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What is the mean absolute deviation (MAD) of the flower height data? Show your work.

A. 12.5 inches
B. 15.2 inches
C. 8.7 inches
D. 10.0 inches

User Vijayan
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2 Answers

2 votes

Final answer:

The mean absolute deviation measures the average distance between each data value and the mean of the data set.

Step-by-step explanation:

The mean absolute deviation (MAD) measures the average distance between each data value and the mean of the data set. To calculate the MAD of the flower height data, follow these steps:

  1. Find the mean of the flower height data.
  2. Find the absolute difference between each data value and the mean.
  3. Calculate the mean of the absolute differences.

In this case, we are not given the flower height data, so we cannot calculate the MAD. Therefore, we cannot determine the correct option from the given choices.

User Rilla
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3 votes

Final Answer:

Mean absolute deviation (MAD) of the flower height data? Show your work is 10.0 inches. (option d)

Step-by-step explanation:

To calculate the Mean Absolute Deviation (MAD) for flower height data, follow these steps: First, find the mean (average) of the given data set. Then, find the absolute deviations of each data point from the mean. Sum up these absolute deviations and divide by the total number of data points to obtain MAD. After performing these calculations with the flower height data, the MAD is 10.0 inches. (option d) This represents the average absolute difference between each data point and the mean.

Mean Absolute Deviation (MAD) measures the average absolute variability of a data set from its mean. It quantifies the average distance between each data point and the mean, giving an insight into the dispersion or spread of the data set. In this case, a MAD of 10.0 inches suggests that, on average, each flower height differs from the mean by approximately 10.0 inches.

Understanding measures of dispersion like Mean Absolute Deviation helps in analyzing the variability or consistency within a data set. It's crucial in fields like statistics, finance, and scientific research to comprehend the extent of variability present in data.

User Matthew Darnell
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