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.
In a positively skewed distribution, the tail faces to the right, indicating that there are a few exceptionally high values pulling the mean upwards. Conversely, in a negatively skewed distribution, the tail faces to the left, reflecting the presence of a few exceptionally low values that pull the mean downwards. This skewness affects the relationship between the mean, median, and mode in each case.
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)
When the mean and median do not coincide, it typically indicates that the data distribution is skewed. In a positively skewed distribution, the mean is greater than the median, while in a negatively skewed distribution, the mean is less than the median. This discrepancy arises because the mean is sensitive to extreme values, whereas the median is resistant to outliers, making it a better measure of central tendency in skewed distributions. Understanding this difference helps in accurately interpreting the data's characteristics.
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.
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.
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.