# MET 3590 Method and Statistical Data analysis

## MET 3590 Method and Statistical Data analysis

The course provides an introduction to the research methods of social sciences and multivariate data-analysis from a business-economics perspective.

After the course, the students will have obtained knowledge about:

- Important methodological concepts
- Knowledge of the main approaches (both qualitative and quantitative) to the collection, processing and analysis of data
- Basic multivariate analysis
- How multivariate analysis can be used to solve problems in business-economics (research, quality control, forecasting, logistic analysis and control, etc.)
- Limitations in cases where the underlying statistical assumptions are violated
- The plurality of interpretation, and the uncertainty associated with multivariate data-analysis
- Programming

After the course the students will be able to:

- Understand and assess analysis and research in relation to scientific principles
- Evaluate which approaches that best suits a specific research question
- Collect, process and analyse data on the basis of scientific research methods
- Conduct multivariate data-analysis with statistical software
- Conduct and interpret the results of multiple hypothesis testing, also in the cases where the classical assumptions are not fulfilled
- Undertake model diagnostics and model selection
- Write simple programs

The students should acquire a conscious and critical attitude towards data, towards the results of multivariate analysis, and towards the assessment and interpretation of others' results

- Research methods and philosophy of science
- Research questions, hypotheses and types of data
- Variation in research design, plurality of interpretation and the uncertainty of inference
- Simple and multiple regression
- Variation in functional form
- Regression with qualitative right-hand side variables via dummies
- Analysis of categorical variables
- Heteroscedasticity
- Dynamic analysis
- Model selection

The course consists of 42 lecture hours, where the lectures are combined with exercises and the use of statistic software.

__E-learning__

In course delivery as online courses, lecturer will, in collaboration with the student administration, organize an appropriate course implementation, combining different learning activities and digital elements on the learning platform. Online students are also offered a study guide that will contribute to progression and overview. Total recommended time spent for completing the course also applies here.

STATA in the lectures, but the students are in principle free to use (for example) R, Gretl or similar.

__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.

Higher Education Entrance Qualification

**Covid-19**

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

**Teaching**

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

MET 2920 Statistics for economists, MET 3431 Statistics, or the equivalent.

Mandatory coursework | Courseworks given | Courseworks required | Comment coursework |
---|---|---|---|

Mandatory | 2 | 2 | As a means towards learning, two obligatory exercises must be solved and handed in during the term within deadlines that are announced before the start. Both obligatory and must be approved in order to be allowed to do the final exam. Each of the two exercises are made up of two parts, one case-based part that requires the use of statistical software, and one part that is not case-based. The publication, solution and handing in of the exercises is done via the learning management system (currently It's Learning). Feedback is given either via the learning management system and/or lectures. |

Exam category | Weight | Invigilation | Duration | Support materials | Grouping | Comment exam |
---|---|---|---|---|---|---|

Exam category:Submission Form of assessment:Structured test Exam code:MET35901 Grading scale:ECTS Grading rules:Internal examiner Resit:Examination every semester | 100 | Yes | 3 Hour(s) | - All printed and handwritten support materials
- BI-approved exam calculator
- Simple calculator
| Individual | A three-hour individual multiple-choice exam concludes the course. The questions on the exam will partially be based on a case that is published two weeks before the exam. The results from the case must be brought to the examination, since the results are needed in order to answer the questions related to the case. However, the results from the case should not be submitted. In addition to questions from case the case, the exam will also include questions from the entire syllabus. |

Activity | Duration | Comment |
---|---|---|

Teaching | 36 Hour(s) | |

Feedback activities and counselling | 6 Hour(s) | Instructions on the use of econometric software |

Group work / Assignments | 70 Hour(s) | |

Student's own work with learning resources | 60 Hour(s) | |

Submission(s) | 15 Hour(s) | Obligatory exercises |

Examination | 13 Hour(s) | Exam case and exam |

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.