In general the distribution of F-ratio means what
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
Not necessarily.
skewed right.
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)
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
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
Not necessarily.
When the data distribution is negatively skewed.
If most the population has many high scores, the distribution is negatively skewed. If most have many low scores, it is positively skewed
skewed right.
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.
In a negatively skewed distribution, the tail extends to the left, indicating that there are a few lower values. As a result, the mode, which is the most frequently occurring value, is typically located to the right of the mean and median. This means that in negatively skewed distributions, the mode is usually higher than both the median and the mean.
No, a distribution is considered negatively skewed if the left tail is longer or fatter than the right tail. In this case, the bulk of the data is concentrated on the right side, with a longer tail extending to the left. A positively skewed distribution, on the other hand, has a longer right tail.
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The term used to describe this shape of a distribution is "negatively skewed" or "left-skewed." In a negatively skewed distribution, most of the data points are concentrated on the higher end, with a tail extending towards the lower end. This results in a longer left tail and a peak that is shifted to the right.
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)
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