
To find: for a given set of data, why does

Answer to Problem 8SGR
For observational data, correlations can't confirm causation. Correlations between variables show us that there is a pattern in the data, which the variables we have tend to move together. However, correlations alone don't show us whether or not the data are moving together because one variable causes the other.
Explanation of Solution
Given information: correlation and causation.
Calculation:
Correlation is a statistical technique which tells us how strongly the pair of variables are linearly related and change together. It does not tell us why and how behind the relationship but it just says the relationship exists.
Example: Correlation between Ice cream sales and sunglasses sold.As the sales of ice creams is increasing so do the sales of sunglasses.Causation takes a step further than correlation. It says any change in the value of one variable will cause a change in the value of another variable, which means one variable makes other to happen. It is also referred as cause and effect.
Example: When a person is exercising then the amount of calories burning goes up every minute. Former is causing latter to happen.So now we know what correlation and causation is, it’s time to understand “Correlation does not imply causation!” with a famous example. Ice cream sales are correlated with homicides in New York (Study).As the sales of ice cream rise and fall, so do the number of homicides. Does the consumption of ice cream causing the death of the people?No. Two things are correlated doesn’t mean one causes other.Correlation does not mean causality or in our example, ice cream is not causing the death of people.When 2 unrelated things tied together, so these can be either bound by causality or correlation.
In Majority of the cases correlation, are just because of the coincidences. Just because it seems like one factor is influencing the other, it doesn’t mean that it’s actually does.
Chapter 4 Solutions
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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