Reading a Picture

Visual storytelling

Visualising data helps understanding facts.
Sometimes it’s very easy to understand a graph; sometimes it’s necessary to read it and to study it to discover unknown territory.

Such graphs are little masterpieces. Here’s one of these and I am sure the authors had more than one iteration and discussion while creating it.
The graph tells the story of the average disposable income and savings of households in Switzerland, published by the Swiss Federal Statistical Office FSO.

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The authors kindly give a short explanation:

How to read this graph.
In one-person households aged 64 or under, the upper-income group has a disposable income of CHF 8487 per month and savings of CHF 2758 per month. Representing 4.0% of all households, this income group corresponds to a fifth of one-person households aged 64 or under (20.1%)

There’s another nice graph, a little bit less elaborated, also explained by the authors:

snip-povertyrates

Statistics ♥

But there’s one thing that is not explained:

snip_poverty-cithe confidence interval!

‘A confidence interval gives an estimated range of values which is likely to include an unknown population parameter, the estimated range being calculated from a given set of sample data,‘ and the above poverty data are from a sample of ‘approximately 7000 households, i.e. more than 17,000 persons who are randomly selected…’.
Or:
The confidence intervals for the mean give us a range of values around the mean where we expect the “true” (population) mean is located (with a given level of certainty, see also Elementary Concepts). ….. as we all know from the weather forecast, the more “vague” the prediction (i.e., wider the confidence interval), the more likely it will materialize. Note that the width of the confidence interval depends on the sample size and on the variation of data values…..’

Khan Academy gives lectures about topics like confidence intervals, sampling, etc.

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Which one ?

The above graphs use just one of multiple possibilities for visualising data.

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Severino Ribecca’s Data Visualisation Catalogue is one of many websites trying to give an overview. And there’s the risk to get lost in these compilations.

snip_swimring                            © listverse.com
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Optimism with Data

What will our future be like? Is there no or some hope that things evolve in a good direction? Will we make progress?

Data play a crucial role in answering these questions.

Steven Pinker (Harvard University, Department of Psychology) in his answer to the EDGE question of 2016 considers that Quantifying Human Progress is the most interesting recent (scientific) news:

But the most interesting news is that the quantification of life has been extended to the biggest question of all: Have we made progress? Have the collective strivings of the human race against entropy and the nastier edges of evolution succeeded in improving the human condition?’

‘Human intuition is a notoriously poor guide to reality. …. But the cognitive and data revolutions warn us not to base our assessment of anything on subjective impressions or cherry-picked incidents. As long as bad things haven’t vanished altogether, there will always be enough to fill the news, and people will intuit that the world is falling apart. The only way to circumvent this illusion is to plot the incidence of good and bad things over time. Most people agree that life is better than death, health better than disease, prosperity better than poverty, knowledge better than ignorance, peace better than war, safety better than violence, freedom better than coercion. That gives us a set of yardsticks by which we can measure whether progress has actually occurred.

The interesting news is that the answer is mostly “yes.” …. Economic historians and development scholars (including Gregory Clark, Angus Deaton, Charles Kenny, and Steven Radelet) have plotted the growth of prosperity in their data-rich books, and the case has been made even more vividly in websites with innovative graphics such as Hans Rosling’s Gapminder, Max Roser’s Our World in Data, and Marian Tupy’s HumanProgress.’

What may be true for the world must not be true for the individuals.
Let’s have a look at these mostly well-known data sites:

Max Roser: Our World in Data

‘Max Roser is the founder of OurWorldInData. He is an economist working at the University of Oxford. His background is in economics, geoscience and philosophy. His research is focusing on the long-term growth and distribution of living standards.’

‘On my website I am presenting the long-term data on how we are changing our world. The idea is to tell the history of our present world – based on empirical data and visualised in graphs.’

snip_worldindata-about-method

‘Most of the long-run trends are positive and paint an optimistic view of our world. Topic by topic, the empirical view of our world shows how the Enlightenment continues to make our world a better place. It chronicles how we are becoming less violent and increasingly more tolerant. The data displays how new ideas continue to improve living standards, allowing us to live a healthier, richer and happier life. It is the story of declining poverty and better food provision in a world we care about.

