Introduction to Quantitative Research Methods (QNRM)

Graduate Program (& Advanced Certificate) Status

Course Level: 
Master’s
Campus: 
Vienna
Course Open to: 
Students on-site
Academic Year: 
2022-2023
Term: 
Fall
US Credits: 
1
ECTS Credits: 
2
Course Code: 
ENVS5154
Course Description: 

“Show me the numbers!” or “Do we really need more numbers here?”

Quantitative empirical data and statistical analyses can seem like holy grail of ‘real science’ or like a very complicated way of presenting obvious truths. Through hands-on work with quantitative environmental accounting data, accompanied by short lectures and in-class discussions, students will be introduced to the opportunities and challenges of this line of research and the insights it yields. The overarching aim is to qualify students both as critical consumers of quantitative research (in academic publications and popular media, especially) and as competent producers of their own basic analyses. This course aims to cater to different skill levels, but may underwhelm students familiar with interpretation and basic manipulation of quantitative data. If in doubt, please contact the instructor! Those who have been shying away from ‘anything with numbers’ altogether are especially welcome.

Learning Outcomes: 

At the end of the course, students will be able to

-        identify and describe key terms and concepts in quantitative research,

-        explain the role of measurement and units in data generation,

-        conduct basic statistical analyses of central tendency and variation and interpret the results

-        organize data and run basic functions in graphical user interface (GUI) spreadsheet software (e.g. Calc),

-        examine the role of quantitative empirical work for environmental research and research communication,

-        identify different forms of visual representation of quantitative data and critically reflect and discuss how this impacts the message communicated,

-        organize and analyze data and create visual representations for their own mini-projects.

Assessment: 

The class is pass/fail. In order to pass, students must actively participate in class, complete the in-class and at-home exercises, and complete a min-project by the end of the class.

Prerequisites: 

None