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Introduction to Statistics: Help and Review9 chapters | 137 lessons

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Lesson Transcript

Instructor:
*Vanessa Botts*

In this lesson, you will learn about causation. In statistics, causation means that one thing will cause the other, which is why it is also referred to as cause and effect. When you are through, take a short quiz to test your understanding!

Let's say you have a job and get paid a certain rate per hour. The more hours you work, the more income you will earn, right? This means there is a relationship between the two events and also that a change in one event (hours worked) causes a change in the other (income). This is causation in action!

**Causation** indicates a relationship between two events where one event is affected by the other. In statistics, when the value of one event, or variable, increases or decreases as a result of other events, it is said there is causation.

Each of the events we just saw can also be considered variables, and as the amount of hours worked increases, so does the income earned. Conversely, if you work less hours, you would make less money. Determining causation is not always as easy as the work and income example we just explored. Let's dig into causation further and see how it can easily be misunderstood by taking a look at some other situations.

Some studies indicate that among students as their amount of hours of sleep per night increases so does their GPA (grade point average). This means that the longer students sleep each night, the higher their grades tend to be. Great! Now, all we need to do is sleep longer, and our grades will improve, right?

Unfortunately, it is not that simple. Although based on the study there is definitely a correlation between the two variables, there is no way to say with certainty that the increase in one variable is the definitive cause for the increase in the other.

There is a phrase that sums up what is often a source of confusion when determining statistical relationships: correlation does not mean causation. In the next section, we will see exactly what that means. So, let's take this situation further to determine if there may be some other variables at play that could explain the relationship between sleep and grades.

In the situation above, we saw a relationship between sleep and grades. Based on this, we may have inferred that more sleep will always result in higher grades or that there would be causation. However, there may be other variables at play that could account for why grades are higher for those who sleep longer: lurking variables. **Lurking variables** are variables that may not have been observed or accounted for in a study or experiment but that may have an effect on the results.

So, what are some possible lurking variables that may account for the higher grades? Well, maybe students who sleep longer happen to be more studious to begin with and therefore would get better grades no matter how much sleep they got. There is no way to know for sure what, if any, lurking variables may have been at play in the sleep study, but we definitely need to be careful not to confuse correlation with causation because they are not the same thing.

In this lesson, we have seen that **causation** states that a change in one event, or variable, will cause a change in the other. Causation is not to be confused with correlation, which shows a relationship between the events but does not explain why or how these events are related. Remember, this is due to **lurking variables**, or variables that may not have been observed or accounted for in a study or experiment but that may have an effect on the results.

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Introduction to Statistics: Help and Review9 chapters | 137 lessons

- Descriptive & Inferential Statistics: Definition, Differences & Examples 5:11
- Difference between Populations & Samples in Statistics 3:24
- Defining the Difference between Parameters & Statistics 5:18
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