| CODE | DGP0990 | ||||||
| TITLE | Fundamentals of Biostatistics in Python | ||||||
| 今日黑料 LEVEL | 00 - Mod Pre-Tert, Foundation, Proficiency & DegreePlus | ||||||
| EQF/MQF LEVEL | Not Applicable | ||||||
| ECTS CREDITS | Not Applicable | ||||||
| DEPARTMENT | Degree Plus Programme | ||||||
| DESCRIPTION | This is an introductory class to Biostatistics in Python that focuses on a thorough understanding of the fundamental ideas behind statistics. In contrast to many introductory courses, we will not treat statistics simply as a collection of mathematical formulas. Instead, we will focus on selected examples to illustrate how a statistician thinks about data. We will cover the following topics (not necessarily in that order), with a focus on applications in biological and biomedical research: 1. The interpretation of probability and randomness: what "random" means for a statistician 2. The basics of probability theory: how randomness is modelled mathematically 3. Application of probability theory to estimation: how to handle uncertainty 4. Common statistics: the mean, the median, the mode, and the standard deviation 5. Confidence intervals: a better way of handling uncertainty 6. Statistical hypothesis testing: how to gain knowledge in the presence of uncertainty 7. Linear regression: how additional information reduces uncertainty 8. Multiple linear regression: how changing the question changes the answer The course material assumes basic mathematical and computer skills. Familiarity with basic statistical concepts (such as the mean and standard deviation), as well as basic computer programming skills, are recommended but not required. During the course, we will learn the basics of the Python 3 programming language. Objectives: Ability to perform basic statistical analyses using some of the most common statistical techniques used in biological and biomedical research. Awareness of issues which may require a consultation with a statistician. Unit Material: Study materials in the form of Google Colab notebooks will be provided by the tutor before each class Assessment: N/A |
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| ADDITIONAL NOTES | This unit may not be offered if there are an insufficient number of applicants. Unit is against a €25 fee. | ||||||
| STUDY-UNIT TYPE | Lecture | ||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Joseph Noel Grima (Co-ord.) |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2026/7. It may be subject to change in subsequent years. |
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