Instructors:
Prof. Dr. M. Rauterberg,
Full Professor
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Workload Lectures (2 hours/week), exercises (2 hours/week) and homework assignments (4 hours/week); in total 8 lecture weeks + 2 weeks examination/re-examination.
Benefits This introductory course provides an overview over research based on empirical data and what we can learn from them. The art and science of learning from data helps students become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to students without compromising necessary rigor. The course has been designed for conciseness and clarity to keep students focused on the main concepts. The data-rich examples that feature intriguing design-interest topics now include topic labels to indicate which statistical topic is being applied. Clear learning objectives for each part make it easy to plan homework. Incorporates simulations in addition to the mathematical formulas enables the student to play with the data.
Learning Objectives
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Previous Knowledge No specific pre-knowledge beyond basic math from highschool is required. |
Abstract
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Course
work
The feedback for this course will be determined by the work done on the set of deliverables (Dx; see below). Each deliverable (Dx) will cover a number of steps. |
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Deliverables [Dx] | Date due |
D1-D4: |
end of each block |
D5: A text with reflections about the whole course (min. 1 A4 page) |
end of week 8 |
Course
schedule
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Date |
Topic |
Background material |
week-1 & 2: |
intro lecture: what is hard core science Teacher: Rauterberg |
obligatory material: pdf-1 optional material: Theory Building in Applied Disciplines |
week-3: |
research methodology: step by step Teacher: Rauterberg |
obligatory material: pdf-2 optional material: Research Methodology |
week-4: | descriptive statistics Teacher: Rauterberg |
obligatory material: pdf-3 optional material: Art and Science of Data |
week-5: | population, sample, and inference Teacher: Rauterberg |
obligatory material: pdf-4 optional material: Art and Science of Data |
week-6: | test design, effect size, and test power Teacher: Rauterberg |
obligatory material: pdf-5 optional material: Essential Guide to Effect Sizes |
week-7-8:
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alpha inflation and other important aspects |
obligatory material: pdf-6 optional material: SPSS Demystified |
examination
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Based on the reports each student will be evaluated individually. |
obligatory material: list of references |
Feedback
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