{"id":2540,"date":"2022-11-10T15:26:26","date_gmt":"2022-11-10T15:26:26","guid":{"rendered":"https:\/\/sites.manchester.ac.uk\/sossteachlearn\/?page_id=2540"},"modified":"2022-11-10T15:30:33","modified_gmt":"2022-11-10T15:30:33","slug":"social-statistics","status":"publish","type":"page","link":"https:\/\/sites.manchester.ac.uk\/sossteachlearn\/about\/depts\/social-statistics\/","title":{"rendered":"Social Statistics"},"content":{"rendered":"

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Social Statistics<\/h1>\n

Department statement<\/h2>\n

At undergraduate level, Social Statistics has been expanding teaching through the development of new course units and new degree pathways in the two main School interdisciplinary degree programmes, BASS and BA(Econ). The Award of the Manchester Q-Step Centre<\/a> (led from Social Statistic) has been particularly influential in shaping our teaching approach at UG level where we put considerable emphasis on the value of learning through practical application of skills to real problems using real world data<\/strong> and crucially to make connections with the substantive subject areas in which many of our students are studying. We make heavy use of lab-based learning<\/strong> where students get to put theory into practice, building experience and confidence in how to source, handle and make sense of the ever-increasing range of digital data, using a range of different software and analytical approaches. The development of new courses is shaped by emergence of new areas of demand and interest, and to the new forms of digital social data available.\u00a0 Thus, alongside teaching of traditional survey methods we have specialist courses in analysis of social media data, demography, social network analysis and policy evaluation<\/strong>.<\/p>\n

The Q-Step drive to make the learning of stats relevant and embedded within substantive curriculum is further reflected in the way we have sought to build applied data analytics pathways in the two main school interdisciplinary degree programmes, where we offer the chance for students to specialise in substantive areas with data analytics. We are conscious that for these to be appealing we have to make our courses accessible to those who come from backgrounds without a lot of experience or confidence in studying quantitative approaches (most BASS entrants do not have A level maths) and this is a key consideration in the way we design out courses with minimal use of pre-requisites<\/p>\n

At undergraduate level, Social Statistics staff have been instrumental in developing more innovative ways of teaching quantitative schools. These have included a series of externally funded grants on curriculum innovation culminating in the award of the 5-year Q-Step Centre from 2014. Led by Social Statistics in collaboration with other Social Science departments this has led to a series of curriculum developments with new courses (featuring teaching with real world data and substantively embedded) and a nationally recognised internship programme led by Jackie Carter.\u00a0<\/p>\n

Another Q-Step initiative was the development of a Q-Step Help Desk to support final year students choosing to do a dissertation with quant methods. This addressed a \u2018gap\u2019 in the provision of quants support in the 3rd year curriculum (most methods courses being focussed in year 2). It has led to a notable increase in students now opting to use quants in dissertations, incentivised and rewarded with our subject based Q-Step dissertation prizes (with our students also featuring among the winners of the UK Data service national Dissertation Prizes)\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\n

We have a number of exciting developments<\/strong> in the pipeline at both UG and PG level. This includes development of new course units at undergraduate level to further integrate us into the School\u2019s interdisciplinary degree programmes. This includes two new units with an international perspective that are targeted to the new BASS Global Change programme. This will take our UG portfolio to 11 across 3 years, an expansion that is crucial for the medium to longer term goal to develop our own dedicated undergraduate programme.\u00a0 Having our own dedicated programme would be a major boost to building a UG student identity in our department (see challenges and obstacles).\u00a0<\/p>\n

At postgraduate level there are firm plans for some major developments that build off the success of the MSc SRMS. This includes the forthcoming launch of a Distance Learning version of SRMS. We are also looking to build on the synergies with data science where our key involvement in the highly successful cross-school PG programme in data science, has identified considerable demand for training in this area, leading to development of proposals (at various stages) for a new MSc in Social Stats and data science, an MSc in Computational Social Science and a UG programme in computational data science.<\/p>\n

Information about studying Social Statistics at The University of Manchester<\/a><\/p>\n

People in the Social Statistics Department<\/a><\/p>\n

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Contact Us<\/h4>\n

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The University of Manchester
Oxford Rd
Manchester
M13 9PL
UK<\/a><\/p>\n

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