1. A non-transitory computer-readable medium storing therein a data analyzing program that causes a computer, which has a memory device storing a set of measured values that include a set of positive case measured values for which an objective variable for an explanatory variable group of one or more explanatory variables represents a positive case and a set of negative case measured values for which the objective variable for the explanatory variable group represents a negative case, to execute a process, the process comprising: extracting randomly, a positive case measured value group and a negative case measured value group from the set of measured values such that the positive case measured values and the negative case measured values extracted are equivalent in number; generating based on the positive case measured value group and the negative case measured value group extracted at the extracting, a prediction equation that predicts the objective variable for a prediction algorithm; first calculating a first predicted value group by substituting into the prediction equation generated at the generating, each remaining positive case measured value group that remains after elimination of the positive case measured value group from the set of positive case measured values; second calculating a second predicted value group by substituting into the prediction equation generated at the generating, each remaining negative case measured value group that remains after elimination of the negative case measured value group from the set of negative case measured values; first identifying among the first predicted value group calculated at the first calculating, a first coincident-case count of predicted values that coincide with the positive case measured values originally substituted into the prediction equation and a first non-coincident-case count of predicted values that do not coincide with the positive case measured values; second identifying among the second predicted value group calculated at the second calculating, a second coincident-case count of predicted values that coincide with the negative case measured values originally substituted into the prediction equation and a second non-coincident-case count of predicted values that do not coincide with the negative case measured values; computing based on identification results obtained at the first and the second identifying, a weighted correct answer percentage that is a correct answer percentage indicative of the degree of coincidence between a measured value and a predicted value for the prediction algorithm and varying depending on a weight variable; and outputting a computation result obtained at the computing.