1.3 Data Collection and Observational Studies
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? When we are interested in the effect one variable may have on another, we call the first variable the explanatory variable and the second the response variable. Questions like these are answered using studies and experiments. Proper study design ensures the production of reliable, accurate data.
Data Collection Methods
There are many ways data is commonly collected, each with their own advantages and disadvantages. Some ways data may be collected are:
The latter two options are more commonly accepted, but we will briefly describe the former first.
Anecdotal Evidence
Consider the following statements seemingly based on data:
- I met two students who took more than seven years to graduate from Duke, so it must take longer to graduate at Duke than at many other colleges.
- A man on the news had an adverse reaction to a vaccine, so it must be dangerous.
- My friend’s dad had a heart attack and died after they gave him a new heart disease drug, so the drug must not work.
Though each conclusion is technically based on data, there are two problems. First, the data in each example only represent one or two cases. Second, and more importantly, it is unclear whether these cases are actually representative of the population. Data collected in this haphazard fashion is called anecdotal evidence. While such evidence may be true and verifiable, be careful of data collected in this way since it may only represent extraordinary or unusual cases. Often, we are more likely to recall anecdotal evidence based on its striking characteristics. For instance, in Case #1 above, we are more likely to remember the two people we met who took seven years to graduate than the six others who graduated in four years. Instead of looking at the most unusual cases, we should examine a sample of many cases that represent the population.
Observational Studies
Researchers perform an observational study when they collect data in a way that does not directly interfere with how the data arises. For instance, researchers may collect information via a questionnaire or survey, review medical or company records, or follow a large group of similar individuals to form hypotheses about why certain diseases develop. In each of these situations, researchers merely observe the data that occurs. In general, observational studies can provide evidence of naturally occurring associations between variables, but they cannot by themselves show a causal connection. Why not? Consider the following example.
Suppose an observational study tracking sunscreen use and skin cancer found that the more sunscreen someone used, the more likely the person was to have skin cancer. Does this mean sunscreen causes skin cancer? Some previous research tells us that using sunscreen actually redu