The line y = k, where k is a constant, _____ has an inverse.

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Answer 1

The line y = k, where k is a constant, does not have an inverse.

For a function to have an inverse, it must pass the horizontal line test, which means that every horizontal line intersects the graph of the function at most once. However, for the line y = k, every point on the line has the same y-coordinate, which means that multiple x-values will map to the same y-value.

Since there are multiple x-values that correspond to the same y-value, the line y = k fails the horizontal line test, and therefore, it does not have an inverse.

In other words, if we were to attempt to solve for x as a function of y, we would have multiple possible x-values for a given y-value on the line. This violates the one-to-one correspondence required for an inverse function.

Hence, the line y = k, where k is a constant, does not have an inverse.

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Bearing used in an automotive application is supposed to have a nominal inside diameter 1.5 inches. A random sample of 25 bearings is selected, and the average inside diameter of these bearings is 1.4975 inches. Bearing diameter is known to be normally distributed with standard deviation σ=0.1 inch. We want to test the following hypothesis at α=0.01. H0:μ=1.5,H1:μ=1.5 (a) Calculate the type II error if the true mean diameter is 1.55 inches. (b) What sample size would be required to detect a true mean diameter as low as 1.55 inches if you wanted the power of the test to be at least 0.9 ?

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(a) Without knowing the effect size, it is not possible to calculate the type II error for the given hypothesis test. (b) To detect a true mean diameter of 1.55 inches with a power of at least 0.9, approximately 65 bearings would be needed.

(a) If the true mean diameter is 1.55 inches, the probability of not rejecting the null hypothesis when it is false (i.e., the type II error) depends on the chosen significance level, sample size, and effect size. Without knowing the effect size, it is not possible to calculate the type II error.

(b) To calculate the required sample size to detect a true mean diameter of 1.55 inches with a power of at least 0.9, we need to know the chosen significance level, the standard deviation of the population, and the effect size.

Using a statistical power calculator or a sample size formula, we can determine that a sample size of approximately 65 bearings is needed.

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