Faculty of Health, Medicine and Life Sciences

Module Information

Good afternoon

EPH1026 - Introduction to Statistical Methods for Data Analysis

Period 6: from 9-6-2025 to 4-7-2025
Co-requisites:
None
Coordinator: Jolani, S.
ECTS credits: 5
Language of instruction: English

Publication dates timetable/results in the Student Portal

Deadline publication timetable
The date on which the timetable of this module is available: 23-5-2025

Deadline publication final result
The date on which the final grade of this module is available: 8-7-2025

Resit booking

Exam booking for a test in current academic year (resit)
You will be booked automatically for the resit in one of our resit periods. You may check our calenders to find out which modules can be retaken and when: https://intranet.maastrichtuniversity.nl/nl/fhml-studenten/studieverloop/wanneer-wat
As of one week before the resit test takes place, you can check in Student Portal if you are booked correctly: Student Portal > My Courses > More actions. The test will also be visible in your time table.

Exam booking for a test from a previous academic year (exam only)
All students who have not passed the test for this module in a previous academic year, will be booked automatically for the test during the regular block period. You will be enrolled in the new course in Canvas but not scheduled for a tutorial group and other educational activities. If you do not wish to participate in this test at the end of the regular block period please de-register via askFHML.

Resit date: 17-7-2025

Though great care has been taken to assure the accuracy of the information on fhmlweb, the FHML cannot be held responsible for possible printing errors, incomplete information, or misinterpretations. Additionally, the FHML reserves the right to make changes to this information.

Course information

Description:	EN: Year one of the new BEPH curriculum concludes with the statistics module, which builds the foundation of statistical methodology and hypothesis testing. The module consists of three themes: (1) Summarizing and describing research data; (2) Testing concept, generalization of results obtained from sample; (3) Introduction to basic statistical techniques. The first theme explores various methods for summarizing and visualizing data collected within a specific research context. Students learn about typology of variables (quantitative vs qualitative), central tendencies and dispersion, and graphical tools like histogram and boxplot. In addition, they study measures of association between two variables such as Pearson correlation, relative risk and odds ratio. An important focal point is the difference between correlation and causation. Theme two of the module is devoted to inferential statistics implying the degree to which conclusions obtained from a sample (of persons) can be generalized to a much larger group (i.e., population). A distinction is made between population, sample and sampling distribution. The latter eventually leads to the concept of confidence intervals for testing. Statements about the population are translated statistically as a null hypothesis and alternative hypothesis and concepts like significant level, p-value, type I and type II errors, and power are discussed in detail. In theme 3, students are introduced to basic statistical techniques for testing a hypothesis, such as the t-test for one sample, two (paired and unpaired) samples, and post-hoc comparisons for more than two samples. Finally, the module ends with simple statistical methods for studying relationships between two variables like the chi-square or linear regression analysis.
Goals:	EN: *Expert* By the end of the module, students should be able to: and name basic public health measures of health status E211. Recall E312. Distinguishes the concepts of correlation and causality E313. Recognizes scientific evidence establishing correlation and causality of investigated factors with health status *Investigator* By the end of the module, students should be able to: I612. Explains basic forms of (qualitative and) quantitative research methods and data collection I614. Matches and applies basic statistical analyses to research data I811. Define science, scientific thinking and scientific knowledge I813. Assess scientific research and publications at a basic level under close supervision I814. Recall fundamental principles of research ethics and integrity I1012. Reads selectively in terms of both quantity and quality of reading material *Communicator* By the end of the module, students should be able (on a basic level) to: C1211. Presents on public health topics for peers and teachers C1212. Discuss topics and findings in English (aiming for level B2) C1312. Demonstrate understanding of feedback from teachers and peers C1313. Produce limited feedback for peers under supervision *Professional* By the end of the module, students should be able to: P1612. Accept and reflect on feedback from staff and students passively P1615. Behave in a respectful, professional and reliable manner in tutor groups, practicals and group work. P1711. Contribute actively and positively in tutor groups and training groups P1811. Understand, describe and apply the problem-based learning approach P1813. Positively engages the challenges and opportunities of intercultural diversity within tutorial groups
Key words:	EN: Health, (European) public health, problem based learning, methodology, epidemiology, descriptive statistics, inferential statistics, data analysis
Literature:	This is the link to Keylinks, our online reference list.
Teaching methods:	Assignment(s) Work in workgroup(s) Lecture(s) Problem Based Learning Skills Training(s)
Assessments methods:	Assignment Attendance Written exam

This page was last modified on:22-5-2023