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Beverly did a study this past spring using data she collected from a cafeteria She recorded data weekly for ice cream sales and soda sales. Beverly found the line of best fit and the correlation coefficient, as shown in the diagram below.

a) Beverly's Cafeteria Study
b) Cans of Soda Solo
c) Ice Cream Bars Sold
Given this information, which statement(s) can
correctly be concluded?
I. Eating more ice cream causes a person to become thusty
II. Drinking more soda causes a person to become hungry m. There is a strong correlation between ice cream sales and soda sales.

User Makeman
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1 Answer

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Final answer:

Correlation does not imply causation: while Beverly's study shows a strong correlation between ice cream and soda sales, it does not provide evidence that one causes the other. Other variables, like the weather, may influence both sales. Understanding this distinction is crucial in various fields to correctly interpret data.

Step-by-step explanation:

Beverly's study on ice cream and soda sales suggests a strong correlation between the two, but it's essential to understand correlation does not equate to causation. Statements I and II, which suggest that eating more ice cream causes thirst or that drinking more soda causes hunger, cannot be accurately inferred from a correlation alone. Statement III, which describes a strong correlation between ice cream sales and soda sales, can be supported by the data and the correlation coefficient found in Beverly's study. However, this correlation doesn't imply that one causes the other. There could be other factors at play, such as warmer weather leading to an increase in both ice cream and soda sales.

For example, correlational research in different contexts has demonstrated that while two variables may move in conjunction, like ice cream sales and rates of crime during warmer weather, or cereal consumption and healthier weights, one does not necessarily cause the other. A variety of confounding factors or a third variable, such as temperature or health-conscious behavior, may actually be influencing the correlation. This concept is highly relevant in fields as diverse as psychology, geography, and public health, underscoring the importance of careful analysis and experimental research to establish causation.

User Jakub Bartczuk
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