Correlation in Variables
Undoubtedly, a correlation between two variables does not imply that the effect in one variable will cause a change in another variable. This is because causation designates that one event is the outcome of the occurrence of or effect of another variable. Therefore, this can mean there is a causal association between the two dealings. Alternatively, it could result from random chance, where the variable seems related but has no true underlying relationship (Bluman, 2018). Another option would be that there might be an additional lurking variable, making the connection look weaker than it truly is. This confirms that correlations can never confirm causation. For instance, with two variables like income earned and hours worked, there is only an association between these two when the rise in hours people worked is connected with a rise in income received. Without this, there is no correlation. Therefore, correlation is a mathematical measure conveyed as a numeral defining the route and magnitude of an association between two or more variables. In contrast, causation shows that a single occurrence is the outcome of the effect of the other occurrence (Bluman, 2018). Nonetheless, a correlation between variables never implies that a single variable’s effect or change is the reason for the change in another variable.
References
Bluman, Alan. (2018). Elementary statistics: A step by step approach (10th ed.). New York: McGraw-Hill Education. ISBN: 978-1-259-75533-0.
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Question 
If you were asked to explain statistical hypotheses testing to a group of high school seniors taking AP Statistics, how would you explain this concept using what you learned from the video?
Correlation in Variables
DISCUSSION TWO
In your opinion, when two variables are correlated, can a researcher be sure that one variable causes the effect of the other? Explain your response.
PLEASE ANSWER EACH DISCUSSION. THIS ASSIGNMENT SHOULD NOT EXCEED ONE PAGE. HALF PAGE FOR EACH PART
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