MS-E1623 - How to lie with statistics?, Lecture, 24.10.2022-1.12.2022

Guest access
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

The objectives are to learn to evaluate statistical analyses critically, to learn to avoid typical pitfalls in simple statistical analyses and to learn to improve presentation of the results obtained in statistical analyses. The objective is not to learn to lie with statistics, but to learn to spot if there is something fishy in a statistical analysis. The ultimate goal is to learn to tell the truth with statistics.

Credits: 5

Schedule: 24.10.2022 - 01.12.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Pauliina Ilmonen

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    During this course, students talk about typical problems and faults in sample selection, choices of location measure, graphical presentation of data, forming questionnaires, statistical testing, and regression analysis. Students are assumed to be familiar with these methods before attending the course. The focus will be on examples about using these methods wrongly --- either accidentally or on purpose --- and on improving statistical analyses.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    The evaluation is based on attendance, lecture assignments, compulsory study journal and project work presentations.

Workload

  • valid for whole curriculum period:

    The course consists of 12 lectures, lecture assignments, project work and study journal. Majority of the lectures, instead of traditional lecturing, consists of discussions. Students find problematic data examples themselves and their findings and ideas for improving data analyses are discussed during the lectures. Students also learn to defend their ideas and discoveries by conducting their project works, where statistical analyses are used in justifying opinions and claims. In addition, students write a study journal. In the study journals students may write down notes about their thoughts and reactions to what has been discussed. Writing and submitting a study journal on time is compulsory for completing the course.

    Majority of students' workload will come from independent assignments. Lecture assignments will take on average 7*10 = 70 hours to complete. That includes finding representative data examples and observing problems in them. Writing the study journal takes on average 20-25 h as total. Project work will take on average about 15-25 h. Attending the lectures takes as total 24 h.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn II
    2023-2024 Autumn II

    Enrollment :

    Registration for Courses: In Sisu (sisu.aalto.fi).

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof