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# Causes and Effects Help

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## Introduction to Causes and Effects

When two things are correlated, it's tempting to think that there is a cause-and- effect relationship involved. Examples abound; anyone who listens to the radio, reads newspapers, or watches television these days can't escape them. Sometimes the cause–effect relationships aren't directly stated, but only implied. ''Take this pill and you'll be happy all the time. Avoid these foods and you won't die of a heart attack.''

Some of the cause–effect blurbs we hear every day must sound ridiculous to people who have grown up in cultures radically different from ours. ''Drink this fizzy liquid and you'll never get dirt under your fingernails. Eat this creamy white stuff and the hair on your ears will go away.'' The implication is always the same. ''Do something that causes certain people to make a profit, and your life will improve.'' Sometimes there really is a cause– effect relationship. Sometimes there isn't. Often, we don't know.

## Correlation and Causation

Let's boil down a correlation situation to generic terms. That way, we won't be biased (or deluded) into inferring causation. Suppose two phenomena, called X and Y, vary in intensity with time. Figure 7-4 shows a relative graph of the variations in both phenomena. The phenomena change in a manner that is positively correlated. When X increases, so does Y, in general. When Y decreases, so does X, in general.

Is causation involved in the situation shown by Fig. 7-4? Maybe! There are four possible ways that causation can exist. But perhaps there is no cause-and-effect relationship. Maybe Fig. 7-4 shows a coincidence. If there were 1000 points on each plot, there would be a better case for causation. As it is, there are only 12 points on each plot. It is possible these points represent a ''freak scenario.'' There is also a more sinister possibility: The 12 points in each plot of Fig. 7-4 might have been selected by someone with a vested interest in the outcome of the analysis.

When we assign real phenomena or observations to the variables in a graph such as Fig. 7-4, we can get ideas about causation. But these ideas are not necessarily always right. In fact, intense debate often takes place in scientific, political, and even religious circles concerning whether or not a correlation between two things is the result of cause-and-effect, and if so, how the cause-and-effect actually operates. And how do we know that the data itself is not biased?

In the examples that follow, we'll rule out the bias factor and assume that all data has been obtained with the intent of pursuing truth. There are myriad ways in which data can be warped and rigged to distort or cover up truth, but we'll let sociologists, psychologists, and criminologists worry about that.

## X causes Y

Cause-and-effect relationships can be illustrated using arrows. Figure 7-5A shows the situation where changes in phenomenon X directly cause changes in phenomenon Y. You can doubtless think of some scenarios. Here's a good real-life example.

Fig. 7-5A. At A, X causes Y.

Suppose the independent variable, shown on the horizontal axis in Fig. 7-4, is the time of day between sunrise and sunset.

Plot X shows the relative intensity of sunshine during this time period; plot Y shows the relative temperature over that same period of time. We can argue that the brilliance of the sunshine causes the changes in temperature. There is some time lag in the temperature function; this is to be expected. The hottest part of the day is usually a little later than the time when the sunshine is most direct.

It's harder to believe that there's a cause-and-effect relationship in the other direction. It is silly to suggest that temperature changes cause differences in the brilliance of the sunlight reaching the earth's surface. Isn't it? Maybe, but maybe not. Suppose heating causes the clouds to clear, resulting in more sunlight reaching the surface (Y causes X). Maybe there's something to this sort of argument, but most meteorologists would say that the former relation better represents reality. Bright sunshine heats things up. That's obvious.

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