#### Abstract

The problem considered is that of choosing between the two specifications . . . of known multinomial probabilities on the basis of sample values x_{ j}, the observed counts in the j = 1,... ,k, classes, with . . . The particular question examined is 'how large should N be to achieve reliable differentiation?'. It is shown how to find N such that the probability of misc1assification does not exceed a prescribable value. The method is exemplified in a genetic context.

#### Keywords

categorized data, X2, cytogenetic, goodness-of-fit, misclassification probabilities, multinomial distributions, sample size, soybean breeding

#### Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

#### Recommended Citation

Cox, C. Philip
(1994).
"DETERMINING SAMPLE SIZE TO BOUND THE PROBABILITY OF CLASSIFYING A SAMPLE INTO THE WRONG ONE OF TWO MULTINOMIALLY DISTRIBUTED POPULATIONS,"
*Conference on Applied Statistics in Agriculture*.
http://newprairiepress.org/agstatconference/1994/proceedings/5

DETERMINING SAMPLE SIZE TO BOUND THE PROBABILITY OF CLASSIFYING A SAMPLE INTO THE WRONG ONE OF TWO MULTINOMIALLY DISTRIBUTED POPULATIONS

The problem considered is that of choosing between the two specifications . . . of known multinomial probabilities on the basis of sample values x_{ j}, the observed counts in the j = 1,... ,k, classes, with . . . The particular question examined is 'how large should N be to achieve reliable differentiation?'. It is shown how to find N such that the probability of misc1assification does not exceed a prescribable value. The method is exemplified in a genetic context.