Course - Applied Statistics - MET2010
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)
Recommended previous knowledge
Introductory courses in mathematics and statistics, MET1001 and MET1002 or equivalent.
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 |
Version: A
Credits:
7.5 SP
Study level: Intermediate course, level II
Term no.: 1
Teaching semester: AUTUMN 2024
Language of instruction: Norwegian
Location: Trondheim
- Statistics
- Economics and Administration
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD School exam 100/100 C 2024-11-26 15:00 INSPERA
-
Room Building Number of candidates SL111 grønn sone Sluppenvegen 14 50 SL111 brun sone Sluppenvegen 14 41 SL520 Sluppenvegen 14 6 SL238 Sluppenvegen 14 4 - 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.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"