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Data commentary

Data commentary

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Data commentary

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  1. Data commentary

  2. Whydo data commentary? • Highlight the results. • Assess standard theory, common beliefs, or general practice in the light of the given data. • Compare and evaluate different data sets. • Assess the reliability of the data in terms of the methodology that produced it. • Discuss the implications of the data. From: Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students. University of Michigan Press: Ann Arbor. p. 78. • Help the reader to interpret the dataBailey, S. (2011) Academic Writing: A Handbook for International Students (3rd ed.). Routledge: Oxon, p. 162.

  3. Sample Table 5 shows the most common modes of infection for U.S. businesses. As can be seen, in the majority of cases, the source of viral infection can be detected, with disks being brought to the workplace from home being by far the most significant. However, it is alarming to note that the source of nearly 30% of viral infections cannot be determined. While it may be possible to eliminate home-to-workplace infection by requiring computer users to run antiviral software on diskettes brought from home, business are still vulnerable to major data loss, especially from unidentifiablesources of infection. • From: Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students. University of Michigan Press: Ann Arbor. p. 78.

  4. Structure of Data Commentary Three main points: • Locationelementsand/orsummarystatements • Highlightingstatements • Discussions (implications, problems, exceptions)

  5. Structure of Data Commentary 1 Locationelements and summaries

  6. Locationelements and summaries Table 5 shows the most common modes of infection for U.S. businesses. (active) The most common modes of infection are shown in table 5. (passive) Locationelement • Summary

  7. Common verbsused: • Show • Provide • Give • Illustrate • Display • Present • Summarize • Reveal • Demonstrate • Indicate • Suggest

  8. Whatkind of a summarystatement? IndicativeorInformative?

  9. Indicative: stating the obvious Table 5 shows the most common modes of infection for U.S. businesses. Informative: a summary of the data Table 5 shows that home discs are the major source of computer viruses.

  10. The ’as –clause’ A common way to introduce an informativesummary is using the ’As –clause” As shown in table 5, home disksare the mostfrequentsource of infection. Note the difference in the followingstatements!!! As ithasbeenproved, the theorymayhavepracticalimportance. (cause/effect) As hasbeenproved, the theorymayhavepracticalimportance. (announceorconfirm)

  11. The ’as –clause’ and prepositions (announcing/confirming) • As shown IN table 3, • As canbeseen FROM the data in table 3, • As shown BY the data in table 3, • As described ON page 4

  12. Structure of Data Commentary 2 Highlightingstatements

  13. Highlightingstatements Purpose: to demonstratethat • Youcanspottrendsorregularities in the data • Youcanseparatemoreimportantfindingsfromthoselessimportant • Youcanmakeclaims of appropriatestrength Youdonot: • repeat the details in words • attempt to cover ALL the information • claimmorethan is reasonableordefensible Swales, J. and Feak, C. (1994). Academic Writing for Graduate Students. University of Michigan Press: Ann Arbor. p. 86.

  14. Sampleagain… Table 5 shows the most common modes of infection for U.S. businesses. As can be seen, in the majority of cases, the source of viral infection can be detected, with disks being brought to the workplace from home being by far the most significant. However, it is alarming to note that the source of nearly 30% of viral infections cannot be determined. While it may be possible to eliminate home-to-workplace infection by requiring computer users to run antiviral software on diskettes brought from home, business are still vulnerable to major data loss, especially from unidentifiablesources of infection. Red text= highlightstatements

  15. Highlightingrequires • The writer to becautious and sometimescritical. • The writer to knowhow to express thiscaution. • *Hedging*

  16. Sohowdowehedge? 1. Differentlevels of probablitity • It is certainthat • It is almostcertainthat • It is veryprobable/highlylikelythat a reducedspeedlimit • It is probable/likelythatwillresult in fewer • It is possiblethatinjuries. • It is unlikelythat • It is veryunlikely/highlyImprobablythat

  17. Distance: Compare the following • Consumershavelesscofidence in the economytodaythan 10 yearsago. • Consumersseem to havelessconfidence in the economy. • Consumersappear to havelessconfidence in the economy. • Itwouldseem/appearthatconsumershavelessconfidence in the economy. • Anotheralternative is to make the data ’appear’ soft: • On the limited data available, a lowerspeedlimit • In the veiw of someexperts, mayreducehighway • According to thispreliminarystudy, fatalities.

  18. 3. Weakerverbs: Thisdoesnotrefer to the overusedverbs (be, have, get, try) but to thoseweaker in strength. For example: Deregulationcaused the bankingcrisis. (strong) Deregulationcontributed to the bankingcrisis (weaker)

  19. 4. Generalizations (covered in chapter 2.7)

  20. Cocktailsanyone? These 4 elementsareusuallycombined to constructsomethingreasonable and defensible: Startwith a big claim: The use of seatbeltspreventsphysical injuriesin caraccidents.

  21. Take ”The use of seatbeltspreventsphysicalinjuries in caraccidents” then… Change: preventsreduce (weakerverb) reducesmayreduce (weakerstill) Add: In somecircumstances (weaken the generalization) certaintypes of injury (weakening the generalization) According to simulation (addingdistance – softening) studies

  22. Endresult? According to simulationstudies, in some circumstances the use of seatbeltsmay reducecertaintypes of physicalinjuries in caraccidents. = confidentlyuncertain

  23. Exercise 1 - Highlighting

  24. Structure of Data Commentary 3 Discussions (implications, problems, exceptions, etc.)

  25. Discussions… • Usequalifyinglanguage, just like in highlightingphrases. • Usuallyfollow the followingstructure • Explanationsand/orimplicationsusuallyrequired • Unexpectedresultsorunsatisfactorydata ifnecessary • Possiblefurtherresearchorpossiblepredictionsifappropriate

  26. Sampleagain Table 5 shows the most common modes of infection for U.S. businesses. As can be seen, in the majority of cases, the source of viral infection can be detected, with disks being brought to the workplace from home being by far the most significant. However, it is alarming to note that the source of nearly 30% of viral infections cannot be determined. While it may be possible to eliminate home-to-workplace infection by requiring computer users to run antiviral software on diskettes brought from home, business are still vulnerable to major data loss, especially from unidentifiablesources of infection. Red text = implications

  27. Exercise 2 – the wholeenchilada

  28. Homework • Chapter 2.11 – Visual information