Question

What important feature of the data is not revealed through the different measures ofâ variation?

a. the measures of variation reveal nothing about how the numbers of manatee deaths are spread.

b. the measures of variation do not reveal the difference between the largest number of manatee deaths and the smallest number of manatee deaths in the data.

c. the measures of variation reveal nothing about the pattern over time?

Answer 1

Measures of variation such as standard deviation inform about data spread but do not reveal the pattern over time or how data values change during different periods. The shape of the data affects the choice of the central tendency measure.

Step-by-step explanation:

An important feature of the data that is not revealed through the different measures of variation is the pattern over time. Measures of variation, such as standard deviation, provide information about how spread out data points are around the mean, but these statistics do not show how data points are distributed across different times or events. To understand patterns over time, other types of analysis, like time-series analysis, would be necessary.

Examining the shape of the data is also crucial, as it helps in choosing the most appropriate measure of central tendency for the data, which can be the mean, median, or mode. For instance, if data is skewed due to outliers, the median might be preferred over the mean. Measures of central tendency and measures of spread are both valuable in data analysis, but they each provide different pieces of the puzzle.

Answer 2

Answer: c. Measures of variation reveal nothing about the pattern over time.

The measures of variation are the range, interquartile range, variance and standard deviation.

Variance and its square root, standard deviation measure the dispersion of data about the mean. They measure how spread out the data is from the mean.

Range is a measure of variation that shows the difference between the largest and smallest values in the data.

However, measures of variation reveal nothing about the patterns over time. They treat a given data set as a whole and give numbers are applicable for the entire data set.