Abstract: A computing device receives a target value for a design quality metric. The target value indicates a desired quality of a design of an experiment and is related to an input parameter by a response curve. The computing device also validates the target value as being in a feasibility range for the design quality metric, and if so, determines a candidate value for the input parameter that yields a calculated value for the design quality metric. To determine the calculated value, the computing device iteratively adjusts the candidate value until the calculated value is within a predetermined tolerance of the target value. The computing device then updates an interactive graph visually representing the calculated value for the design quality metric as a function of the candidate value for the input parameter and outputs a graph visually representing the relationship that exists between the candidate value and the calculated value.

Abstract: A computing device receives a target value for a design quality metric. The target value indicates a desired quality of a design of an experiment and is related to an input parameter by a response curve. The computing device also validates the target value as being in a feasibility range for the design quality metric, and if so, determines a candidate value for the input parameter that yields a calculated value for the design quality metric. To determine the calculated value, the computing device iteratively adjusts the candidate value until the calculated value is within a predetermined tolerance of the target value. The computing device then updates an interactive graph visually representing the calculated value for the design quality metric as a function of the candidate value for the input parameter and outputs a graph visually representing the relationship that exists between the candidate value and the calculated value.

Abstract: A computing device obtains settings for a design of an experiment. The settings include a first sample size that indicates an amount of members for a first group observed as part of the experiment, a design quality metric that assesses, based on the first sample size, a quality of the design for the experiment prior to conducting the experiment, and a parameter pertaining to the first group. The computing device also displays first and second graphs of the design quality metric on a graphical user interface. The first graph is displayed as a function of the first sample size and the second graph is displayed as a function of the parameter pertaining to the first group. The computing device also receives a first user indication to change one or more of the settings, and then updates both the first and second graphs to account for the first user indication.

Abstract: A computing device obtains settings for a design of an experiment. The settings include a first sample size that indicates an amount of members for a first group observed as part of the experiment, a design quality metric that assesses, based on the first sample size, a quality of the design for the experiment prior to conducting the experiment, and a parameter pertaining to the first group. The computing device also displays first and second graphs of the design quality metric on a graphical user interface. The first graph is displayed as a function of the first sample size and the second graph is displayed as a function of the parameter pertaining to the first group. The computing device also receives a first user indication to change one or more of the settings, and then updates both the first and second graphs to account for the first user indication.

Abstract: A computing system determines a design space for designing a design system. The computing system receives a request to identify input(s) that will provide a response of the design system that advances a user-defined goal for the design system. The computing system, responsive to the request to identify input(s), generates a design for the design space that provides design cases for generating the response of the design system and obtains responses of the design system generated for multiple design cases of the design for the design system. The computing system selects at least one design case based on obtained responses of the design system for the multiple design cases, and based on the at least one design case, outputs an indication of suggested input(s) for the design system. The suggested input(s) advances the user-defined goal for the design system and is not disallowed according to disallowed combination(s).

Abstract: A computing system determines a design space for designing a design system. The computing system receives a request to identify input(s) that will provide a response of the design system that advances a user-defined goal for the design system. The computing system, responsive to the request to identify input(s), generates a design for the design space that provides design cases for generating the response of the design system and obtains responses of the design system generated for multiple design cases of the design for the design system. The computing system selects at least one design case based on obtained responses of the design system for the multiple design cases, and based on the at least one design case, outputs an indication of suggested input(s) for the design system. The suggested input(s) advances the user-defined goal for the design system and is not disallowed according to disallowed combination(s).