course-details-portlet

MET2010 - Applied Statistics

About

Examination arrangement

Examination arrangement: School exam
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
School exam 100/100 4 hours C

Course content

This course gives an introduction to various topics within statistical analysis and how to conduct data analyses using different tools and methods.

Topics covered in the course include:

  • Basic data handling, processing, and visualization
  • Hypothesis testing
  • Chi-square tests
  • Analysis of Variance (ANOVA)
  • F-tests, one-factor, and two-factor models
  • Repetition of simple linear regression and the least squares method
  • Multiple linear regression models
  • Confidence intervals and hypothesis testing for regression coefficients
  • Correlation analysis
  • Non-linear regression: quadratic, inverse, and log-linear models
  • Multicollinearity and autocorrelation
  • Residual analysis
  • Non-parametric statistics

Learning outcome

Knowledge

Upon completion of the course, students should have acquired knowledge of how to conduct and apply data analysis using various statistical techniques. This includes knowledge of:

  • The most commonly used types of statistical tests
  • Simple and multiple regression analysis
  • Hypothesis testing with regression analysis
  • Strengths and weaknesses of various statistical analysis techniques

Skills

Upon completion of the course, students should be able to apply acquired knowledge in conducting data analyses. This includes the ability to:

  • Handle, process, and visualize data
  • Assess the use of tests and methods based on data characteristics
  • Perform various types of statistical tests and methods using data tools
  • Conduct data analysis and interpret results using multiple regression

General competence

The student should have an understanding of all stages involved in high-quality data analysis. They should have a thorough understanding of the general principles for conducting statistical tests and substantial knowledge of the possibilities and limitations in using multiple regression models.

Learning methods and activities

Lectures and exercises.

Compulsory assignments

  • Obligatorisk skriftlig innlevering

Further on evaluation

Mandatory assignment must be passed to gain entry to the exam. This is a group project assignment with up to 3 students per group. Students can hand in individually or in a group of 2 if they wish.

Mandatory assignment will be specified at semester start.

Supporting material allowed on exams:

  • Formula sheet (attached to the exam) and approved calculator regarding NTNUs support material code B-D "specific basic calculator".
  • Other calculators that are allowed in the course are: Casio FC-100V and Texas Instruments - BAII Plus.

Specific conditions

Admission to a programme of study is required:
Business Administration (BØA)
Economics and Business Administration (MSIVØK5)

Required previous knowledge

None.

Course materials

The final syllabus is announced at the beginning of the semester.

Credit reductions

Course code Reduction From To
ME220 6.0 SPRING 2005
ME220 6.0 SPRING 2005
ME210 6.0 SPRING 2005
SØK1005 4.0 AUTUMN 2023
More on the course

Facts

Version: A
Credits:  7.5 SP
Study level: Intermediate course, level II

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2024

Language of instruction: Norwegian

Location: Trondheim

Subject area(s)
  • Statistics
  • Economics and Administration
Contact information
Course coordinator:

Department with academic responsibility
NTNU Business School

Timetable

List view
Calendar view

Examination

Examination arrangement: School exam

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD School exam 100/100 C INSPERA
Room Building Number of candidates
Summer UTS School exam 100/100 C INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU