Answer:
Our goal is to understand how range and interquartile range describe data. To do this, we have to define the range and interquartile range of a given set of data, we have to be able to calculate the range and interquartile a range of a given set of data, and then we want to be able to determine how range and interquartile range are impacted by outliers.
So how can you describe data with range and interquartile range? Range tells us if data is grouped closely together or spread far apart. Interquartile range tells us if data is grouped closely around the median. The key concepts. Range is the difference of the maximum and minimum values.
So if we wanted to calculate the range of this particular data set here, we would say 20 minus 1 and get a range of 19. Interquartile range is the difference of the upper and lower quartiles. In order to do this, we first have to find the median to find those upper and lower quartiles. The median of this data set, the value in the middle, is 6. The lower quartile is the median of the lower half, the middle value then of these three data points being 3.
The upper quartile would be the middle of this data set, and that would be 8. So if we wanted to find the interquartile range, we'd subtract those values. 8 minus 3 gives us an interquartile range of 5. Interquartile range describes the spread of data around the median.
A small interquartile range means that most of the data, the middle half, is clustered tightly around the median, whereas a large interquartile range would mean that that data that's in the middle is more spread out. And finally, outliers impact the range, but have little impact on the interquartile range. If we consider our data set here, we see that we have an outlier of 20, but it really only impacts the range.
It does not play a significant role on the interquartile range.
Step-by-step explanation: also brainleist
Hence your answer will be D
