Probit analysis operates like multiple regression with dependent or response variables that are binary. The term probit was coined to refer to “probability unit.[Page 1326]” The statistic was originally developed to deal with the issues of what percentage of a pest would be killed by a particular dose of pesticide. The particular issue that Chester Bliss wrote about in 1934 was the challenge of determining the best pesticide to reduce insects that were feeding on grape leaves. In response to this consideration, he created a technique that became known as probit analysis. The goal of the model was to create a means of converting the data to a representation that could be viewed as a linear function. The procedure treats the same problems ...
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