"I think there is a good learning atmosphere and all the teachers and staff are very friendly and responsible"

Xiaowen Gu stood smiling in front of a pin board, smiling
Xiaowen Gu
Masters student
Statistics MSc
After coming to Sheffield as an undergraduate, Xiaowen chose to progress onto our MSc Statistics course to further develop her professional skills. For Xiaowen, the new challenge of working in teams not only allowed her to develop skills in writing R programs, it also allowed her to meet and learn from fellow students from different cultural backgrounds.

The reason I chose the statistics major is because this profession is closely related to our lives. In almost any real-life field, we need to process and analyse the data obtained.

In some cases, we can't do a lot of physical experiments because it's too complicated and expensive, so we need statistical tools to do some preliminary research to save costs and make predictions. So it is really a useful subject.

The reason for choosing the University of Sheffield is because I studied here when I was an undergraduate. I think there is a good learning atmosphere and all the teachers and staff are very friendly and responsible.

What I find most enjoyable in this whole course is the group projects of various topics. These group projects are not easy for me and I have not had similar experience before, but after several group collaborations, I found that these projects have brought me a lot.

These projects have trained many of our professional skills step by step, including independent data analysis, design and execution of experiments, write R programs, critical review and so on.


Sensitivity analysis can be applied to almost all areas, such as risk management in the economic field, research on key factors affecting temperature in the climate field and so on.

Statistics MSc

Statistics MSc


In each group work, we meet people from different cultural backgrounds and different age groups, it allows me to learn something from them.

I also got the experience of how to coordinate with the team members and the ability of time planning.

I studied the probabilistic sensitivity analysis in computers in my research project. I studied three different sensitivity analysis methods and discussed the number of samples required for each method to analyze which method is better.

Sensitivity analysis can be applied to almost all areas, such as risk management in the economic field, research on key factors affecting temperature in the climate field and so on.

After finishing the course, I will return to China to find a statistical-related job, such as data analysis or consulting work.


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