Unscrambling information and removing opinions from data

By MUNGAI KIHANYA

The Sunday Nation

Nairobi,

06 January 2008

As the election results started streaming in on 27th December, the distinction between data and information became apparent. Throughout that evening, TV stations were posting the vote counts for the three main presidential candidates from various polling stations around the country.

For about three hours a lot of data from many polling stations was presented on the TV screens but the information within it was not given. That is, the total votes for each candidate, the leader so far, and by how much. This is what I (and probably everybody else) wanted to know – is my candidate leading or lagging.

Finally, when the information started coming through, it was in small portions – every half hour or so. I would have expected the media houses to add up the votes for each candidate and display the results (with some graphics) immediately after receiving the data from individual polling stations. Hopefully, they will remember to do that in 2012!

Weather reports on radio and TV also surfer same imbalance of data and information. It is common to hear the reporter saying that “tomorrow there will be light showers and a high of 19 degrees”.

The first part of that statement gives information without data and second one gives data without information. It leaves the listener / viewer wondering how light the showers will be and whether 19 degrees is hot or warm or cold.

Sometimes however, reporters give their opinion while attempting to provide information from data. Thus we hear (or read) about companies making “huge profits running to billions of shillings” or of politicians addressing “mammoth rallies estimated to be at least 10,000 people”.

 “Huge” and “mammoth” are opinions; they are not part of the data nor are they information. Think about it this way, a billion shillings is about 17 million dollars. In corporate USA, that cannot be described as “huge”. Similarly, 10,000 people are not a mammoth crowd; after all, the UK Premier League matches attract larger numbers than that – every week!

So, how can we distinguish amongst data, information and opinions? As demonstrated above, opinions can vary from one person to another. Data is invariant – that is, it remains the same regardless of the person collecting it. But the collection method must be reliable.

For example, metal objects feel colder than wooden ones. That does not mean that the metal is always at a lower temperature than the wood. It only feels colder because the method of measurement (touching) is unreliable.

Information is the interpretation of data. It was harmless, for example for the ECK to announce that Mwai Kibaki garnered 4,584,721 votes in the 2007 general elections against Raila Odinga’s 4,352,943. That is simply data. The information from the data was the declaration that Kibaki had won the contest.