The following is true about sensitivity: Group of answer choices a) The output of the model is said to be inversely sensitive if the output of the model changes a small amount for a large change in an input variable b) Sensitivity is not an important concept in modeling c) It can help the modeler tell, on a relative basis, what are the important variables d) A variable is considered NOT very sensitive if a small change in the variable results `in a large change in the output of the model

If we decrease the significance level (alpha) all else being equal, the power of the test will:   A. Won't change   B. Increase   C. Decrease   D. It depends – need more information

A group of international experts in fuzzy set theory were invited to classify the overall performance of two research scholars, after a lot of discussion they agreed to consider the following attributes(Creativity, presentation skills) in the classification of the scholar .design a fuzzy inference system to find how would they judge similarity of the research scholars with varying attributes ?Explain the procedure in details. Creativity Skills 1 2 3 4 5 Presentation skills 1 No creativity Bad 2 Fair Fair 3 Good Good 4 Very good 5 Excellent Very good Excellent Creativity 1 5 4 3 2 1 2 4 4 3 2 1 3 4 3 3 2 1 + 3 2 2 1 1 5 3 2 1 1 1 B- Draw the Genetic algorithm flowchart and write the code for each step.

You build a model predicting blood pressure as a function of three variables: weight (numeric) age (numeric) income (categorical: low, medium, high) You first specify your model as: blood pressure ~ age * income + weight How many parameters (k) does your model have? (Remember, we do not count the grand mean in k)   You change the above model specification to be: blood pressure ~ age * income + weight * income How many parameters does your model have now?   You change your model to include the three-way interaction (which, remember, includes all two-way interactions and main effects, too!) Your model now looks like this: blood pressure ~ age * income * weight How many parameters does your model have now?