Practice Sensitivity in Math
Use these practice problems to test your method after reviewing the concept explanation and worked examples.
Quick Recap
In the context of functions, sensitivity measures how much the output changes in response to a small change in the input — high sensitivity means small input changes cause large output changes.
A sensitive scale notices tiny weight differences. An insensitive one doesn't.
Showing a random 20 of 50 problems.
Example 1
easyFor , compute the sensitivity at with and compare to .
Example 2
easyFor , what is the sensitivity?
Example 3
easyFor , estimate the sensitivity near using .
Example 4
hardFor , the sensitivity is . By what factor is more sensitive at than at ?
Example 5
challengeFor , the sensitivity (slope) is . Find every input where the sensitivity equals 12, and state where the function is least sensitive.
Example 6
hardFor , estimate the slope at and explain why the function is more sensitive to input near than near .
Example 7
easyBetween and , which is more sensitive to input changes?
Example 8
mediumA weather model uses where is pressure. If and measurement error is , estimate the resulting error in .
Example 9
mediumFor , compare sensitivity at vs , using slope .
Example 10
mediumFor , find ALL inputs where the sensitivity (slope ) equals .
Example 11
mediumTwo models predict the same output at , but model A has slope 1 and model B has slope 8 there. If is uncertain by , which model's prediction is more reliable?
Example 12
easyTrue or false: doubling the input always doubles the sensitivity for a linear function.
Example 13
mediumFor , an input measured as produces what output, with what uncertainty?
Example 14
easyA scale shows 100.0 g for a true 100 g object and 100.5 g when 0.5 g is added. Is this scale sensitive to small changes?
Example 15
challengeA four-stage cascade has local sensitivities . Compute the total sensitivity and decide whether the cascade amplifies or attenuates a small input perturbation.
Example 16
hardTwo predictive models for output given : has and has at the operating point. If is measured with uncertainty, which model's prediction has lower output uncertainty?
Example 17
mediumAn input has a uncertainty. After , what is the approximate uncertainty in the output?
Example 18
mediumFor followed by , what is the overall sensitivity of to ?
Example 19
easyFor , what is the sensitivity of the output to the input (change in output per unit change in input)?
Example 20
mediumFor , compare the sensitivity near with the sensitivity near (use the derivative ). Which input region is more sensitive?