Answer:
A weak positive correlation
Explanation:
As the ages increase, the shoe sizes tend to increase slightly. This makes it a positive correlation.
However, when we graph the points, we see they are very scattered; they are not grouped in any manner. This means it is a very weak correlation.
The best description of the strength of the model is a weak positive correlation. Thus, option 'a' is correct.
The Correlation coefficient is a measure of how similar two datasets are acting. The range of correlation coefficient is [-1, 1]
• When the correlation coefficient comes out as -1, it means that both the datasets are negatively oppositely correlated. One data increases and other data starts to decrease in the opposite direction.
• When the correlation coefficient comes out below 0, values are negatively correlated.
• If the correlation coefficient comes out as 0, that means both the data sets are uncorrelated with respect to how we compare them.
• When the correlation coefficient comes out > 0, that means both datasets' values are positively correlated.
• If the correlation coefficient comes out as 1, then the values grow exactly similarly, in the same direction.
As per the two initial data points as the age of the women increases the shoe size must increase as well, but instead, in the third data point the size is reduced, further, for the fourth data point, the size is again increasing.
This indicates that age has to do nothing with the shoe size, or even if it is related the not a strong bond exists between the two therefore, the correlation is weak. Also, it can be observed that the overall graph of the data point is going towards the positive.
Hence, the best description of the strength of the model is a weak positive correlation. Thus, option 'a' is correct.
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