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Can you think of your own potentially "headline-catching" correlation that could be explained by a third factor? Tell a causal story that could be mistakenly attributed to correlational data.

Sagot :

  • "Correction is not causing" means that it would not necessarily be that the one causes another because two items are related.
  • A third factor that influences both can cause the correlation between two things.
  • This dull, hidden third wheel is referred to as a confounder.
  • Correlation means that two or more variables (such as ice cream consumption and crime) have to be linked, although this does not necessarily have any effects and causes.
  • If two variables are correlated, it just means that the other changes if one variable changes.
  • When using statistics called a coefficient of correlation, we may measure the connection.
  • A correlation coefficient is a number between -1 to +1 that shows the force and direction of a relationship between the variables.
  • In general, this correlation coefficient can be seen in the letter r.
  • The correlation coefficient number portion reflects the strength of the association.
  • The closer the figure is 1 (whether negative or positive), the stronger the factors are connected, therefore, as other variable changes become the more punctuate in a single variable.
  • The closer the number to null, the weaker and the less predictable the correlations between the variables.
  • For example, a correlation coefficient of 0.9 shows a much greater association than 0.3.
  • The correlation coefficient is 0 if the variables are non-related.
  • An example of two variables, which one may anticipate to have no link to each other, is the instance above concerning ice cream and crime.
  • The sign – positive or negative – specifies the direction of the connection.
  • If there is a positive correlation then the variables move in the same direction.
  • Another way of thinking is that another rises with one factor, as well as, the other lower with one variable.
  • The negative correlation suggests two variables move opposite.
  • If two variables are connected negatively, a reduction in one variable includes an increase in the other variable, conversely.

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