True
When the majority of the data values fall to the right of the mean, the distribution is indeed said to be left skewed, or negatively skewed. In this type of distribution, the tail on the left side is longer or fatter, indicating that there are a few lower values pulling the mean down. This results in the mean being less than the median, as the median is less affected by extreme values. Overall, left skewed distributions show that most data points are higher than the average.
This is true
Unimodal skewed refers to a distribution that has one prominent peak (or mode) and is asymmetrical, meaning it is not evenly balanced around the peak. In a right (or positively) skewed distribution, the tail on the right side is longer or fatter, indicating that most data points are concentrated on the left. Conversely, in a left (or negatively) skewed distribution, the tail on the left side is longer, with most data points clustered on the right. This skewness affects the mean, median, and mode of the data, typically pulling the mean in the direction of the tail.
A normal distribution is not skewed. Skewness is a measure of how the distribution has been pulled away from the normal.A feature of a distribution is the extent to which it is symmetric.A perfectly normal curve is symmetric - both sides of the distribution would exactly correspond if the figure was folded across its median point.It is said to be skewed if the distribution is lop-sided.The word, skew, comes from derivations associated with avoiding, running away, turning away from the norm.So skewed to the right, or positively skewed, can be thought of as grabbing the positive end of the bell curve and dragging it to the right, or positive, direction to give it a long tail in the positive direction, with most of the data still concentrated on the left.Then skewed to the left, or negatively skewed, can be thought of as grabbing the negative end of the bell curve and dragging it to the left, or negative, direction to give it a long tail in the negative direction, with most of the data still bunched together on the right.Warning: A number of textbooks are not correct in their use of the term 'skew' in relation to skewed distributions, especially when describing 'skewed to the right' or 'skewed to the left'.
A distribution or set of observations is said to be skewed left or negatively skewed if it has a longer "tail" of numbers on the left. The mass of the distribution is more towards the right of the figure rather than the middle.
Symmetric
a binary tree with only left sub trees is called as left skewed binary tree
False. It can be skewed to the left or right or be symmetrical.
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.
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)
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.
on the left and when it is skewed left it is on the right
If it is very highly skewed then the mode is best.
A distribution or set of observations is said to be skewed right or positively skewed if it has a longer "tail" of numbers on the right. The mass of the distribution is more towards the left of the figure rather than the middle.
The population data may be skewed and thus the mean is not a valid statistic. If mean > median, the data will be skewed to the right. If median > mean, the data is skewed to the left.
True