To interpret the scatterplot regarding the relationship between shoe size (x-axis) and the number of movies watched (y-axis), you'll want to observe the overall trend of the data points. Here’s how you can analyze it based on common patterns:
-
Linear Association (A): If the points roughly form a straight line (either increasing or decreasing), it indicates a linear association.
-
Non-linear Association (B): If the points form a curve or any pattern that isn't a straight line, it indicates a non-linear association.
-
Positive Association (C): If as one variable increases (for example, shoe size), the other variable (movies watched) also tends to increase, then there is a positive association.
-
Negative Association (D): If as one variable increases, the other variable tends to decrease, then there is a negative association.
Without seeing the actual scatterplot, I can't provide a definitive interpretation. However, you can assess the trend of the points based on these definitions.
- If most points fall along an upward slope, choose A (Linear association) and C (Positive association).
- If the points fall along a downward slope, choose A (Linear association) and D (Negative association).
- If the points appear curved or scattered without forming a clear line, choose B (Non-linear association).
Make your choice based on what you see represented in the scatterplot. If you see a mixture of trends, you may need to specify which aspect is most prominent.