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What else can I help you with?
When is data negatively or positively 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
Is considerably skewed distribution the same as bimodal 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
What is a skewed right?
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 shape of the F distribution is?
skewed right.
Can the distribution of the mean median and mode be equal if the are positively skewed or negatively skewed or symmetric?
Not necessarily.
When a population distribution is right skewed is the sampling distribution normal?
No, as you said it is right skewed.
When population distribution is right skewed is the sampling also with right skewed distribution?
If the population distribution is roughly normal, the sampling distribution should also show a roughly normal distribution regardless of whether it is a large or small sample size. If a population distribution shows skew (in this case skewed right), the Central Limit Theorem states that if the sample size is large enough, the sampling distribution should show little skew and should be roughly normal. However, if the sampling distribution is too small, the sampling distribution will likely also show skew and will not be normal. Although it is difficult to say for sure "how big must a sample size be to eliminate any population skew", the 15/40 rule gives a good idea of whether a sample size is big enough. If the population is skewed and you have fewer that 15 samples, you will likely also have a skewed sampling distribution. If the population is skewed and you have more that 40 samples, your sampling distribution will likely be roughly normal.
When is data negatively or positively 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
How many tails in skewed distribution?
A skewed distribution typically has one tail that is longer or fatter than the other. In a right-skewed distribution, the tail on the right side is longer, while in a left-skewed distribution, the left tail is longer. Therefore, a skewed distribution has one dominant tail, but it can be characterized by its direction (right or left).
Who invented skewed distribution?
Nobody invented skewed distributions! There are more distributions that are skewed than are symmetrical, and they were discovered as various distribution functions were discovered.
Is a normal distribution a skewed?
No.
Can a normal distribution curve be symmetric or left-skewed or right-skewed?
Symmetric
What is a positively skewed distribution?
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.
What if the mean is greater than the median?
In the majority of Empirical cases the mean will not be equal to the median, so the event is hardly unusual. If the mean is greater, then the distribution is poitivelt skewed (skewed to the right).
Is considerably skewed distribution the same as bimodal 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
What is skewed 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.
What is a skewed right?
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.
