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Evaluate the expression without using a calculator.\(\log _{a} a^{5}\)

Short Answer

Expert verified
The result of this logarithmic expression, \(\log _{a} a^{5}\), is \(5\).

Step by step solution

01

Identify Base and Exponent

In the given expression \(\log _{a} a^{5}\), the base is \(a\) and the exponent is \(5\).
02

Apply Properties of Logarithms

According to the rule \(\log _{a} a^{n}=n\), if the base of the logarithm and the number are the same, then the result is simply the exponent. Therefore, \(\log _{a} a^{5}\) equals to \(5\).

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Key Concepts

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

Properties of Logarithms
Logarithms have several important properties that help simplify expressions and solve equations efficiently. Understanding these properties is key to mastering logarithmic expressions. One of the fundamental properties is the identity property, which states that if you have a logarithm with a base \(b\) and you are taking the logarithm of \(b^n\), the result is simply \(n\). Mathematically, it is represented as:
  • \(\log_b (b^n) = n\)
This property is crucial when bases in logarithmic and exponential forms match, allowing for direct simplification. It essentially works by reversing the process of exponentiation, stripping away the base and leaving the exponent.
Another useful property is the product property, which allows us to add logarithms when multiplying numbers:
  • \(\log_b (xy) = \log_b (x) + \log_b (y)\)
These fundamental properties can be greatly helpful when breaking down complex logarithmic expressions into more manageable parts.
Exponentiation
Exponentiation refers to the process of raising a number to the power of another number. This is a core concept in mathematics, where the number being multiplied, known as the base, is multiplied by itself a number of times indicated by the exponent. For example, in the expression \(a^5\), the base is \(a\) and the exponent is 5.
Exponentiation is shown as:
  • \(x^n\) where \(x\) is the base and \(n\) is the exponent
When we talk about logarithms, they are essentially the inverse operation of exponentiation. Logarithms help us "undo" exponentiation by finding the exponent.
Understanding exponentiation is critical when dealing with logarithms because many logarithmic properties derive from the principles of exponents, such as simplifying logarithms of products, quotients, and powers. Learning to "recognize" expressions like \(a^5\) allows us to use logarithmic properties effectively.
Evaluating Logarithmic Expressions
Evaluating logarithmic expressions involves applying properties of logarithms to simplify and find the value of a logarithmic statement. Logarithms tell us what the power is that a number must be raised to, in order to get another number. When evaluating logarithmic expressions, it often involves:
  • Recognizing the base and its corresponding exponent
  • Applying the relevant logarithmic properties to simplify the expression
  • Calculating the result, if needed, without a calculator
For instance, in the expression \(\log_{a} a^{5}\), the task is to determine "to what power must \(a\) be raised to get \(a^5\)?" The answer is simply 5, because of the identity property which states \(\log_b(b^n) = n\).
Evaluating requires practice in recognizing and applying these rules. The fewer steps one needs to compute the result, the easier it becomes to solve real world logarithmic problems. Always look out for opportunities to leverage properties like the identity property to quickly find solutions.

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Most popular questions from this chapter

Population The populations \(P\) of the United States (in thousands) from 1990 to 2005 are shown in the table. (Source: U.S. Census Bureau)$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Population } \\ \hline 1990 & 250,132 \\ \hline 1991 & 253,493 \\ \hline 1992 & 256,894 \\ \hline 1993 & 260,255 \\ \hline 1994 & 263,436 \\ \hline 1995 & 266,557 \\ \hline 1996 & 269,667 \\ \hline 1997 & 272,912 \\ \hline \end{array} $$$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Population } \\ \hline 1998 & 276,115 \\ \hline 1999 & 279,295 \\ \hline 2000 & 282,403 \\ \hline 2001 & 285,335 \\ \hline 2002 & 288,216 \\ \hline 2003 & 291,089 \\ \hline 2004 & 293,908 \\ \hline 2005 & 296,639 \\ \hline \end{array} $$(a) Use a graphing utility to create a scatter plot of the data. Let \(t\) represent the year, with \(t=0\) corresponding to 1990 . (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) Use the regression feature of a graphing utility to find a linear model and a quadratic model for the data. (d) Use a graphing utility to graph the exponential model in base \(e\) and the models in part (c) with the scatter plot. (e) Use each model to predict the populations in 2008 , 2009 , and 2010 . Do all models give reasonable predictions? Explain.

(a) \(I=10^{-3}\) watt per square meter (loud car horn) (b) \(I \approx 10^{0}\) watt per square meter (threshold of pain)

Domestic Demand The domestic demands \(D\) (in thousands of barrels) for refined oil products in the United States from 1995 to 2005 are shown in the table. (Source: U.S. Energy Information Administration)$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Demand } \\ \hline 1995 & 6,469,625 \\ \hline 1996 & 6,701,094 \\ \hline 1997 & 6,796,300 \\ \hline 1998 & 6,904,705 \\ \hline 1999 & 7,124,435 \\ \hline 2000 & 7,210,566 \\ \hline \end{array} $$$$ \begin{array}{|c|c|} \hline \text { Year } & \text { Demand } \\ \hline 2001 & 7,171,885 \\ \hline 2002 & 7,212,765 \\ \hline 2003 & 7,312,410 \\ \hline 2004 & 7,587,546 \\ \hline 2005 & 7,539,440 \\ \hline \end{array} $$(a) Use a spreadsheet software program to create a scatter plot of the data. Let \(t\) represent the year, with \(t=5\) corresponding to 1995 . (b) Use the regression feature of a spreadsheet software program 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) Use the regression feature of a spreadsheet software program to find a logarithmic model \((y=a+b \ln x)\) for the data. (d) Use a spreadsheet software program to graph the exponential model in base \(e\) and the logarithmic model with the scatter plot. (e) Use both models to predict domestic demands in 2008 , 2009, and \(2010 .\) Do both models give reasonable predictions? Explain.

The logarithm of the product of two numbers is equal to the sum of the logarithms of the numbers.

Solve the logarithmic equation algebraically. Approximate the result to three decimal places.\(5 \log _{3}(x+1)=12\)

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