# MET 3431 Statistics

## MET 3431 Statistics

Course code:
MET 3431
Department:
Economics
Credits:
7.5
Course coordinator:
Njål Foldnes
Product category:
Bachelor
Portfolio:
Bachelor - Core Courses
Semester:
2018 Spring
Active status:
Active
Teaching language:
Norwegian
Course type:
One semester
Introduction

This course is an introduction to statistical thinking. Firstly, the student will learn to produce and to interpret descriptive statistics. Secondly,  the student will learn the logic of statistical inference and how to construct confidence intervals and perform hypothesis tests. The emphasis is on understanding concepts and interpretation of results, more than on mathematical machinery.

Learning outcomes - Knowledge

The student will learn the most central concepts underlying statistical methodology, from the collection of data to inference about the population. The underlying logic behind the diversity of methods will be perceived. Concepts such as random sampling, population, parameters and statistics, inference, margin of error and levels of significance and confidence should be understood. Through real-world data example students will understand the usefulness of statistics in business and marketing. However, the student should understand the limitations on conclusions drawn from data.

Learning outcomes - Skills

kills in descriptive statistics are to determine level of measurement, and to choose and calculate measures of center and spread, and to produce graphs, for a given sample. Covariation among variables should also be described. The student should be able to understand and interpret descriptive statistics. Students should be able to perform simple probability calculations. The student should be able to construct and understand confidence intervals and perform statistical tests. The student should become familiar with statistical software, and be able to interpret output from such software. The student should be able to report the results of statistical analysis in an easy-to-understand language.

Learning Outcome - Reflection

The student should be aware that statistical methods may be easily misused and misinterpreted. It is important that the judgment required for statistical analysis is fair and just.

Course content
• Collection of data
• Describing the sample at hand
• Probability
• Confidence intervals for mean and proportion
• Hypothesis tests  for mean and proportion
• Correlation and regression
• Chi-square test
Learning process and requirements to students

The course consists of 48 hours of lectures, including 4 hours of demonstration of statistical software. The problems studied in class and given as homework assignments will serve as a basis for the final examination.

For each week there will be given a work program with literature references and assignments. In lectures and SAS JMP exercises, theory will be illustrated by using multiple data sets and associated tasks. The final exam will be based on that the student has solved all these tasks throughout the semester.

E-learning
When course is delivered online, lecturer, in cooperation with the Academic Servises Network, will organize an appropriate combination of digital teaching and lectures. Online students are also offered a study guide to contribute to progression and overview. Total recommended time spent for completing the course also applies here.

Software tools
SAS - JMP

Re-sit examination
Students that have not gotten approved the coursework requirements, must re-take the exercises during the next scheduled course.

Students that have not passed the written examination or who wish to improve their grade may re-take the examination in connection with the next scheduled examination.

Qualifications

Higher Education Entrance Qualification.

Required prerequisite knowledge

No specific prerequisites required.

Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory85In the course of the semester 8 mandatory multiple-choice assignments will be given. These are submitted on Itslearning. Each assignment is assessed as either pass or fail. The student needs at least 5 passes in order to take the final exam.
Mandatory coursework:
 Mandatory coursework: Mandatory Courseworks given: 8 Courseworks required: 5 Comment coursework: In the course of the semester 8 mandatory multiple-choice assignments will be given. These are submitted on Itslearning. Each assignment is assessed as either pass or fail. The student needs at least 5 passes in order to take the final exam.
Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
MET34311
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: MET34311 Grading scale: ECTS Resit: Examination every semester
Exam organisation:
Ordinary examination
Total weight:
100
Workload activityDurationType of durationComment student effort
Teaching48Hour(s)
Group work / Assignments50Hour(s)
Prepare for teaching42Hour(s)Working with SAS JMP (or some statistical software)
Self study40Hour(s)
Examination20Hour(s)Exam incl. preparations.
Expected student effort:
 Workload activity: Teaching Duration: 48 Hour(s) Comment:
 Workload activity: Group work / Assignments Duration: 50 Hour(s) Comment:
 Workload activity: Prepare for teaching Duration: 42 Hour(s) Comment: Working with SAS JMP (or some statistical software)
 Workload activity: Self study Duration: 40 Hour(s) Comment:
 Workload activity: Examination Duration: 20 Hour(s) Comment: Exam incl. preparations.
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.

Talis literature

#### Obligatorisk/Compulsory

##### Book
Authors/Editors År Tittel Edition Publisher StudentNote
Foldnes, Njål; Grønneberg, Steffen; Hermansen, Gudmund 2018 Statistikk og dataanalyse: en moderne innføring   Cappelen Damm Akademisk

#### Anbefalt/Recommended

##### Book
Authors/Editors År Tittel Edition Publisher StudentNote
Ubøe, Jan 2015 Statistikk for økonomifag 5. utg Gyldendal akademisk