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TRANSCRIPT
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Writing Statistics:Relevant parameters for
highlighting in the article/report
CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION
Iraj NamdarianLuxumbourg – 15/01/2015
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2. Relevant parameters for highlighting in the article/report:
1 Principles of Media Objectivity2 Making Data Meaningful (writing stories
about numbers) 3 Visual elements4 Review and discussion about some
international Official Statistics2
Session overview
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“If it is not right do not do it; if it is not true do not say it.”
― Marcus Aurelius, Meditations
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Media Objectivity:• People's right to true information• Dedication to objective reality• Social responsibility• Professional integrity• Public access and participation
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Media Objectivity:• Respect for privacy and human dignity• Respect for public interest• Respect for universal values and diversity
of cultures• Principles of freedom in the honest
collection and publication of news, and of the right of fair comment and criticism
• Respect for truth and for the right of the public to truth 5
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Making Data Meaningful:
How to write a statistical story• Statistical offices have an
obligation to make the data they collect useful to the public.
• Stories get people interested in statistical information and help them to understand what the information means in their lives.
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2.2 Making Data Meaningful:
How to write a statistical story• After they read good statistical stories,
people should feel wiser and informed, not confused.
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Making Data Meaningful:
How to write a statistical story• A statistical story must be based on
sufficient knowledge of the data and the phenomenon under study.
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Making Data Meaningful:
How to write a statistical story• When preparing a statistical story, you
must also remember the European Statistics Code of Practice: (http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=KS-32-11-955)
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Making Data Meaningful:
How to write a statistical storyFundamental Principles of Official Statistics:• Impartiality;• Professionalism;• Metadata;
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Making Data Meaningful:
How to write a statistical storyFundamental Principles of Official Statistics:• Comment on erroneous interpretation;• Diverse sources;• Confidentiality;• Transparency;
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Making Data Meaningful:
How to write a statistical storyFundamental Principles of Official Statistics:• National coordination;• International standards;• International cooperation.
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Making Data Meaningful:
Possible topics/themes for stories:• Current interest (policy agenda, media coverage, etc.)• Reference to everyday life (food prices, health, etc.)
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Making Data Meaningful:
Possible topics/themes for stories:• Reference to a particular group (teens, women, the elderly, etc.)• Personal experiences (transportation, education, etc.)
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Making Data Meaningful:
Possible topics/themes for stories:• Holidays (Labour Day, Christmas, etc.)• Current events (statistics on a topic frequently in the news)
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Making Data Meaningful:
Possible topics/themes for stories:• A regular series (“This is the way we live now”, “Spotlight on xxxx”, etc.)• Calendar themes (spring, summer, etc.)• New findings
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Making Data Meaningful:
Write like a journalist - The “inverted pyramid”:Journalists use the “inverted pyramid” style. Conclusions at the top of the news story, and followed with secondary points in order of decreasing importance throughout the text.
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Making Data Meaningful:
Some tips for clear writing:• Use short sentences;• Aim for one idea per sentence;• Break up long sentences;
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Making Data Meaningful:
Some tips for clear writing:• Start each paragraph with the most
important message;• Keep paragraphs short;• Keep your writing crisp.
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Making Data Meaningful:
The lead: Your first paragraph The first paragraph, or lead, is the most important element of the story. The lead not only has to grab the reader’s attention and draw him or her into the story, but it also has to capture the general message of the data.
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Making Data Meaningful:
The lead: Your first paragraph • The Lead should not summarise the whole
report. • The Lead provides the most important and
interesting facts. • The Lead should not be packed with
assumptions, explanations of methodology or information on how the data have been collected.
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Making Data Meaningful:
Tips for Writing a Lead• Brevity: Leads are often short and
concise. • Specificity: A lead should be as specific
as possible. • Active sentences: Strong verbs will
make the Lead lively and interesting.25
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Making Data Meaningful:
Tips for Writing a Lead• Audience and context: Taking into
account what the reader already knows.In today’s media culture, most readers become aware of breaking news as it happens.
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Making Data Meaningful:
Tips for Writing a Lead• Focus on one or two findings• Write in everyday language (the “popular
science” level)• Create images for your readers• Focus on the things you want readers to
remember.27
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Making Data Meaningful:
Tips for Writing a LeadWhat to Avoid:• Flowery language: overuse of adverbs
and adjectives in the leads.• Unnecessary words or phrases:
(unintentional) redundancy. For example, 2 p.m. Wednesday afternoon
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Making Data Meaningful:
Tips for Writing a LeadWhat to Avoid:• Formulaic leads: Readers want
information, but they also want to be entertained.
• The lead must sound genuine, not merely mechanical.
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Making Data Meaningful:
Tips for Writing a LeadWhat to Avoid:• It: Most editors frown on leads that begin
with the word “it” because it is not precise and disorients the reader.
