When correlation between variables is not explicit, data can be collected by adapting the quantitative measurement tools in use for quantitative measurement of possibility, a nonlinear measurement. This adaptation is possible because measurement data can be evaluated more qualitatively using parameters for possibility. These can be defined as regular-symmetric, irregular-symmetric, symmetric with regard to situation at which the distribution begins, event-based symmetric, symmetrical-contiguous, and of symmetrical discrimination, all available using possibility measurement tools. Without modifying the structure of conventional quantitative measurement tools, their pre-measurement adaptation can be carried out, making quantitative possibility measurement tools. This is made possible by converting scale values and scale options of each measurement tool to situation numbers and event numbers. Post-measurement adaptation can be carried out by converting the value measured to a symmetrical situation number. In this study, adaptation techniques and principles will be provided, for conventional quantitative measurement tools which will be classified according to their scale indicators and then used for quantitative measurements of possibility.