The empirical view on our world shows how misplaced doom and defeatism is and my aim is to encourage those who work to make our world a better place still. At the same time my hope is also to help to change the mind of those of you who do not think that we are creating a better world. By looking at the empirical data I want to explain why I am optimistic about how we are changing our world and why I think it is worthwhile to engage in the global long-term project of Enlightenment. Although most trends are clearly going in the right direction I also show where this is not the case. In a world of hysteria we cannot focus on what is important, but a fact based view on our world should help us to focus on the topics that are most important.’  http://ourworldindata.org/about/

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Human Progress.org

Human Progress’ mission statement (http://humanprogress.org/about):

‘Evidence from academic institutions and international organizations shows dramatic improvements in human well-being. These improvements are especially striking in the developing world.
Unfortunately, there is often a wide gap between the reality and public perception, including that of many policymakers, scholars in unrelated fields, and intelligent lay persons. To make matters worse, the media emphasizes bad news, while ignoring many positive long-term trends.

We hope to help in correcting misperceptions regarding the state of humanity through the presentation of empirical data that focuses on long-term developments. All of our wide-ranging data comes from third parties, including the World Bank, the OECD, the Eurostat, and the United Nations. By putting together this comprehensive data in an accessible way, our goal is to provide a useful resource for scholars, journalists, students, and the general public.

While we think that policies and institutions compatible with freedom and openness are important factors in promoting human progress, we let the evidence speak for itself. We hope that this website leads to a greater appreciation of the improving state of the world and stimulates an intelligent debate on the drivers of human progress.

Note: HumanProgress.org is a project of the Cato Institute with major support from the John Templeton Foundation, the Searle Freedom Trust, the Brinson Foundation and the Dian Graves Owen Foundation.’

Some data:

snip_humanprogress-infographics.

Gapminder

And here is top-star Hans Rosling with his gapminder.org where he deconstructs misleading, ’60-years-behind-reality’ opinions with data.

An example: Hans Rosling asks: Has the UN gone mad?

‘The United Nations just announced their boldest goal ever: To eradicate extreme poverty for all people everywhere, already by 2030.
Looking at the realities of extremely poor people the goal seems impossible. The rains didn’t fall in Malawi this year. The poor farmers Dunstar & Jenet, gather a tiny maize harvest in a small pile on the ground outside their mud hut. But Dunstar & Jenet know exactly what they need to break the vicious circle of poverty. And Hans Rosling shows how billions of people have already managed. This year’s “hunger season” may very well be Dunster’s & Jenet’s last.
Up-to-date statistics show that recent global progress is ‘the greatest story of our time – possibly the greatest story in all of human history. The goal seems unrealistic to many highly educated people because their worldview is lagging 60 years behind reality.’

snip_roslingpoverty

snip_gapminder-panic

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A focussed view: OXFAM’s new study

‘An Economy for the 1%

 Runaway inequality has created a world where 62 people own as much wealth as the poorest half of the world’s population – a figure that has fallen from 388 just five years ago, according to an Oxfam report published on January 18th.
How pivilege and power in the economy drive extreme inequality and how this can  be stopped. The global inequality crisis is reaching new extremes.The richest 1%now have more wealth than the rest of the world combined.
Power and privilege is being used to skew the economic system to increase the gap between the richest and the rest. A global network of tax havens further enables the richest individuals to hide $7.6 trillion.’ -> Methodology
snip-oxfam2016
OXFAM’s conclusion:
‘The fight against poverty will not be won until the inequality crisis is tackled.’

Income distribution. Data on Max Roser

snip_wealt-roser
‘A lesson that that we can take away from this empirical research is that political forces at work on the national level are possibly important for how incomes are distributed. If there was a universal trend towards more inequality it would be in line with the notion that inequality is determined by global market forces and technological progress where it is very hard (or for other reasons undesirable) to change the forces that lead to higher inequality. Inequality would then be inevitable. The reality of different inequality trends within countries suggests that the institutional and political framework in different countries play a role in shaping inequality of incomes.’

 

 

 

 

Data2Life

‘Better Data. Better Lives’ is a very well made video about the role of statistics. Everybody agrees that data are necessary for evidence based decisions and progress. But all communication work has to deal with the problem that striking examples demonstrating this connection are not easy to be presented. Perhaps in the next video? 😉

Broader Measures

The 46th session of the United Nations Statistcal Commission from 3 to 6 March 2015 at UN Headquarters in New York will deal with a report on broader (and better) measures of progress. This ‘report presents a roadmap for the development and implementation of an indicator and monitoring framework for the post-2015 development agenda. In particular the report discusses the development of the post-2015 indicator framework.’

It’s high time to demystify

Data, Big Data, Data Scientist, Data Mining …. Statistics. And next: Linked Open Data?

Look at this semantically rich clearing process by Diego Kuonen. It’s worth while!

 

 

See also: https://blogstats.wordpress.com/2013/04/21/big-data-open-data-and-official-statistics/