Question

analyzing shape of a histogram
length of employment
the histogram shows how many employees have worked at a restaurant for the given intervals of time.
the shape of the histogram is ▼ because most employees have worked at the restaurant for a while.
there is an outlier in the interval of ▼ months.
(the histogram on the left has x - axis labeled number of months with intervals 1 - 3, 4 - 6, 7 - 9, 10 - 12, 13 - 15, 16 - 18, 19 - 21 and y - axis labeled number of employees from 0 to 18. the right side has a dropdown for the shape of the histogram and a dropdown for the outlier interval with options 1 - 3, 4 - 6, 7 - 9, 19 - 21.)

Explanation:

A right - skewed histogram has a longer tail on the right side. In this case, as the number of months increases, the frequency (number of employees) first increases and then the last bar (for 19 - 21 months) is not extremely long compared to a left - skewed case. An outlier is a data point that is far from other data points. The intervals 1 - 3, 4 - 6, 7 - 9 have very low frequencies (close to 0 for 1 - 3, 4 - 6 and 2 for 7 - 9) compared to the higher frequencies in 13 - 15, 16 - 18, 19 - 21. Among these low - frequency intervals, 7 - 9 has a non - zero but still relatively low value, but when considering the context of the problem (most employees have worked for a while), the intervals 1 - 3, 4 - 6, 7 - 9 are on the lower end. If we assume a normal situation where we expect more employees to have longer tenures (as per the "most employees have worked at the restaurant for a while" statement), the lower intervals (1 - 3, 4 - 6, 7 - 9) are the ones that deviate. If we consider the non - zero but still very low frequency, 7 - 9 is a candidate. But if we consider the extreme low (close to 0) 1 - 3 and 4 - 6, but since 7 - 9 has a value (2) which is non - zero but still an order of magnitude lower than 12, 16 (values for 16 - 18 and 19 - 21).

Answer:

The shape of the histogram is right - skewed. There is an outlier in the interval of 7 - 9 months.