reduction of credits

    DAT110 (MATH-INF110) - 5 credits reduction

  • Admission requirements

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