Overview
Part of the ModularMaster in Data Science (Healthcare) programme
Data Validation and Statistical Analysis are critical components in the field of data science, playing a vital role in ensuring the accuracy, reliability, and meaningful interpretation of data. Through data validation techniques, professionals can verify the integrity and quality of the collected data, identifying and addressing any inconsistencies, errors, or outliers that may impact the analysis. By conducting rigorous statistical analysis, they gain insights into patterns, relationships, and trends within the data, enabling evidence-based decision-making. Statistical analysis allows for hypothesis testing, correlation analysis, regression modeling, and other techniques to draw valid conclusions and make reliable predictions. The combination of data validation and statistical analysis ensures that data-driven insights are robust, trustworthy, and actionable, empowering organizations to make informed choices and achieve meaningful outcomes.
This course, spanning a duration of five days, is specifically designed to equips participants with valuable skills in data exploration, statistical anomaly detection, and dataset validation in healthcare contexts. Over the first four days, participants will learn essential skills related to exploring data distribution, detecting statistical anomalies, and statistically validating datasets. The course will equip healthcare professionals with the necessary tools to analyse healthcare data effectively and make informed decisions based on statistical evidence. Participants will be actively involved in a healthcare-related project throughout the module. The final day, which is split into two half-days on separate weeks, will be dedicated to project consultation and project presentation.
Plan your learning path
This course can be taken as a module on its own or as part of the Graduate Certificate in Data Analytics (Healthcare) or ModularMaster in Data Science (Healthcare).
Who Should Attend
Catering to healthcare professionals and individuals aspiring to join the healthcare industry, this course is specifically designed to develop essential skills in validation and statistical analysis of data. It is highly recommended for clinicians, administrators, and managers who involve in crucial task of finding patterns in data and making inferences about those patterns, as well as preparing aspiring data analysts or data scientists to perform rigorous statistical testing on healthcare data.
Prerequisites
- Participants should preferably have passed mathematics at least ‘O’ Level or equivalent.
- Participants should preferably have basic knowledge of statistic.
- Participants should be conversant with basic IT skills such as software installation, file management and web navigation.
- Participants are encouraged to complete the Foundation of Data Science and Data Wrangling and Preparation with Programming before enrolling in this course.
- Participants are required to pass a pre-course assessment to ensure participants have the requisite knowledge of Python programming. This assessment can be waived if participants have completed both Fundamentals in Python (Basic) and Fundamentals in Python (Intermediate).
- Participants are required to bring their laptops.