Sources

Many of the information we are daily given include affirmations stating something cathegoric about the world or about something we are interested in. We are told that unemployment here and there is currently at x%, that the sales of this company have changed in x%, education levels have dropped or gone up, the success rate of this is x%, X out of Y people who did thsi diet lost weight and so on. Many of these things aren't presented as an opinion, but as facts. Facts are good, I'm okay with facts, but what's puzzling for me is how this information lacks entirely of very important elements to sustain their credibility, namely sources and details.

More decent, respectable newspapers and magazines (which naturally don't include fashion magazines), tend to add some detail by explaining the period to which the data apply, and also the place, like "Last quarter's inflation rate", or "Number of iPads sold last month in New York", but these are not the most of cases, and these also often lack the source. The idea of it should be that if you follow the source, you can get the same result they did. If you can follow the source, test the reliability of the source, and get the same results, you can then trust on the rest of the message.

People normally don't think about it and thus don't realize when they are being manipulated. Numbers and relations are thrown around to impress you, to put pressure on you, to make you lean this or that way so you make a decision that others want you to make while feeling you are actually deciding on your own based on facts.

When you are presented with these "facts", always look for the following information: which is the source? What's the institution that gathered up the data? It's not the same if it was gathered by some no-name little company or a respectable university. Consider the source and don't be wooed by the name, as many companies have been "bought" by different branches or parties to say what they want to hear. If you haven't heard about it, start by doubting all data and those dishing it like truth, until you have researched the organization.

It would be nice to know how the information was gathered, as there is a chance to guide the people interviewed, if the information comes from an interview, BUT when the information comes from databasis - say the sales of iPads - you could technically ask what are the paramethers they are using. For instance, it's not the same looking for the sales of the iPads while completely disregarding the number of iPads returned because the buyer changed their minds or because there was a problem with them. It could be a mistake also to consider for sold iPads the number of iPads out of the inventory, because maybe some were lost, stolen or returned and dumped because they were faulty. See what I mean? Ask for the paramethers. In a broader scope, it's not the same to count as unemployed the people who stay at home because they don't want to work, or choose to take care of the home, their family and so on, or students who are in age of working but instead are studying, as it is not acurate either to count only as unemployed the people who recently have been fired and not those who have been looking for a job for a while, or those who got out of school and started looking for it. One way yields a bigger number and another yields a smaller number.

The next thing you need to know about a number is when was the measure done. Many are not above using old data - more in line with what they want to say - than fresher numbers that could cross over their plans. It's not the same using the data of sales of iPhones before Samsung Galaxy than after, if you want to prove how many high are the sales. The period is also important, as it's not the same to use the sales of a year, the sales of a month or those accumulated up to this moment.

Finally there's location. For instance, when you talk about the number of schools that have computer labs for children, it isn't the same to take only the schools in good parts of the metropolis, or the schools in rural areas.

If the data give is incomplete or you can't pose this questions and have them replied to your satisfaction - and here dare to be petty and ask until they are blue in the face and PROVE to you that what they say is right - then distrust. If data is peppered around, and there's no depth in it, no analyzing, but rather it seems like a display of how much they know - distrust. Those numbers and "facts" are being used to distract you, to impress you, to get you emotionally while tricking your reason.

When you become aware of data and its proper use, you will most likely be astonished at the many times it is abused of, and used for manipulation. Yes, often even in the most serious circumstances, and from people who should be sound, these mistakes push out and flap around impressing others. But not you. Once you become aware of data, the hardest part starts: how to fiend it off and how to work around it, explaining people why "just because you said so" doesn't make the data acceptable and proved safe to be used.

Good luck!