I need a response to a coworker\'s discussion This is the discussion instruction

Question

I need a response to a coworker's discussion

This is the discussion instructions below

"Choose one of the following three questions and post your answer:

1. In your own words, what is meant by the statement that correlation does not imply causality (Section 10-2)?
2. In your own words, please describe the difference between the regression equation and the regression equation (Section 10-3).
3. A geneticist wants to develop a method for predicting the eye color of a baby, given the eye color of each parent. In your own words, can the methods of Section 10-5 be used? Why or why not?

Please respond to my discussion question by clicking on the Reply button after this section. When you reply to another student’s comments, click on Reply after their comments.

EXAMPLE:
Hello! I will take number 2. There can be a correlation between two items, for instance an increase in someone’s salary and purchasing clothing, but we cannot conclude that increases in someone’s salary causes an increase in purchasing clothing.

This is the discussion post I need a response to

Hi Class! I choose #1. What is meant by the statement is that just because two things occurred together doesn't mean that one caused the other. For example, if we used that heavier vehicles get less gas mileage and even though to some point it maybe true it might not be true for the whole world.

Explanation / Answer

1.) "Correlation does not apply causality"

Correlation is a property to define linear relationship between two variables, if that number is positive there is correlation.

Causation describes how much a variable affects the other one (Given that Y happened, what should we expect from X).

So, if the correlation of two variables (or data sets) is positive, it means that they both increase pseudo-proportionally (or decrease).

These are the four scenarios with an example of causation on two correlated variable :

One can cause the other (Ex: Salary Vs Expenses)

They can both cause one another (Ex. Fitness Vs athletic performance)

A third variable could cause both of them (Ex. Amount of snow vs flue cases)

it can be coincidence and there is no causation (Ex. Number of pirates vs Global warming).

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