Answer:
b. Skewed-left
Step-by-step explanation:
The histogram will be expressed with the x-axis representing the salaries, in growing amount to the right. The y-axis will represent the relative or absolute frequency.
We know that most of the players earn the minimum league wage. Then, we will have a high frequency in the low salaries classes, at the left of the histogram. A few players earn very high salaries, so we will have a right tail with high values for the salaries a little frequency.
There is no symmetry in this histogram and it is not uniform, as there is no representative mean salary.
As most of the data will be close to the left side, we can conclude that the histogram will be skewed-left.
The Histogram of salary data, with most having less salary is RIGHT Skewed
Given : Data of players' salary is concentrated towards towards most players having less ( minimum ) salary.
Right Skewness denotes a distribution where Tail is on the right side. This implies data is highly concentrated toward left side, ie lower independent variable (x - here 'salary') values.
Left Skewness denotes a distribution where Tail is on the left side. This implies data is highly concentrated towards right side, ie higher independent variable (x - here 'salary') values.
In this case : As more players have lower values of independent variable ie salary, so the data will be concentrated at left - having tail at right.
Hence, it will be Skewed Right
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