What does a Platykurtic curve mean?
What does a Platykurtic curve mean?
The term “platykurtic” refers to a statistical distribution in which the excess kurtosis value is negative. For this reason, a platykurtic distribution will have thinner tails than a normal distribution will, resulting in fewer extreme positive or negative events.
What does a Platykurtic distribution look like?
Negative excess values of kurtosis (<3) indicate that a distribution is flat and has thin tails. Platykurtic distributions have negative kurtosis values. A platykurtic distribution is flatter (less peaked) when compared with the normal distribution, with fewer values in its shorter (i.e. lighter and thinner) tails.
Is Platykurtic normal?
The word “platykurtic” refers to a statistical distribution where the value of excess kurtosis is negative. A platykurtic distribution would, therefore, have thinner tails than a normal distribution, leading to less extreme positive or negative events.
Is T distribution a Leptokurtic?
The T distribution is an example of a leptokurtic distribution. It has fatter tails than the normal (you can also look at the first image above to see the fatter tails). Therefore, the critical values in a Student’s t-test will be larger than the critical values from a z-test. The t-distribution.
When coefficient of skewness is zero the distribution is?
The skewness for a normal distribution is zero, and any symmetric data should have a skewness near zero. Negative values for the skewness indicate data that are skewed left and positive values for the skewness indicate data that are skewed right.
Which of the following is not a measure of dispersion?
Absolute measures include Range, quartile deviation, mean deviation, and standard deviation. Relative measures include coefficients of range, quartile deviation, variation, and mean deviation. Hence, Quartile is not the measure of dispersion.
What does it mean when kurtosis is zero negative or positive?
kurtosis=∑Ni=1(Yi−Y¯)4/Ns4−3. This definition is used so that the standard normal distribution has a kurtosis of zero. In addition, with the second definition positive kurtosis indicates a “heavy-tailed” distribution and negative kurtosis indicates a “light tailed” distribution.
