0
Want this question answered?
Be notified when an answer is posted
Add your answer:
Earn +20 pts
In which situations mean and median are not same?
If there is any skewness in the distribution.
How skewness help in determining relation between different measures of central tendency?
Negative skewness means the average (mean) will be less than the median. Positive skewness means the opposite. I'm not sure if any rule holds for the mode.
What is skewness how would you find it in a non symmetrical distribution?
Skewness is a measure of the extent to which the probability distribution of a random variable lies more to one side of the mean, as opposed to it being exactly symmetrical.If μ and s are the mean and standard deviation of a random variable X, thenSkew(X) = Expected value of [(X - μ)/s]3
The use of Pearson Coefficient of Skewness?
the use of the pearson's of skewness
If coefficient of skewness equals 0 then what would you say about the skewness of the distribution?
if coefficient of skewness is zero then distribution is symmetric or zero skewed.
What is Pearson's first rule of the measure of coefficient of skewness?
skewness=(mean-mode)/standard deviation
What is the definition for skew in math terms?
The skewness of a random variable X is the third standardised moment of the distribution. If the mean of the distribution is m and the standard deviation is s, then the skewness, g1 = E[{(X - m)/s}3] where E is the expected value. Skewness is a measure of the degree to which data tend to be on one side of the mean or the other. A skewness of zero indicates symmetry. Positive skewness indicates there are more values that are below the mean but the the ones that are above the mean, although fewer, are substantially bigger. Negative skewness is defined analogously.
In which situations mean and median are not same?
If there is any skewness in the distribution.
How skewness help in determining relation between different measures of central tendency?
Negative skewness means the average (mean) will be less than the median. Positive skewness means the opposite. I'm not sure if any rule holds for the mode.
What is skewness how would you find it in a non symmetrical distribution?
Skewness is a measure of the extent to which the probability distribution of a random variable lies more to one side of the mean, as opposed to it being exactly symmetrical.If μ and s are the mean and standard deviation of a random variable X, thenSkew(X) = Expected value of [(X - μ)/s]3
The use of Pearson Coefficient of Skewness?
the use of the pearson's of skewness
Please explain positive and negative skewness?
A positive skewness is when the value of mean is greater than the mode. that is, the curve is more skewed at the right hand side or the right tail is longer than the left tail. The negative skewness is when the mean is smaller than the mode, and in this case the curve is more skewed on the left hand side.
If coefficient of skewness equals 0 then what would you say about the skewness of the distribution?
if coefficient of skewness is zero then distribution is symmetric or zero skewed.
What is the difference between Dispersion and Skewness?
distinguish between dispersion and skewness
If mean is 8 median is 6 and standard deviation is 2 what is skewness?
Karl Pearson simplified the topic of skewness and gave us some formulas to help. The first is the Pearson mode or first skewness coefficient. It is defined by the (mean-median)/standard deviation. So in this case the Pearson mode is: (8-6)/2 =1 There is also the Pearson Median. This is also called second skewness coefficient. It is defined as 3(mean-median)/standard deviation which in this case is 6/2 =3 hence the distribution is positive skewed
What is the values of the skewdness and kurtosis coefficient for the normal distribution 0 and 3 respectively?
No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.
What shows the skewness of a probability distribution?
The third moment. That is, the expected value of the cubes of the deviations from the mean.
