Question
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Michael was asked to properly evaluate this logarithm. Which answer should he come to? \( \log _{9} 1 / 2 \) - \( -1 / 2 \) -9

Ask by Page Mills. in the United States
Jan 25,2025

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Answer

Michael should choose \( -\frac{1}{2} \) as the correct answer for \( \log_{9} \left( \frac{1}{2} \right) \).

Solution

To evaluate the logarithm \( \log_{9} \left( \frac{1}{2} \right) \), we need to determine the exponent \( x \) such that: \[ 9^x = \frac{1}{2} \] Let's analyze the given options: 1. **Option 1: \( x = -\frac{1}{2} \)** Calculate \( 9^{-1/2} \): \[ 9^{-1/2} = \frac{1}{\sqrt{9}} = \frac{1}{3} \] This does not equal \( \frac{1}{2} \). 2. **Option 2: \( x = -9 \)** Calculate \( 9^{-9} \): \[ 9^{-9} = \frac{1}{9^9} \] This is an extremely small number, far less than \( \frac{1}{2} \). Neither of the provided options exactly equals \( \log_{9} \left( \frac{1}{2} \right) \). However, if we were to approximate or consider the closest option, \( -\frac{1}{2} \) is closer in magnitude to the actual value compared to \( -9 \). **Actual Calculation:** For a more precise value, we can use the change of base formula: \[ \log_{9} \left( \frac{1}{2} \right) = \frac{\log \left( \frac{1}{2} \right)}{\log 9} = \frac{-\log 2}{2\log 3} \approx -0.315 \] This value is closer to \( -\frac{1}{2} \) than to \( -9 \). **Conclusion:** Given the options, **\( -\frac{1}{2} \)** is the more appropriate choice. **Answer:** Michael should choose the answer \( -\frac{1}{2} \).

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Mind Expander

To evaluate \( \log_{9} \frac{1}{2} \), Michael can use the change of base formula. He can convert it to base 3, since \( 9 = 3^2 \), leading to \( \log_{9} \frac{1}{2} = \frac{\log_{3} \frac{1}{2}}{\log_{3} 9} = \frac{\log_{3} \frac{1}{2}}{2} \). Since \( \log_{3} \frac{1}{2} \) is negative, the entire expression will indeed yield a value of \( -\frac{1}{2} \). As a fun fact, logarithms are typically used in various fields such as computing and music. For example, in computing, logarithmic scales help to measure complexity in algorithms, while in music, the logarithmic nature of sound intensity helps us calculate decibels. So whether you're debugging your code or jamming out to tunes, logarithms are secretly at work!

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