Use the tables to create scatterplots and determine which scatterplot shows a linear association.(1 point)

Responses

x
x
5 8 2 4 6 12 10 1 3 7
y
y
800 700 350 450 500 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 800 700 350 450 500 1000 900 250 400 750

x
x
5 8 2 4 6 12 10 1 3 7
y
y
550 800 250 300 700 1000 650 300 100 700
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 300 700 1000 650 300 100 700

x
x
5 8 2 4 6 12 10 1 3 7
y
y
550 800 250 500 500 400 650 150 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 250 500 500 400 650 150 400 750

x
x
5 8 2 4 6 12 10 1 3 7
y
y
550 800 350 450 700 1000 900 250 400 750
x 5 8 2 4 6 12 10 1 3 7 y 550 800 350 450 700 1000 900 250 400 750

1 answer

To determine which scatterplot shows a linear association, we would analyze the datasets described.

I cannot create actual scatterplots in this text format, but I can guide you through how to analyze the data numerically based on the descriptions given for each scatterplot.

Dataset Analysis:

  1. First Dataset:

    • \( x: 5, 8, 2, 4, 6, 12, 10, 1, 3, 7 \)
    • \( y: 800, 700, 350, 450, 500, 1000, 900, 250, 400, 750 \)
    • The values of \( y \) do not show a clear increasing or decreasing trend as \( x \) increases.
  2. Second Dataset:

    • \( x: 5, 8, 2, 4, 6, 12, 10, 1, 3, 7 \)
    • \( y: 550, 800, 250, 300, 700, 1000, 650, 300, 100, 700 \)
    • This dataset also lacks a clear linear trend; \( y \) values fluctuate widely as \( x \) increases.
  3. Third Dataset:

    • \( x: 5, 8, 2, 4, 6, 12, 10, 1, 3, 7 \)
    • \( y: 550, 800, 250, 500, 500, 400, 650, 150, 400, 750 \)
    • This dataset again shows considerable fluctuation in \( y \) values relative to \( x \) and does not suggest a linear relationship.
  4. Fourth Dataset:

    • \( x: 5, 8, 2, 4, 6, 12, 10, 1, 3, 7 \)
    • \( y: 550, 800, 350, 450, 700, 1000, 900, 250, 400, 750 \)
    • Similar to the previous datasets, it shows varying \( y \) values.

Conclusion:

From this analysis, none of the provided datasets exhibit a clear linear association since \( y \) values do not consistently increase or decrease in relation to \( x \).

If you feel that one of the datasets might suggest linearity upon visual inspection (for example, consistent upward or downward patterns), plotting the points on a graph is crucial to confirming this. In a hypothetical case, if one of them did appear to create a straight line or a narrow band upon plotting, that would be indicative of a linear association.

If you need more analysis or specifics, feel free to clarify!