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if coefficient of skewness is zero then distribution is symmetric or zero skewed.
It depends on what the underlying distribution is and which coefficient you want to calculate.
A measure of skewness is Pearson's Coefficient of Skew. It is defined as: Pearson's Coefficient = 3(mean - median)/ standard deviation The coefficient is positive when the median is less than the mean and in that case the tail of the distribution is skewed to the right (notionally the positive section of a cartesian frame). When the median is more than the mean, the cofficient is negative and the tail of the distribution is skewed in the left direction i.e. it is longer on the left side than on the right.
lol...u seem to be studying in swinburne?? may be coincidence...! I was looking for the same stuff :P
coefficient
if coefficient of skewness is zero then distribution is symmetric or zero skewed.
Coefficient of varation
It depends on what the underlying distribution is and which coefficient you want to calculate.
To determine the distribution coefficient in a chemical system, one can conduct a partitioning experiment where the compound of interest is placed in two immiscible phases. By measuring the concentrations of the compound in each phase at equilibrium, the distribution coefficient can be calculated as the ratio of the compound's concentration in one phase to its concentration in the other phase.
The coefficient distribution F of I2 between H2O and CCl4 refers to the partitioning of I2 between the two solvents. It quantifies the relative solubility of I2 in each solvent and is determined experimentally using a partition coefficient measurement. The coefficient distribution F is calculated as the concentration of I2 in CCl4 divided by the concentration of I2 in H2O at equilibrium.
The distribution coefficient is used to measure how a solute partitions between two immiscible phases, typically a solid and a liquid. It is useful in various fields such as chemistry, pharmacy, and environmental science to predict and understand the distribution behavior of solutes in different phases. It helps in optimizing extraction processes, designing separation techniques, and determining the bioavailability of drugs.
The Gini coefficient is calculated by comparing the distribution of income among individuals in a population to a perfectly equal distribution. It ranges from 0 (perfect equality) to 1 (perfect inequality). A higher Gini coefficient indicates greater income inequality within a society.
The Gini coefficient is calculated by comparing the distribution of income within a population to a perfectly equal distribution. It ranges from 0 (perfect equality) to 1 (perfect inequality). A higher Gini coefficient indicates greater income inequality within a population.
The Gini coefficient is a measure of income inequality within a population, with a value of 0 indicating perfect equality and 1 indicating perfect inequality. It is commonly used by economists and policymakers to understand the distribution of income or wealth within a country. A higher Gini coefficient suggests a more unequal distribution of income.
The distribution coefficient of iodine between water and chloroform is approximately 35. This means that iodine is more soluble in chloroform than in water.
To calculate the Gini coefficient for income distribution, you need to plot a Lorenz curve showing the cumulative share of income against the cumulative share of the population. The Gini coefficient is then calculated as the area between the Lorenz curve and the line of perfect equality, divided by the total area under the line of perfect equality. The Gini coefficient ranges from 0 (perfect equality) to 1 (perfect inequality).
A measure of skewness is Pearson's Coefficient of Skew. It is defined as: Pearson's Coefficient = 3(mean - median)/ standard deviation The coefficient is positive when the median is less than the mean and in that case the tail of the distribution is skewed to the right (notionally the positive section of a cartesian frame). When the median is more than the mean, the cofficient is negative and the tail of the distribution is skewed in the left direction i.e. it is longer on the left side than on the right.