Nobody invented skewed distributions! There are more distributions that are skewed than are symmetrical, and they were discovered as various distribution functions were discovered.
No.
2
It is not at all skewed. As to oddly shaped, it depends on your expectations.
A distribution that is NOT normal. Most of the time, it refers to skewed distributions.
It is a positively skewed distribution.
If most the population has many high scores, the distribution is negatively skewed. If most have many low scores, it is positively 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
A distribution is skewed if one of its tails is longer than the other. The first distribution shown has a positive skew. This means that it has a long tail in the positive direction.
No, as you said it is right skewed.
Nobody invented skewed distributions! There are more distributions that are skewed than are symmetrical, and they were discovered as various distribution functions were discovered.
No.
Symmetric
A positively skewed or right skewed distribution means that the mean of the data falls to the right of the median. Picturewise, most of the frequency would occur to the left of the graph.
The median is the most appropriate center when the distribution is very skewed or if there are many outliers.
2
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).