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Community Bot
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I have a number of samples of different sizes from a population of unknown size. The data are market shares for five different products within a category (so they sum to 1). I want to know how many observations I need for the configuration of shares in a sample to be a reasonable approximation of the configuration of shares in the population.

I have read this: Sample size for categorical dataSample size for categorical data, but I have priors about what the shares look like (that is, I don't want the "worst case" configuration of shares). Is there a way to calculate n* for alpha = .05, d = .05 and some a priori configuration of proportions?

I have a number of samples of different sizes from a population of unknown size. The data are market shares for five different products within a category (so they sum to 1). I want to know how many observations I need for the configuration of shares in a sample to be a reasonable approximation of the configuration of shares in the population.

I have read this: Sample size for categorical data, but I have priors about what the shares look like (that is, I don't want the "worst case" configuration of shares). Is there a way to calculate n* for alpha = .05, d = .05 and some a priori configuration of proportions?

I have a number of samples of different sizes from a population of unknown size. The data are market shares for five different products within a category (so they sum to 1). I want to know how many observations I need for the configuration of shares in a sample to be a reasonable approximation of the configuration of shares in the population.

I have read this: Sample size for categorical data, but I have priors about what the shares look like (that is, I don't want the "worst case" configuration of shares). Is there a way to calculate n* for alpha = .05, d = .05 and some a priori configuration of proportions?

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Nate Hutchinson
Nate Hutchinson
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Sample Size Determination for Multinomial Proportions

I have a number of samples of different sizes from a population of unknown size. The data are market shares for five different products within a category (so they sum to 1). I want to know how many observations I need for the configuration of shares in a sample to be a reasonable approximation of the configuration of shares in the population.

I have read this: Sample size for categorical data, but I have priors about what the shares look like (that is, I don't want the "worst case" configuration of shares). Is there a way to calculate n* for alpha = .05, d = .05 and some a priori configuration of proportions?