# EBA 2904 Statistics with Programming

## EBA 2904 Statistics with Programming

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.

After compledted course students shall:

- Understand the relevance of statistical analysis in economics and marketing
- Acuire knowledge of basic concepts and overview of statistics
- Understand the difference between a population and a sample
- Understand what a random variable and a statistical model is
- Understand that statistical methods are based on assumptions that must be checked
- Understand what estimation and hypothesis testing is about
- Be acquainted with the statistical and mathematical notations used in statistics

After completed course students will be able to:

- Discern randomness from real underlying effects
- Use statistical software and interpret computer displays from such software
- Produce statistical graphics
- Compute probabilities and confidence intervals
- Conduct the most basic types of hypothesis testing and estimation
- Reflect on the role of randomness

Students will understand that in many situations a statistical analysis will help making better decisions, but also be ware that statistical methods can be wrongly applied and lead to false conclusions.

- Probability. Basic definitions. Limits of relative frequencies.
- Introduction to Monte Carlo simulation.
- Random variables and their distributions. Approximating distributions through Monte Carlo simulations: Histograms as approximations to densities.
- The law of large numbers and the central limit theorem illustrated through Monte Carlo simulations.
- Confidence intervals and hypothesis testing in large samples. A brief summary of the t-test under normality assumptions.
- Correlation and simple linear regression.
- Assessing the performance of statistical procedures using Monte Carlo simulations.

There are 48 course hours, some of which will be used for instructions in the computer software Python.

__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.

.

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. |

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

Exam category:Submission Form of assessment:Written submission Exam code:EBA 29041 Grading scale:ECTS Grading rules:Internal and external examiner Resit:Examination every semester | 100 | Yes | 5 Hour(s) | - Bilingual dictionary
| Individual |

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

Teaching | 48 Hour(s) | |

Submission(s) | 50 Hour(s) | |

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

Student's own work with learning resources | 57 Hour(s) | |

Examination | 3 Hour(s) |

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.