Lies damned Lies and Statistics Rhys Jones Lecturer

Lies, damned Lies and Statistics Rhys Jones Lecturer in Quantitative methods FE Cardiff University – SOCSI http: //sites. cardiff. ac. uk/qstep/.

Quantitative approaches in the social sciences �Shortage in Social scientists with quantitative background (Williams, Payne and Hodgkinson 2008, Payne 2014, Platt 2014) �Universities and Science Minister: "Evaluating and analysing data is an essential part of science education and we need more people with these important skills. ” �A level/FE Sociology content – research methods module at AS and A 2

What is Q Step? �Q-Step is a nationwide initiative to promote a step change in quantitative social sciences (Nuffield 2014) �£ 19. 5 m programme funded by UK Government �Involves 15 centres - only Q-Step Centre in Wales is based at Cardiff University �Scientific investigation of social process using statistical analysis

�A major strand of the Cardiff Q-Step Centre work will focus on the development of a new L 3 qualification (and L 2) in Social Analytics �Working with WJEC, Welsh Government, Agored Cymru and Royal Statistical Society (now ICSE – International centre for Statistical Educati 0 n) �Launch a new BSc Social Analytics in September 2015

Pilot scheme in SA 2014/15 �Two hours per week (Wed) � 5 local school and colleges – 50 students �Hosted at Cardiff University �Postgraduate input �Worksheets & activities completed in class �Certificate of attendance �Welsh Baccalaureate requirements (2015 compulsory)

Programme: QCF level 3 Pilot in Social Analytics Course: Unit 1 – Social Science in Practise (SSP) Unit 2 – Applied Statistics (AP) Scheme of Work 2014/15 (Wednesday 4. 00 -5. 00 pm – break – 5. 30 -6. 30 pm) Week Date (Week commen cing) Topic Unit 1 SSP (4 -5 pm) Unit 2 AP (5. 30 -6. 30 pm) Induction Statistics covered Assessment/ Assignment Designing research questions and correlations Unit 2 AP - Launch coursework Hand in data: Draft: 19/12/2014, Final: 13/02/2015 1 15/09 2 22/09 3 4 5 6 29/09 06/10 13/10 20/10 Health changes over time What is intelligence? Infection and disease Food and learning Epidemiology Genes and learning Data analysis and simulation Hypothesis testing t tests ANOVA 7 8 9 10 27/10 03/11 10/11 17/11 24/11 Half Term break Data analysis and visualisation Coursework and presentation guidance ANOVA Unit 1 SSP: Coursework/Worksheets 11 12 Introduction to health Psychology of learning introduction Gender and Health professionals Boys vs girls ANOVA 01/12 Science tech and the real world introduction Mass media and journalism introduction Chi squared test 08/12 What is science? Science in the media Chi squared test

Subject y ia ed gy ol o M Ge og no l hs t Ar w La s es sin in La t m at ch te ic us M er Fu rt h Bu hy rm an Ge ic ap og r Ge s or y ist H s re tu ra te ic Po lit on om Ec ish li gl En og y ol y s s ic og ho l ci So Ps yc m at Ph ys ic he at M ry ist ol og y em Ch Bi Student numbers A' level courses studied (AS and A 2) 30 25 20 15 10 5 0

Attendance 2015 (total students = 43) 50 45 40 35 30 25 20 15 10 5 0 19 01 26 01 02 02 09 02 23 02 02 03 09 03 16 03 26 03

Student evaluation Pilot Scheme SA 2014 -2015 45 40 35 30 25 20 15 10 5 0 Agree or strongly agree Dec 2014 Disagree or strongly disagree Dec 2014 Agree or strongly agree April 2015 Disagree or strongly disagree April 2015 I can see the value of the course to my other studies I enjoy the statistical elements of the course The statistics is linked well with relevant examples

Subjects Social Analytics supports Science Business studies Social Sciences Welsh Bacc Humanities Health (medicine etc) Maths

Benefits �Suitable for students studying sociology, psychology, mathematics, geography, health, business studies, economics and the sciences in either years 12 or 13 �Opportunity to participate in the development of a new L 3 Social Analytics Qualification �Admissions tutor briefings from Cardiff University �Improve students’ current attainment �Enhance student UCAS applications �Enriched learning environment

LEARNING OUTCOMES The learner will: 1. Know how social issues can be measured and monitored. ASSESSMENT CRITERIA The learner can: 1. Explain the strengths and weaknesses of methods used to measure and monitor a range of social issues. 2. Outline the strengths and weaknesses of primary and secondary data. 3. Design hypotheses and related questions to explore social issues. 2. Be able to carry out statistical tests linked to data sets derived from social issues. 3. Be able to evaluate the outcomes of statistical testing. 1. Perform ‘t’ tests to compare secondary data sets linked to the range of issues in 1. 1. 2. Perform Chi squared tests on data sets related to a social issue. 3. Perform regression analysis between two variables. 1. Evaluate the reliability and validity of evidence produced from statistical tests. 2. Draw conclusions from the analysis of the data sets.

Assessment Information AC 1. 1 A minimum of two different methods and two social areas e. g. Health, science and crime. AC 1. 3 A minimum of two hypotheses. AC 2. 1 A minimum of two tests. AC 2. 2 A minimum of two tests. AC 2. 3 A minimum of three sets of two variables. AC 3. 1 Evaluate evidence from a minimum of two statistical tests. AC 3. 2 A minimum of two data sets from a range of different issues.

Other activities �Teacher placement scheme �CSC workshops �WBQ 2015 Conference – Cardiff university (WJEC and WG) �Pilot scheme in SA due to run again in Sep 2015 (2015/16) �ESRC Festival of Social Science (Nov 2015)

BSc Social Analytics �Builds on pilot scheme SA (level-3) �Placement module (6 week) � 20 employers involved (ONS, Welsh Government, Nat. Cen, British Gas, You. Gov, Shelter Cymru) �BSc Social Analytics – J 395 �BSc SA and Politics – L 3 HW

References �Nuffield Foundation (2014). Available from: http: //www. nuffieldfoundation. org/q-step. Accessed on: 05/12/2014. �Payne, G. (2014). Surveys, Statisticians and Sociology: A History of (a Lack of) Quantitative Methods. ELi. SS; 6(2): 74 -89. �Platt, J. (2014). Making them count: How effective has official encouragement of quantitative methods been in in British sociology. Current Sociology; 60(5): 690 -704. �Williams, M. , Payne, G. and Hodgkinson, L. (2008) ‘Does Sociology Count? Student attitudes to the teaching of quantitative methods. ’ Sociology; 42 (5): 1003 -1022

Rhys Jones Lecturer in Quantitative Methods FE Jones. RC 10@cardiff. ac. uk; 029 2087 0106 Andy Dodge Placements Manager Dodge. A@cardiff. ac. uk; 029 2087 0098