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23 August, 12:35

Suppose that you are asked if there would be a strong or weak correlation between the number of people shopping in malls and the approach of the Holiday Season. Explain whether there would be a strong or weak correlation and the difference between the two.

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  1. 23 August, 12:56
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    Most likely, there would be a strong correlation between the two.

    A correlation is a measurement of the relationship between two variables. When two variables are strongly correlated, this means that a change in one variable has a strong impact on the other one. On the other hand, when the correlation between variables is weak, this means that the two variables are not strongly connected. In this example, the two situations are likely to be strongly correlated because the number of people is very likely to go up as the holiday season approaches.
  2. 23 August, 13:00
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    There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.

    It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.

    Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.

    This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.

    There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation

    A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.

    When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero
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