1. Dr Nicky Cashman, Aberystwyth University nnc@aber.ac.uknnc@aber.ac.uk Gregynog, 2010

2. Use of data Formatting Ethical issues Where to start Gathering information Creating the document Surveys and other forms of reporting Conclusion

3. Descriptive: Statistics that merely describe the group they belong to, e.g. the class did well on its first exam, with a mean (average) score of 89.5% …and inferential. These are statistics used to draw conclusions about a larger group of people, e.g. our research indicates that only 33% of people like purple cars

5. Any statistical investigation produces an output data that needs to be analysed. So, organise it, study it under different circumstances and control the data as required This data needs to be modified in a presentable form so that further conclusions and inferences can be drawn

7. Tables – much easier to read than a block of text. It can help to sort the information/group comparisons etc for both you and your audience Group AGroup BGroup CGroup D Mean10.512.315.921.3 S.D. (standard deviation) 2.11.21.82.5

8. Pie chart – to give a general indication of percentages/groups etc via each ‘slice’

9. Bar chart – a way of representing absolute numbers

10. Histogram – a way of encapsulating data that can be summarised on an interval scale

11. Scatter Plot – to illustrate the degree of correlation (not causation) between two variables

12. Line graph – to demonstrate a continual stream of data which could indicate growth, decline, peaks and troughs Early years education Number of three and four-year-olds at school triples

14. Failure to deal honestly with readers about non-random error (bias) Inappropriate statistical tests and other statistical procedures Fragmentation of reports Low statistical power Suppressing, trimming, or “adjusting” data Selective reporting of findings www.flickr.com

15. The task in all of this is to do the best job possible to assure that the numbers represent the actual population or process. Anything which distorts the true depiction of the original population or process might lead to false conclusions, which is an ethical problem

17. Costly waste of resources Difficult statistical analysis Data for which interpretation is controversial Research which is precise but which answers the wrong questions

18. Determine beforehand what sort of information is required Remember that the order or arrangement of the data does not matter You have the freedom to organise the subject under study – consider keeping subjective material Creating a statistical data set is only the first step in research. The interpretation and validity of the inferences drawn from the data is what is most important www.flickr.com

19. Who has asked for this report? Who is likely to read this report? What do you think they want to know about? What do you want to highlight? Do you need to collaborate with colleagues? What is the eventual purpose of the report? Should it be monthly, bi-annual and/or annual? http://www.mindwaveglobal.com/Profile. html

21. http://www.google.com/analytics/ with repository statistics [IR Stats with E-Prints] http://www.google.com/analytics/ Top articles Top theses Most searched departments Number of visits/hits & from where in the world Asking individual academics for comments Listing past, present & future repository projects & collaborations

25. TRY SOME VARIATION… SOME COLOUR…DIFFERENT FORMATS…

26. General Overview JANFEBMARAPRMAYJUNTotal Items Archived 4925414020296453 Page views17,59020,64925,78721,60326,46222,616134,707 Visits4,5855,3497,3687,0547,3076,16837,831 VISITS: JAN-JUNE 09 WORLD-WIDE PERCENTAGE UK - 13,57035.87% US - 6,02615.93% Ind - 1,8194.81% Can - 1,1282.98% Aus - 9362.47% Ger - 9162.42% Spa - 8562.26% Chi - 7141.89% Ita - 5631.49% Fra - 5191.37% CADAIR: STATISTICAL REPORT – JANUARY - JUNE 2009

27. Top 3 articles across Aberystwyth University Top 3 theses Main contributors (departments) Projects Collaborations

28. Thank you for the invitation to add papers on Cadair. Prof Michael Hambrey, IGES. That’s all looking very good. Thanks for addressing it so quickly. Prof David Ian Rabey, TFTS 'I have found CADAIR to be a most effective and efficient way of publicising my work ’. Prof Nicholas Wheeler, InterPol. “I think CADAIR is a vital resource for the University, and should be the default used to accurately record and assess research output. My view is that it should record only published outputs: preprints should be discouraged as there are servers available for this purpose elsewhere. It should be used internally for consideration by committees such as Awards and Titles, post-graduate competitions, departmental research monitoring, etc. Externally, it fulfils the role of dissemination of published research now required by the Research Councils. It is easy to use and compares favourably with other repositories. There is no reason why CADAIR should not become mandatory, and act as the definitive source of information on published research output for Aberystwyth”. Prof John Gough, IMAPS “I think that Cadair represents a very helpful new development in the services provided by the university. The internet is a most powerful research tool – increasingly papers are being accessed first in this way. From my perspective Cadair provides an opportunity to give access to work that is no longer available elsewhere and also links to more recent work which is available in print or internet form”. Prof Howard Williams, Department of International Politics.

