How would you respond to the following? The statement \"Correlation means causat

Question

How would you respond to the following?

The statement "Correlation means causation" is false. I state that fact because the correlation may imply a connection between the two variables but that does not mean it implies to causation. The influence of other variables must be taken into account before indicating a causation in regard to the correlation of statistics. It ultimately depends more on the design of the study or experiment rather than the data itself. Correlation doesn't equate with causation. Causation can only be established by a well-designed and carried out experiment making use of random subjects. But still there will be some degree of uncertainty due to the variables that are unknown or cant be controlled.

An increase in education by one year is predicted to reduce sleep by 11.13 minutes per week. In this case, work is negatively related to sleep thus a person who has chosen work more will have little minutes to sleep per week. If other factors were the same or held constant, the increase to work by one minute will reduce sleep 0.15 minutes per week.

Explanation / Answer

As mentioned in the above statement "Correlation means causation" is false. An increase in education by one year is predicted to reduce sleep by 11.13 minutes per week. It does not indicate any other factor or activities that a person performs in a day. This statement may be tempting as it assume that one variable ( education) causes the other (sleep). Now one Correlation that we can generate is perhaps more educated individual have jobs that require longer hours

Again in the statement that the increase to work by one minute will reduce sleep 0.15 minutes per week, we can not determine whether they are related or not. It is mentioned that all the other variables are constant. If we consider average sleeping time is between 7 to 9. Which means if a person works 1 hour extra then the sleep time will reduce by 9 minutes.

Biddle and Hamermesh (1990) built multiple regression models to study the tradeoff between time spent in sleeping and working and to look at other factors affecting sleep:

Sleep = ?0 + ?1 total work + ?2 education + ?3 age + ?

Where sleep and total work are measured in minutes per week and education and age are measured in years. Suppose the following equation is estimated:

Sleep = 3500 – 0.15 total work – 11.20 education + 2.29 age + ?

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