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There is a positive linear correlation between the number of daily customers wearing winter gloves and the number of cups of soup sold daily.

The scatterplot indicates that as the number of daily customers wearing winter gloves increases, the number of cups of soup sold also tends to increase, demonstrating a positive linear correlation.

A) There is a negative linear correlation between the number of daily customers wearing winter gloves and the number of cups of soup sold daily.

This statement is incorrect because a negative linear correlation would imply that as one variable increases, the other decreases. However, the scatterplot shows a direct relationship where both variables increase together, contradicting this option.

B) There is a positive linear correlation between the number of daily customers wearing winter gloves and the number of cups of soup sold daily.

This option accurately reflects the observed data in the scatterplot, which shows that higher numbers of customers wearing winter gloves correspond to higher sales of cups of soup. This indicates a clear positive relationship between the two variables.

C) There is no linear correlation between the number of daily customers wearing winter gloves and the number of cups of soup sold daily.

This statement is incorrect as the scatterplot does show a relationship between the two variables. A lack of correlation would suggest that the data points are scattered without any discernible pattern, which is not the case here.

D) An increase in the number of daily customers wearing winter gloves causes a decrease in the number of cups of soup sold daily.

This option is incorrect because it implies a negative effect, which contradicts the observed positive correlation in the scatterplot. The data does not support any causative decrease linked to the increase in customers.

E) An increase in the number of daily customers wearing winter gloves causes an increase in the number of cups of soup sold daily.

While this option suggests a positive relationship, it incorrectly states that there is a causative effect implied. Correlation does not equate to causation without further evidence.

Conclusion

The correct answer is option B, as it accurately describes the positive linear correlation observed in the scatterplot. Options A, C, D, and E fail to represent the data correctly, either by suggesting negative correlations or misrepresenting the nature of the relationship without sufficient evidence.