Presentation on theme: "Technical Writing NISS – ASA Workshop JSM Salt Lake City 29 July – 1 August."— Presentation transcript:
Technical Writing NISS – ASA Workshop JSM Salt Lake City 29 July – 1 August
Writing for a Technical Audience Purpose: To Inform Aspects Structure Choice of Material Organization of Ideas Depth of Detail Style Grammatical Structure Word Choice Caveat: Don’t Lose the Reader!
A Technical Writer Is NOT: J.K. Rowling Kid at summer camp Norah Roberts Peter Mayle Ken Follett Dan Brown or Iain Pears Alexandre Dumas Thomas Hardy or Charles Dickens Emily Bronte D.H. Lawrence Cervantes Artur Perez-Reverte or Franz Kafka Leo Tolstoy
A Technical Audience is NOT: On a QUEST Challenge to participate Obstacles to overcome, each more difficult than the one before Prize for success Penalty for failure Keywords Title Abstract Introduction Body of article Section by section Result Theorem Discussion/Conclusion
Starting Point Decide Purpose Breakthrough (ground-breaking) – new formulation to solve old or new open problem Progress / development – often new methodology or extension to higher dimension, a new context, or relaxation of assumptions Comparison of existing methods with/without modification Reprise – new more elegant proof of known result yielding greater insight, often entirely new technical approach Illustration – application to real problem/ data of importance, typical of other applications Scientific result – not primarily statistical innovation Identify Major Results Determine Audience
Structure: Logical Introduction Problem Statement in Technical Form Sequence of Lemmas and Theorems Primary Result Example / Simulation / Proof of Concept Discussion or Conclusions Simple Case / Progression to General Case Primary Result Application Example / Simulation / Data Analysis
Structure: Signposts Goal: Provide reader with a map to the article “You are here” and “What comes next” Introduction Outline for article, section by section Section - preamble or paragraph Outline for section Overview of sequence of lemmas, theorems Overview of model development, inferential method construction Overview of data, analytic sequence Extensive proof or complex algorithm Paragraph (as preamble) outlining proof or construction Sentence (midway) summarizing what has been proved, what comes next Outline for subsection – introductory paragraph Paragraph – opening sentence stating purpose
Choice of Material Space allocation – by importance Of result and its consequences For making reasoning transparent Critical steps and keys to solution Proofs “Substitute (#.#) into (#.##) and apply Green’s theorem” Construction / derivation of methodology “Noting that (#.#) can be rewritten as a mixed model with correlated error structure, partitioning by... gives” Application – orderly analysis Principle finding through consequences OTHERWISE: Skip the obvious and summarize “By straightforward but tedious algebra... “ Following the proof by ***** in (reference) NOT by chronology of research NOT by pain of obtaining result
Introduction Goals Convey Importance, Impact of research results Attract readers Content General Context What is the problem? Why care about the work? Technical Context What was already known? What was the gap (before this paper)? Contribution of this paper What is the approach to (nature of) the solution? Outline of paper – “Signposts” References within text Natural choices, signal papers – not entire literature review Citation without interrupting flow of text
Style: Transparent, Clear, Precise, Parsimonious, Concise, Spare, Lean, Direct Overall Impression “Careful writing reflects careful work” Precise word usage – Standard English 1:1 Word:Concept Precise notation usage Definition before first use of notation or symbol 1:1 Notation:Definition Numbered for internal referencing throughout text (as appropriate) Repeated (brief) definition for delayed use or for modification (e.g., dropping subscript) Grammar! Spell and grammar check Useful Neither Necessary nor Sufficient References: Strunk & White
Style: Transparent, Clear, Precise, Parsimonious, Concise, Spare, Lean, Direct Effective Writing Verbs ACTIVE not passive when possible Correct verb tenses Data Exist – Present (NOTE: Data ARE - plural) Papers Exist – Present Experiments End – Past Theorems Hold - Present Clear Sentences CONSISTENT voice – either 1 st person (“I” or “we”) or 3 rd person USE PARALLEL structure for series Series of sentences Series within sentences – clauses, verbs, objects DISENTANGLE complex sentences Reference numbering Equations Figures – all types Definitions – if referred to later, especially for section-long gap
Style: Transparent, Clear, Precise, Parsimonious, Concise, Spare, Lean, Direct “Do Not Litter” DELETE: Wasted sentences Vague, overly general Only approximately (not precisely) true Unnecessarily repetitive “Mixed models are important to many areas of application.” DELETE: Wasted phrases and words “It is easy to see that...” “In order to...” (“To” almost always suffices) Most adjectives, especially judgmental, emotional REPLACE: Non-standard English Personal words... You are not [yet] Tukey Cute / funny / trendy / jargon /TXT expressions
Abstract: Illustration This article proposes...[a general semiparametric model...]... This model provides... [tests]... This contrasts with previous approaches based on... We demonstrate that conditional likelihood is robust to... Its main advantages are that... A case study of spike data illustrates that this method...