Understanding Statistics in the World of Work
Netherlands, Maastricht
| Study location | Netherlands, Maastricht |
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| Type | Summer Courses, Full-time |
| Nominal duration | 1 week (2 ECTS) |
| Study language | English |
| Tuition fee | €249 one-time |
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| Entry qualification | Enrolled as an Undergraduate student or Undergraduate diploma Students should have basic knowledge of statistics and statistical software such as R and/or STATA (can be). Students should have a keen interest in understanding labour market statistics. Students should have attended introductory level courses in data science, economics, or sociology. The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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| Language requirements | English The language of the course is English, so we expect a fluent level and the ability to follow and participate in class. |
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| More information |
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Overview
Course Description
In today’s data-driven world, interpreting labour market statistics is a crucial skill. This one-week intensive course is designed to empower students with the knowledge, critical thinking, and data visualization skills necessary to navigate the complexities of labour market data. The course delves into the multifaceted role of statistics in labour market analysis: the potential for misuse, the influence of politics, the role of statistics in social policies, and the importance of statistics to understand social and technological transitions. The course will help students visualise such statistics using R and/or STATA and provide strategies for robust interpretation of statistics on job creation, unemployment, training, and informality.
Goals
• Comprehend the foundations of labour market statistics.
• Identify and scrutinise misuse of labour market statistics (by governments, politicians, and businesses).
• Engage in data interpretation, analysis, and visualisation using R and/or STATA.
• Forecasting labour market statistics.
• Consider future trends in labour market statistics.
• Develop skills in ethical interpretation of labour market statistics.
Recommended Literature
To be decided (Literature will be open source).
Teaching Methods
Lectures, PBL
Assessment Methods
Attendance, Presentation
Course Coordinator
Mantej Pardesi
Central European Time
Central European Time