Organizing and Describing Data
Statistics & Risk Management
Organizing and Describing Data
Statistics & Risk Management
By the year 2020, there will be 15 people aged 65 and over for every new baby born.
25% of all home accidents occur in the bathroom.
There is a 70% chance that an adult between 18 and 22 will be paroled from prison only to be returned to prison for another serious crime.
15% of smokers develop lung cancer.
While you are sitting here viewing this lesson, there is a 0.83% chance that your car will be stolen, but don't run outside because there is a 0.011% that you would be hit by another car.
Whether we realize it or not, we are exposed to statistics
every day. While the above examples aren't exactly good news, there is a silver lining. You don't have to be mathematician to understand what they mean!
The general field of statistics is fairly new (only about 300 years old). However, that doesn't mean that people didn't find ways to express what we know about probability in games of chance. In fact, it's well known that early Romans would bet on their favored gladiator based on his previous performances. Granted the probabilities were less precise values since, unlike today's modern gladiators, you could only lose once.
However, having a field of study does not guarantee that people will study it or even pay attention to it. Many of us still choose to trust in blind luck, rather than paying attention to probabilities. How often have you heard "Why should I worry about getting cancer from smoking (15% chance) when I may get hit by a car tomorrow?" (.011% chance). Looking at the probability of both events, the answer becomes quite obvious.
So where and when did we finally develop an interest in statistics? Oddly enough, around the mid 1600's Chevalier de Mere was interested in knowing why he lost at craps so often.
Was it bad luck, or the product of unrealistic expectations of winning? To understand this he turned to Pascal, later to be titled the father of probability theory. Long story short, he was making bad bets. Fast forward to 1908 and we have William Gosset's discovery of the standard error of the mean, a key concept to most of our analyses, while working for the Guinness brewery. So the turning point in the study of statistics came from gambling and beer. Hopefully this takes away some of your nervousness.
So what do you gain from a course in statistics? Statistics, like those we started with, are commonplace in today's world. You hear them on the news, you hear them on the radio, and you read them in the paper. If you plan to understand research at it's source, rather than listening to an incorrect translation from the cast of the Today Show, you should understand statistics. There have even been arguments made that studies of statistics lead to increases in reasoning ability. An idea demonstrated by Lehman in 1988.
The study of statistics involves math and relies upon calculations of numbers. But it also relies heavily on how the numbers are chosen and how the statistics are interpreted. For example, even when the numbers add up, the interpretation may be wrong. If nothing else, after going through this course you should be equipped to fight off some of the most common pieces of information shared in the media...bad statistics and even worse interpretations.
From now on your first reflex must be to question the statistics that you encounter. No longer will you blindly accept numbers or findings. Instead, you will begin to think about the numbers, their sources, and most importantly, the procedures used to generate them.
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