11. Correlation

Scatterplots & Intro to Correlation

11. Correlation

Scatterplots & Intro to Correlation

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Multiple Choice

Engineers are studying how cargo weight affects the flight duration of a delivery drone. The data below shows the cargo weight (pounds) and the corresponding flight time (minutes) for 12 test flights. Generate a scatterplot using a graphing calculator with cargo weight as the x-axis. Is there a correlation between cargo weight and flight duration.

Positive correlation

Negative correlation

Nonlinear correlation

No correlation

Verified step by step guidance

Step 1: Begin by organizing the data provided into two variables: cargo weight (x-axis) and flight duration (y-axis). The cargo weight values are [1, 7, 8, 4, 2, 3, 9, 6, 2, 6, 5, 10], and the flight duration values are [62, 45, 43, 53, 59, 56, 41, 48, 60, 47, 51, 38].

Step 2: Use a graphing calculator or software to create a scatterplot. Plot each pair of values (cargo weight, flight duration) as a point on the graph, with cargo weight on the x-axis and flight duration on the y-axis.

Step 3: Observe the pattern of the points on the scatterplot. Look for trends such as whether the points generally move upward, downward, or show no clear pattern as cargo weight increases.

Step 4: Analyze the relationship between the variables. If the points tend to decrease in flight duration as cargo weight increases, this indicates a negative correlation. If they increase together, it indicates a positive correlation. If the points form a curve, it may suggest a nonlinear correlation. If there is no discernible pattern, it suggests no correlation.

Step 5: Based on the scatterplot, determine the type of correlation. In this case, as cargo weight increases, flight duration tends to decrease, which suggests a negative correlation.

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