Brief notes from week 1 & 2 of “Writing in the Sciences” course

Hello, folks!

I am not good at writing. So I decided to take “Writing in the Sciences” [1] course from Coursera [2] to overcome the fear of not being a good writer. A big thank you to Dr. Kristin Sainani [3] for this great course 🤗 While taking this course, I would like to share highlighted points of the course. In this post, you can find brief notes from the first two weeks. Let’s start 🙌🏽

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The followings are suggestions for the principles of effective writing:

  • Cut unnecessary words and phrases
  • Use the active voice (subject + verb + object)
  • Write the verbs (use strong verbs, avoid turning verbs into nouns, and don’t bury the main verb)

She points out that there are some advantages using the active voice as below:

  • Emphasizes author responsibility
  • Improves readability
  • Reduces ambiguity

She also highlighted that it is OK to use “We” and “I”.

There are also some suggestions about avoiding turning verbs into nouns:

  • obtain estimates of → estimate
  • has seen an expansion in → has expanded
  • provides a methodologic emphasis → emphasizes methodology
  • take an assessment of → assess
  • provide a review of → review
  • offer confirmation of → confirm
  • make a decision → decide
  • shows a peak → peaks
  • provide a description of → describe

She emphasizes a few grammar tips:

  • The word “data” is plural
  • Be careful about the use of affect vs. effect (in general, affect and effect take the form of verb and noun, respectively)
  • That vs which (“that” is the restrictive (defining) pronoun and “which” is the nonrestrictive (non-defining) pronoun)
  • Singular antecedents (do not use “they” or “their” when the subject is singular. to avoid gender choice, turn to a plural)

That’s all for now. I hope it will be helpful to you. Goodbye until next time!🦄

References

[1] https://www.coursera.org/learn/sciwrite

[2] https://www.coursera.org/

[3] https://profiles.stanford.edu/kristin-sainani

Written by

Ph.D. Cand. in CmpE @Boğaziçi University. #ai #privacy #uncertainty #ml #dl #running #cycling #she/her https://www.cmpe.boun.edu.tr/~gonul.ayci/

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