# MET 1190 Statistics

## MET 1190 Statistics

Course code:
MET 1190
Department:
Economics
Credits:
7.5
Course coordinator:
Christian Brinch
Product category:
Bachelor
Portfolio:
Bachelor - Core Courses
Semester:
2018 Spring
Active status:
Active
Teaching language:
Norwegian
Course type:
One semester
Introduction

This course gives an introduction to basic probability and basic classic statistics. Probability is a tool used in many contexts that student will encounter later in their studies and working lives. Methods from probability are used to analyze risk and uncertainty in finance and economics. In this course, the probability is used for statistics. The course gives a short introduction to basic descriptive statistics. In addition, a thorough introduction is given to classic statistical inference, methods that are used to describe uncertainty in the conclusions from statistical analyses. As part of the classical statistics, an introduction to regression analysis is also included in the course.

Learning outcomes - Knowledge

After completing the learning process described in this course description, students will:

• Know basic terms from probability, like «random variabel», «expectation», «variance», «probability distribution», «statistical independence» and «conditional probability.
• Know basic models for discrete and continuous random variables, like the normal distribution, the binomial distribution and the Poisson distribution.
• Know basic terms from classic statistics, like «estimator», «null hypothesis», «two-sided test», «p-value» and «confidence interval».
• Know basic methods for describing the relationship between two variables, like «scatter plot», «covariance» and «regression analysis».
Learning outcomes - Skills

After completing the learning process described in this course description, students will:

• Be able to apply standard methods, graphical and tabular, for describing a sample or dataset.
• Be able to apply basic rules from probabiity for solving simple problems, in particular related to card games, dice games, draws from small samples etc.
• Be able to perform one-sided and two-sided hypothesis tests for hypothesis about the population mean when the populastion variance is known or unknown, and in addition the case where we study a population share – based on random samples.
• Be able to construct confidence intervals for population means, population shares and population variances based on random samples.
• Be able to perform simple regression analyses to describe the relationship between two variables, including hypothesis tests or confidence intervals.
Learning Outcome - Reflection

At the end of the course, the students will have aquired an understanding of the importance of why and how we reach different techniques and formulas in statistics, in addition to being able to apply the formulas.

Course content
• Probability calculus
• Random variables
• Standard probability models
• Descriptive statistics
• Estimation and hypothesis testing
• Analysis of the relationship between variables
Learning process and requirements to students

To each lecture there will be exercises and reading assignments. The student must gain knowledge from the material presented in the reading assignments and work through the exercises. The exam will require that the student has solved the exercises during the semester. Feedback will be given by sample solutions and presentations.

Software tools
No specified computer-based tools are required.
Qualifications

Higher Education Entrance Qualification.

Required prerequisite knowledge

Basic skills in mathematics and statistics equivalent to admission requirements for the program.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
MET11901
ECTS
Internal and external examiner
Resit:
Examination every semester
100Yes5 Hour(s)
• All printed and handwritten support materials
• BI-approved exam calculator
• Simple calculator
Individual
Exams:
 Exam category: Submission Form of assessment: Written submission Weight: 100 Invigilation: Yes Grouping (size): Individual Support materials: All printed and handwritten support materials BI-approved exam calculator Simple calculator Duration: 5 Hour(s) Comment: Exam code: MET11901 Grading scale: ECTS Resit: Examination every semester
Exam organisation:
Ordinary examination
Total weight:
100
Workload activityDurationType of durationComment student effort
Teaching54Hour(s)
Group work / Assignments96Hour(s)
Self study40Hour(s)
Examination10Hour(s)Exam incl. preparation
Expected student effort:
 Workload activity: Teaching Duration: 54 Hour(s) Comment:
 Workload activity: Group work / Assignments Duration: 96 Hour(s) Comment:
 Workload activity: Self study Duration: 40 Hour(s) Comment:
 Workload activity: Examination Duration: 10 Hour(s) Comment: Exam incl. preparation