The retaining wall is skewed perfectly.
Nobody invented skewed distributions! There are more distributions that are skewed than are symmetrical, and they were discovered as various distribution functions were discovered.
Skewed is an irregular adjective because it ends in -ed. An example of a sentence would be, "The results of his test were skewed due to the teacher's mistakes." Or you could say something like, "His conception of religion was skewed."
It is not at all skewed. As to oddly shaped, it depends on your expectations.
No.
Skews are used on a graph. If the points or lines go to one side then they are skewed to the right or left. For example, If your lines or plots start low and go up right to the right, then it is skewed to the right (same as the left). Now, if the plots are everywhere then there is no skew.
Due to systematic error, my results are skewed.
i) Since Mean<Median the distribution is negatively skewed ii) Since Mean>Median the distribution is positively skewed iii) Median>Mode the distribution is positively skewed iv) Median<Mode the distribution is negatively skewed
The retaining wall is skewed perfectly.
As the mean is greater than the median it will be positively skewed (skewed to the right), and if the median is larger than the mean it will be negatively skewed (skewed to the left)
When a set of votes has been skewed it means that either the mean is higher than the median or lower. If it is higher the vote is said to be skewed to the right and when lower it is skewed to the left.
Symmetric
Nobody invented skewed distributions! There are more distributions that are skewed than are symmetrical, and they were discovered as various distribution functions were discovered.
Skewed is an irregular adjective because it ends in -ed. An example of a sentence would be, "The results of his test were skewed due to the teacher's mistakes." Or you could say something like, "His conception of religion was skewed."
No, as you said it is right skewed.
how can information from sources be skewed to validate an argument
In the majority of Empirical cases the mean will not be equal to the median, so the event is hardly unusual. If the mean is greater, then the distribution is poitivelt skewed (skewed to the right).