# EXC 2904 Statistics

## EXC 2904 Statistics

This course gives an introduction to statistics. Main themes are descriptive statistics, probability and hypothesis testing. Formulas and formal procedures play an important role, but the emphasis is on developing statistical literacy and critical thinking.

- To understand the relevance of statistical analysis in economics and marketing
- Knowledge of basic concepts and overview of statistics
- Understanding the difference between a population and a sample
- Understanding what a random variable and a statistical model is
- Understanding that statistical methods are based on assumptions that must be checked
- Understanding what estimation and hypothesis testing is about
- To be able to reflect on the role of randomness
- To be acquainted with the statistical and mathematical notations used in statistics

- To be able to discern randomness from real underlying effects
- To be able to use statistical software and interpret computer displays from such software
- To be able to produce statistical graphics
- To be able to compute probabilities and confidence intervals
- To be able to conduct the most basic types of hypothesis testing and estimation

- To understand that statistical methods can be wrongly applied and lead to false conclusions
- To understand that in many situations a statistical analysis will help making better decisions

- Graphical and descriptive statistics
- Random samples and populations
- Discrete and continuous random variables
- Probability
- Statistical models
- Estimation
- Confidence intervals
- Hypothesis testing
- Correlation and regression
- Chi square tests

There are 48 course hours, 38 of which are ordinary lectures where the syllabus is covered. The remaining 10 hours will be dedicated to SAS JMP or Excel demonstrations in class.

For each week there will be given a work programme with literature references and exercises. Training / use of Excel will be integrated into teaching. In the lectures the theory will be exemplified by a set of SAS JMP data samples with exercises. The final exam is loosely based on these SAS JMP examples.

The course uses an appropriate statistical software.

__Work requirements__

There are 8 mandatory multiple choice tests to be answered in It's Learning.

If a test is not approved in the first try, the student can retry. It is mandatory that the student get approved at least 5 of these tests in order to take the final exam.

__Re-sit examination__

Students without the approved 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.

No particular prerequisites.

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

Mandatory | 8 | 5 | The student must pass 5 of the 8 Work Requirements to be able to sit for the exam. |

Assessments |
---|

Exam category: Submission Form of assessment: Written submission Invigilation Weight: 100 Grouping: Individual Support materials: - BI-approved exam calculator
- Simple calculator
- Bilingual dictionary
Duration: 5 Hour(s) Exam code: EXC29041 Grading scale: ECTS Resit: Examination when next scheduled course |

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

Teaching | 48 Hour(s) | |

Submission(s) | 50 Hour(s) | Multiple-choice tests on Itslearning. |

Group work / Assignments | 42 Hour(s) | SAS JMP work |

Student's own work with learning resources | 40 Hour(s) | |

Examination | 20 Hour(s) | Exam incl. preparations. |

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.