If intelligence and shoe size are positively correlated one can predict that as a foot increased in so does intelligence right
The correct answer and explanation is:
Correct Answer:
No, this statement is incorrect.
Even if intelligence and shoe size are positively correlated, it does not mean that an increase in shoe size causes an increase in intelligence.
Explanation (300 words):
Correlation refers to a relationship or association between two variables, but it does not imply causation. A positive correlation means that as one variable increases, the other tends to increase as well. In this case, the statement suggests that as shoe size increases, intelligence also increases. However, this doesn’t mean one causes the other.
This kind of correlation can occur because of a third variable influencing both factors. For example, during childhood development, both shoe size and intelligence tend to increase with age. A 5-year-old usually has smaller feet and a lower cognitive ability compared to a 15-year-old. So, when you measure intelligence and shoe size across a wide age group, a positive correlation might be found — but this is due to age, not because shoe size causes intelligence to grow.
If you compare shoe size and intelligence among adults, this correlation disappears because adults have reached full physical growth, and their shoe sizes remain stable while intelligence varies based on many complex factors like education, environment, genetics, and experience.
This example highlights a common mistake in interpreting statistical data — confusing correlation with causation. Just because two things occur together does not mean one causes the other.
In research and critical thinking, it’s important to look for underlying variables, control for age or other factors, and avoid drawing false conclusions. Using correlation alone to make predictions or assumptions can be misleading and unscientific.
So, while the numbers might show a relationship, we must understand why that relationship exists before making any claims or predictions. In conclusion, correlation does not equal causation — a key principle in statistics and scientific reasoning.