# Example of reverse cause and effect relationship

### Examples for teaching: Correlation does not mean causation - Cross Validated

In statistics, many statistical tests calculate correlations between variables and when two variables are found to be correlated, it is tempting to assume that this shows that one variable causes the other. That "correlation proves causation" is considered a questionable cause Determining whether there is an actual cause-and-effect relationship. Reverse cause-and-effect relationships are when the dependent and independent For example, say a correlation exists between people's fitness level and the. It might be useful to explain that "causes" is an asymmetric relation (X causes Y is different from Y . (Which is the cause and which is the effect?) An example of " possible" reverse causality: Social drinking and earnings - drinkers earn more.

So you can create something right then and there that causes it, and thereby fills in that hole. Take Act One and do Reverse Cause and Effect for that act, stating the Object of the act, the Final Effect that demonstrates the Object on screen with real actors, the Immediate Cause of that effect, the cause of that and the cause of that, etc. You keep the unnecessary at bay, taking only what you need and incorporating it, so that you stay in control of the material as you develop it.

There are two-to-five sequences in an act. There are two-to-five scenes in each sequence. A scene is a complete story unit that may take place over a couple of different locations, so if your slug line changes from INT.

Now you do Reverse Cause and Effect for the first scene of the opening sequence. Now this scene will be tight, because you never allowed the unnecessary into it. So keep it tight. Sure, you need to be able to let the scene breathe and move, but keep it lean. Then this scene will be crisp and tight, and it will be part and parcel of a tight sequence, which is part of a tight act, which is part of a tight overall script.

You never let the unnecessary in. When a tailor is done making a suit, there is leftover cloth on the floor. He throws it away. Then you do Reverse Cause and Effect for the next scene, and then write it. By applying Reverse Cause and Effect to the whole script, then to each act, then to each sequence, and then to each scene you gradually assemble a script in which every part consists only of those actions that advance the plot.

By sticking with strict cause and effect, you continually eliminate the unnecessary, like a chemical process that expels undesired byproducts and retains only the desired pure product—in this case, clean, coherent, compelling, forward-moving dramatic action. Suppose we have three young teenagers, two 14 and one Their two fathers are mobsters who run a bookie joint together and the boys are expected to join the family business.

## Correlation does not imply causation

But they hate it and want to go to MIT to study robotics. Their dads are forcing them to be career criminals. They decide to rob the bookie joint to pay for college. They case the place, adding to what they already know about it. They create a plan. Things go wrong, but they manage to heist a huge sum of crooked money. They exit the building and vanish like ghosts.

## Lesson 3 – Cause and Effect Relationships

They get away clean with the money. They get outside and pull off a vanishing act. They launch their robbery, but things go wrong. They complete their plan. They case the joint and start planning. Their dads say the only way they can go to college is if they pay for it themselves.

The kids get furious. The dads insist that they forget their geek nonsense and join the family business. Image courtesy of MIT. Read it from the bottom up and you get the story. The kids refuse to be bookies and want to study robotics at MIT, but their dads insist they forget that crap and join the family business, which makes them furious. They case the operation and make a plan, then launch their robbery, but things go wrong. They get outside and vanish like ghosts.

They launch their robbery and things go wrong. Now we want to think it through in a little more detail, fleshing out the story a bit more. They disappear outside and create a distraction to lead the chase away. The boys point at where the getaway car went and angry mobsters race after it. They force their dads to pull out the cash and bag it up.

What if they had a hostage? They grab their grandfather and put a gun to his head. What would cause them to do this, since in their planning session they swore to not hurt any of their family? They demand the cash. They disarm him and get back to their robbery. How would they get the gun away from him? They will also need a voice-changing device so no one recognizes their voices. They create a distraction with a small hidden robot and then breech the door with a small explosion.

Having to continually find causes for events raises certain questions, the answers to which fill in the plot. Spurious relationship The third-cause fallacy also known as ignoring a common cause [6] or questionable cause [6] is a logical fallacy where a spurious relationship is confused for causation.

It is a variation on the post hoc ergo propter hoc fallacy and a member of the questionable cause group of fallacies. All of these examples deal with a lurking variablewhich is simply a hidden third variable that affects both causes of the correlation. Example 1 Sleeping with one's shoes on is strongly correlated with waking up with a headache. Therefore, sleeping with one's shoes on causes headache. The above example commits the correlation-implies-causation fallacy, as it prematurely concludes that sleeping with one's shoes on causes headache.

A more plausible explanation is that both are caused by a third factor, in this case going to bed drunkwhich thereby gives rise to a correlation. So the conclusion is false. Example 2 Young children who sleep with the light on are much more likely to develop myopia in later life.

### Reverse Cause and Effect

Therefore, sleeping with the light on causes myopia. This is a scientific example that resulted from a study at the University of Pennsylvania Medical Center. Published in the May 13, issue of Nature[7] the study received much coverage at the time in the popular press. It did find a strong link between parental myopia and the development of child myopia, also noting that myopic parents were more likely to leave a light on in their children's bedroom.

Example 3 As ice cream sales increase, the rate of drowning deaths increases sharply. Therefore, ice cream consumption causes drowning. This example fails to recognize the importance of time of year and temperature to ice cream sales.

Ice cream is sold during the hot summer months at a much greater rate than during colder times, and it is during these hot summer months that people are more likely to engage in activities involving water, such as swimming. The increased drowning deaths are simply caused by more exposure to water-based activities, not ice cream.

### Correlation does not imply causation - Wikipedia

The stated conclusion is false. This suggests a possible "third variable" problem, however, when three such closely related measures are found, it further suggests that each may have bidirectional tendencies see " bidirectional variable ", abovebeing a cluster of correlated values each influencing one another to some extent.

Therefore, the simple conclusion above may be false. Example 5 Since the s, both the atmospheric CO2 level and obesity levels have increased sharply. Hence, atmospheric CO2 causes obesity. Richer populations tend to eat more food and produce more CO2. Example 6 HDL "good" cholesterol is negatively correlated with incidence of heart attack.

Therefore, taking medication to raise HDL decreases the chance of having a heart attack. Further research [14] has called this conclusion into question. Instead, it may be that other underlying factors, like genes, diet and exercise, affect both HDL levels and the likelihood of having a heart attack; it is possible that medicines may affect the directly measurable factor, HDL levels, without affecting the chance of heart attack.

A causes B, and B causes A[ edit ] Causality is not necessarily one-way; in a predator-prey relationshippredator numbers affect prey numbers, but prey numbers, i. Another well-known example is that cyclists have a lower Body Mass Index than people who do not cycle.

This is often explained by assuming that cycling increases physical activity levels and therefore decreases BMI. Because results from prospective studies on people who increase their bicycle use show a smaller effect on BMI than cross-sectional studies, there may be some reverse causality as well i.

The more things are examined, the more likely it is that two unrelated variables will appear to be related. The result of the last home game by the Washington Redskins prior to the presidential election predicted the outcome of every presidential election from to inclusivedespite the fact that the outcomes of football games had nothing to do with the outcome of the popular election.

This streak was finally broken in or using an alternative formulation of the original rule.