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.
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. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.
positively skewed
It is a positively skewed distribution.
Not necessarily.
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.
If most the population has many high scores, the distribution is negatively skewed. If most have many low scores, it is positively skewed
When the data distribution is negatively skewed.
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)
If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.
No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.
positively skewed
It is a positively skewed distribution.
A normal curve, also known as a bell curve, is symmetric around its mean, indicating that data points are evenly distributed on either side, with most values clustering around the center. In contrast, a skewed curve is asymmetrical, meaning that it has a tail extending more to one side than the other; in a positively skewed curve, the tail is on the right, while in a negatively skewed curve, it is on the left. This skewness affects the mean, median, and mode of the data distribution, leading to different interpretations of the data's central tendency.
One of the characteristics of mean when measuring central tendency is that when there are positively skewed distributions, the mean is always greater than the median. Another characteristic is that when there are negatively skewed distributions, the mean is always less than the median.
When the data are skewed to the right the measure of skewness will be positive.