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KU Correlation Causation and Regression Discussion

KU Correlation Causation and Regression Discussion

Description

part 1 Choose two of the following three questions and post your answers:

1. In your own words, what is meant by the statement that correlation does not imply causality?
2. In your own words, please describe the difference between the regression equation y-hat and the regression equationBetaReg .
3. Values of r: If you had computed the value of the linear correlation coefficient to be 1.200, what should you conclude?

Part 2 respond to two peers

Peer 1

  1. Correlation does not imply causality.

-Where there is causation, there is a correlation, but also a sequence in time from cause to effect, a plausible mechanism, and sometimes common and intermediate causes. While correlation is often used when inferring causation because it is a necessary condition, it is not a sufficient condition.

Of course, circumstances can be that straightforward occasionally, but assuming that they are is never a good idea because you will often jump to the wrong conclusions.

*Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. For any two correlated events, A and B, their possible relationships include:

-A causes B (direct causation)

-B causes A (reverse causation)

-A and B are both caused by C

-A causes B and B causes A (bidirectional or cyclic causation)

-There is no connection between A and B; the correlation is a coincidence.

Just because correlation is evident, that doesn’t mean that A causes B. In statistics, it’s a logical fallacy to suggest that correlation proves causation, and no one will take you seriously if your research falls into this trap.

There are many variables that must be examined when looking at the relationship between two events. You will usually find other factors that have an impact, and it might be these factors that are responsible for the correlation

.Peer 2 1.Connection implies the coordination between two factors with which they move together. Then again, causality implies circumstances and logical results connection between two factors. Presently, regardless of whether the two factors are moving together that doesn’t imply that one variable might cause the other.

That implies, assuming that we work out relationship between’s two factors utilizing a couple of information we will get the worth however it doesn’t demonstrate that both the factors are connected with one another, they can be free factors

3.The correlation coefficient cannot be 1.2, it can be inferred.

An algebraic expression is what?

A combination of terms that are both variables and constants makes up an algebraic expression.


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