I had an interesting text message from my cousin today. He was asking, ‘What is meant when a study is deemed to be flawed due to uncontrolled variables? i.e. what does it really mean to have uncontrolled variables?’
It’s an excellent question – and one that is well addressed in a book I recently recommended here called How to Lie With Statistics.
I gave him the following answer:
‘A simple example might be someone looking back through historical data and seeing that the number of cancer cases (of all kinds) has been on the sire over the past twenty years. In terms of absolute numbers, this is true. Some people use this to raise the alarm that we have to get more aggressive in our fight against cancer because it has become a leading killer. Perhaps that’s not a bad idea either, but if someone were to look more closely at the details they would quickly see that these absolute numbers aren’t the right data to make this conclusion by. There are uncontrolled variables.
The unaltered or crude cancer death rate per 100,000 US population for the year 1970 is 162.8. Multiply this rate by the US population of that year, 203,302,031 and divide by 100,000, we obtained the total cancer deaths of that year, 330,972. Divide this number by the number of days in a year, we obtain the average number of Americans who died of cancer in 1970 at 907.
Twenty years later, the unaltered cancer death rate for the year 1990 is 505,322, the total population, 248,709,873. The cancer death rate per 100,000 population rose to 203.2. The daily cancer death rate was 1384.