29. MOST SEARCHED DEPARTMENTS: Information Studies – 677 times IBERS – 422 times Computer Science – 363 times History and Welsh History – 340 times International Politics – 305 times

31. 50 universities and their e-theses mandates were surveyed – questions via email to UKCoRR discussion list + hard copy forms (survey monkey another option) There are 166 universities in the UK (Universities UK 04/05/2010) Therefore, this inferential survey shows 30.1% of them all (50÷166x100) Organise data under appropriate headings Plot information initially on an Excel spreadsheet if you are comfortable with this format http://pinoyelections.com/wp- content/uploads/2010/03/survey.jpg

32. Proposal to AU Research Degree Board to move to an opt-out mandate Of 50 UK HEIs, 34 have opt-out mandates, 8 opt-in, 8 none at all

33. Headings included: What mandate does AU presently have? What have been the problems faced? What mandates do other UK HEIs have? Why choose opt-out? How can we address potential issues? What do we do next? TOP 5 THESES IN AU Depts. No of hits Postmodern NihilismEnglish3038 Poetics of the PastEnglish2332 Management Control Systems SMB2210 A Library of our OwnDIS1718 Consonantal System of Cornish Welsh1626

34. For individual academics – how many hits an article has received/where in the repository list For departments – impact of articles/items submitted to repository/impact of postgraduate theses To your own department – external visits to the repository etc Personal portfolio – detailed examples of work achieved/courses attended/presentations given http://www.aecsoftusa.com/picElements/2 TierReporting.jpg

35.  PRESENTATIONS  CONFERENCES & EVENTS  INDIVIDUALLY DESIGNED TRAINING & WORKSHOPS  INTENAL/REPOSITORY MEETINGS  EXTERNAL MEETINGS  COURSES ATTENDED  ONE-TO-ONE MEETINGS WITH ACADEMICS  I.S. RELATED ACTIVITIES  REPOSITORY PROJECTS  MEMBERSHIPS/ASSOCIATIONS  REPORTS/PUBLICATIONS & ADVOCACY http://office.microsoft.com/en-us/templates/TC300001821033.aspx?CategoryID=CT101043361033

36. Were the original questions important? Were the assumptions from which the original questions emerged valid? Was there adequate precision and planning? Was there the proper degree of generality? Was the research overambitious? Have there been proper control checks? Was there an extension of the purpose of the research after it was planned, for another function?

37. Know who the information is for Gather relevant data Decide on appropriate formats Use a variety if possible Ask for opinions Make sure data is correct

38. Bailar, J. C. (1997) Science, Statistics and Deception, in Research Ethics: A Reader (Deni Elliott and Judy E. Stern, eds., Hanover University Press: of New England, 104. Brown, J. (n. d.)Literature review of research into attitudes towards electronic theses and dissertations (ETDs). London E-Prints Access Project, http://www.sherpa-leap.ac.uk/http://www.sherpa-leap.ac.uk/ Greig, M. (2005) Implementing electronic theses at the University of Glasgow: cultural challenges. Library Collections, Acquisitions and Technical Services, 29, 326-335. Nelson, L. A., Crotty, M. (n. d.) The Ethical Use Of Statistics in Research. North Carolina State University. Initial draft. Pickton, M.J., McKnight, C. (2006) Research students and the Loughborough institutional repository. Journal of Librarianship and Information Science, 38, (4), 203-219. Office for National Statistics: http://www.statistics.gov.uk/glance/http://www.statistics.gov.uk/glance/ American Statistical Association: http://www.amstat.org/publications/sadm.cfmhttp://www.amstat.org/publications/sadm.cfm International Statistical Institute: http://isi.cbs.nl/ethics.htmhttp://isi.cbs.nl/ethics.htm

39. Unless otherwise referenced, all images from Word Clip Art or my own charts and data. Nicky Cashman, Gregynog 2010 nnc@aber.ac.uknnc@aber.ac.uk