Hi guys!
So we have a data set that includes 8 categories with a population size of 10,000. Each category has multiples values within them. A score is assigned to each category value that is equal to the population size over the number of occurrences of that value within that category (populationCount / occurrencesForThatValue).
The categories need to be normalized in such a way that applies more weight to the categories with less values in them.
The table below has the 8 categories and how many values are in each category.
The table below shows Category C as an example with its 8 values and each values' scores and normalized scores with the occurrences of each value in the population.
We have tried multiplying the total score by the normalization formula below but the numbers are not matching.
Any help is appreciated. Thanks!
So we have a data set that includes 8 categories with a population size of 10,000. Each category has multiples values within them. A score is assigned to each category value that is equal to the population size over the number of occurrences of that value within that category (populationCount / occurrencesForThatValue).
The categories need to be normalized in such a way that applies more weight to the categories with less values in them.
The table below has the 8 categories and how many values are in each category.
The table below shows Category C as an example with its 8 values and each values' scores and normalized scores with the occurrences of each value in the population.
We have tried multiplying the total score by the normalization formula below but the numbers are not matching.
Any help is appreciated. Thanks!