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Making Data Meaningful:
Good writing techniques • Terms meaningful to an economist may be
foreign to a layperson, so avoid jargon. • Use everyday language as much as
possible.• If you have to use difficult terms or
acronyms, you should explain them the first time they are used.
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Making Data Meaningful:
Good writing techniques • Large numbers are difficult to grasp. Use
the words millions, billions or trillions. Instead of 3,657,218, write “about 3.7 million.” You can also make data simpler and more comprehensible by using rates, such as per capita or per square mile.
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Making Data Meaningful:
Good writing techniques Use:• Language that people understand;• Short sentences, short paragraphs;• One main idea per paragraph;• Subheadings to guide the reader’s eye;
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Making Data Meaningful:
Good writing techniques Use:• Simple language: “Get,” not “acquire.”
“About,” not “approximately.” “Same,” not “identical”;
• Bulleted lists for easy scanning;
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Making Data Meaningful:
Good writing techniques Use:• A good editor. Go beyond Spell-Check; ask
a colleague to read your article;• Active voice. “We found that…” Not: “It
was found that....”;
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Making Data Meaningful:
Good writing techniques Use:• Numbers in a consistent fashion: For
example, choose 20 or twenty, and stick with your choice;
• Rounded numbers (both long decimals and big numbers);
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Making Data Meaningful:
Good writing techniques Use:• Embedded quotes (these are sentences
that generally explain “how” or “why”, and which journalists like to use verbatim in their news stories in quotes);
• URLs, or electronic links, to provide your reader with a full report containing further information. 37
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Making Data Meaningful:
Good writing techniques Avoid:• “Elevator statistics”: This went up, this
went down, this went up;• Jargon and technical terms;• Not explained Acronyms;
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Making Data Meaningful:
Good writing techniques Avoid:• All capital letters and all italics: Mixed
upper and lower case is easier to read;• “Table reading”, that is, describing every
cell of a complex table in your text.
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Making Data Meaningful:
Make the numbers “stick” • Numbers don’t “talk”. But they should
communicate a message, effectively and clearly.
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• How well they do this depends a lot on how well authors use numbers in their text.
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Making Data Meaningful:
Make the numbers “stick” • In a sense, journalists and statisticians are
from two cultures. They tend not to talk the same language.
• Journalists communicate with words; statisticians communicate with numbers.
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Making Data Meaningful:
Some suggestions for making the data“stick”:• Don’t peel the onion. Get to the point • Avoid proportions in brackets• Avoid changing denominators• Reduce big numbers to understandable
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Making Data Meaningful:
Visual elementsOne of the best techniques for understanding data is to visualize the numbers as a picture.
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Making Data Meaningful:
The target group: different forms of presentation may be needed for different audiences (e.g. business or academia, specialists or the general population).
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Tips about visual presentations:
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Making Data Meaningful:
The role of the graphic in the overall presentation: analysing the big picture or focusing attention on key points may require different types of visual presentations.
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Tips about visual presentations:
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Making Data Meaningful:
How and where the message will be presented: a long, detailed analysis or a quick slideshow.
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Tips about visual presentations:
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Making Data Meaningful:
Contextual issues that may distort understanding: expert or novice data user.
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Tips about visual presentations:
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Making Data Meaningful:
Whether textual analysis or a data table would be a better solution.
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Tips about visual presentations:
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Making Data Meaningful:
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Tables:Five support components are needed to describe the data displayed in a table:
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Making Data Meaningful:
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Charts:Statistics can often be better understood when they are presented in a chart than in a table.A chart is a visual representation of statistical data, in which the data arerepresented by symbols such as bars or lines.
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Making Data Meaningful:
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Charts:Charts can be used to illustrate patterns in a large amount of data or tocommunicate a key finding or message.
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Making Data Meaningful:
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Charts:You should consider using charts if youwant to show:• Comparison: How much? Which item is
bigger or smaller?• Changes over time:
How does a variable evolve?
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Making Data Meaningful:
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Charts:You should consider using charts if youwant to show:• Frequency distribution: How are the
items distributed? What are the differences?
• Correlation: Are two variables linked?• Relative share of a whole: How does
one item compare to the total?
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Making Data Meaningful:
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A good chart:• grabs the reader’s attention;• presents the information simply,
clearly and accurately;• does not mislead;
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Making Data Meaningful:
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A good chart:• displays the data in a concentrated way
(e.g. one line chart instead of many pie charts);
• facilitates data comparison and highlights trends and differences;
• illustrates messages, themes or storylines in the accompanying text.
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Making Data Meaningful:
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Reconsider using charts when data:• are very dispersed;• have too few values;• have too many values;• show little or no variation.
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Making Data Meaningful:
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BAD EXAMPLE GOOD EXAMPLE
All components have maximum impact. The result is a busy chart, difficult to read, even though it shows only three values.
This chart is much easier to read. Minimal use of support components ensures that datatake centre stage.