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Evaluate the expression without using a calculator.\(\log _{8} 2\)

Short Answer

Expert verified
The value of \(\log_8 2\) is \(1/3\).

Step by step solution

01

Convert the Logarithm to Exponential Form

Recall that a logarithm \(\log_b a = c\) can be rewritten in exponential form as \(b^c = a\). Let's apply this to the equation \(\log_8 2\). So, if \(\log _{8} 2 = x\), we can rewrite this as \(8^x = 2\).
02

Express 8 and 2 with the same base

We can express both 8 and 2 as powers of 2. Remember 8 can be written as \(2^3\) and 2 can be written as \(2^1\). So, we can rewrite our equation as \((2^3)^x = 2^1\).
03

Solve for x

Simplify \((2^3)^x = 2^1\) to \(2^{3x} = 2^1\). In an equation of the form \(a^m = a^n\), one can say that \(m = n\). Therefore, \(3x = 1\). Solving for \(x\), we get \(x = 1/3\).

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Exponential Functions
Exponential functions are a fundamental part of mathematics, especially when dealing with growth patterns and interest calculations. An exponential function is typically in the form of \(b^x\), where \(b\) is a positive real number, known as the base, and \(x\) is any real number. The beauty of exponential functions is in how they grow—quickly and unpredictably.
  • Exponential growth: Occurs when the base \(b > 1\). If something grows exponentially, it increases rapidly at a rate proportional to its current value.
  • Exponential decay: Happens when the base \(0 < b < 1\). In this case, the value decreases rapidly.
Exponential functions are pivotal in converting logarithmic expressions into a form that can be more easily manipulated and understood. For example, converting \(\log_8 2\) into \(8^x = 2\) allows us to clearly see the underlying relationships between the numbers.
Logarithmic Properties
Logarithms are the inverse operations of exponentials. They help to "undo" an exponent. The equation \(\log_b a = c\) tells us the power \(c\) to which the base \(b\) must be raised to produce the value \(a\). Some key properties of logarithms are very useful in simplifying complex mathematical problems.
  • Product Property: \(\log_b (mn) = \log_b m + \log_b n\). Useful for combining logs.
  • Quotient Property: \(\log_b \left(\frac{m}{n}\right) = \log_b m - \log_b n\). Handy for splitting logs.
  • Power Property: \(\log_b (m^n) = n \cdot \log_b m\). Breaks exponents into multipliers.
By using the exponential form of a logarithm, as seen with the conversion in \(\log_8 2 = x\) to \(8^x = 2\), we can utilize these properties to make calculations more straightforward and achieve solutions more efficiently.
Algebraic Manipulation
Algebraic manipulation involves the skillful transformation and rearrangement of equations in order to find unknowns or to simplify expressions. In the context of logarithmic and exponential equations, this often involves changing the form of the expression to reveal hidden pathways to the solution.
In the problem \(\log_8 2 = x\), we express both terms \(8\) and \(2\) using the same base, which is 2. Recognizing that \(8 = 2^3\) allows us to rewrite \((2^3)^x = 2^1\), streamlining the problem into a simpler equivalent form, \(2^{3x} = 2^1\).
  • Common principles include the use of equivalent expressions to simplify equations.
  • Match bases when dealing with exponential terms to directly equate the exponents.
  • Solving for unknown variables becomes an easier task once the expressions are simplified.
Algebraic manipulation is thus fundamental in breaking down complex mathematical problems into understandable and solvable parts.

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Most popular questions from this chapter

Use a graphing utility to solve the equation. Approximate the result to three decimal places. Verify your result algebraically.\(2^{x}-7=0\)

Solve the logarithmic equation algebraically. Approximate the result to three decimal places.\(\ln x+\ln (x-2)=1\)

Solve the exponential equation algebraically. Approximate the result to three decimal places.\(\frac{119}{e^{6 x}-14}=7\)

Automobiles are designed with crumple zones that help protect their occupants in crashes. The crumple zones allow the occupants to move short distances when the automobiles come to abrupt stops. The greater the distance moved, the fewer g's the crash victims experience. (One \(\mathrm{g}\) is equal to the acceleration due to gravity. For very short periods of time, humans have withstood as much as 40 g's.) In crash tests with vehicles moving at 90 kilometers per hour, analysts measured the numbers of g's experienced during deceleration by crash dummies that were permitted to move \(x\) meters during impact. The data are shown in the table. $$ \begin{array}{|l|l|l|l|l|l|} \hline x & 0.2 & 0.4 & 0.6 & 0.8 & 1.0 \\ \hline g \text { 's } & 158 & 80 & 53 & 40 & 32 \\ \hline \end{array} $$A model for these data is given by \(y=-3.00+11.88 \ln x+\frac{36.94}{x}\) where \(y\) is the number of g's. (a) Complete the table using the model.$$ \begin{array}{|l|l|l|l|l|l|} \hline x & 0.2 & 0.4 & 0.6 & 0.8 & 1.0 \\ \hline y & & & & & \\ \hline \end{array} $$(b) Use a graphing utility to graph the data points and the model in the same viewing window. How do they compare? (c) Use the model to estimate the least distance traveled during impact for which the passenger does not experience more than \(30 \mathrm{~g}\) 's. (d) Do you think it is practical to lower the number of g's experienced during impact to fewer than 23 ? Explain your reasoning.

Population The population \(P\) of the United States officially reached 300 million at about 7:46 A.M. E.S.T. on Tuesday, October 17,2006 . The table shows the U.S. populations (in millions) since 1900. (Source: U.S. Census Bureau)$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Population } \\ \hline 1900 & 76 \\ \hline 1910 & 92 \\ \hline 1920 & 106 \\ \hline 1930 & 123 \\ \hline 1940 & 132 \\ \hline 1950 & 151 \\ \hline \end{array} $$$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Population } \\ \hline 1960 & 179 \\ \hline 1970 & 203 \\ \hline 1980 & 227 \\ \hline 1990 & 250 \\ \hline 2000 & 282 \\ \hline 2006 & 300 \\ \hline \end{array} $$(a) Use a graphing utility to create a scatter plot of the data. Let \(t\) represent the year, with \(t=0\) corresponding to 1900 . (b) Use the regression feature of a graphing utility to find an exponential model for the data. Use the Inverse Property \(b=e^{\ln b}\) to rewrite the model as an exponential model in base \(e\). (c) Graph the exponential model in base \(e\) with the scatter plot of the data. What appears to be happening to the relationship between the data points and the regression curve at \(t=100\) and \(t=106 ?\) (d) Use the regression feature of a graphing utility to find a logistic growth model for the data. Graph each model using the window settings shown below. Which model do you think will give more accurate predictions of the population well beyond \(2006 ?\)

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