In other words "our society has modified and tempered with traditional values and beliefs for their own selfish wants" to me this quote seems like a negative view, not one the speaker is enthusiastic about. He/she is not pleased with the way the "world has skewed values"
But hey as with many forms of literature, especially quotes they can be interpreted many different ways so read more than one response. Hope this helped
positively skewed with all values greater than or equal to zero
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.
The word is correctly spelled "skewed" meaning distorted or out of line, as with numerical values or sequences. The similar word is askew.
skewed
positively skewed
positively skewed with all values greater than or equal to zero
Logical Fallacies
It is a positively skewed distribution.
No. A distribution may be non-skewed and bimodal or skewed and bimodal. Bimodal means that the distribution has two modes, or two local maxima on the curve. Visually, one can see two peaks on the distribution curve. Mixture problems (combination of two random variables with different modes) can produce bimodal curves. See: http://en.wikipedia.org/wiki/Bimodal_distribution A distribution is skewed when the mean and median are different values. A distribution is negatively skewed when the mean is less than the median and positively skewed if the mean is greater than the median. See: http://en.wikipedia.org/wiki/Skewness
No, the properties inside the distortion would be consistent with universal values however the inter-relational values in the area of transition might be 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
You would use the median if the data were very skewed, with extreme values.
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)