Exponential Functions Definition of Exponential Function: The exponential function with base a a a is defined for all real numbers x x x by:f ( x ) = a x f(x) = a^x f ( x ) = a x
where a > 0 a > 0 a > 0 and a ≠ 1 a \neq 1 a = 1 .
Characteristics and Rate of Growth: Exponential functions feature an independent variable in the exponent. To illustrate how rapidly these function values increase, consider f ( x ) = 2 x f(x) = 2^x f ( x ) = 2 x :
f ( 3 ) = 2 3 = 8 f(3) = 2^3 = 8 f ( 3 ) = 2 3 = 8 f ( 10 ) = 2 10 = 1024 f(10) = 2^{10} = 1024 f ( 10 ) = 2 10 = 1024 f ( 30 ) = 2 30 = 1 , 073 , 741 , 824 f(30) = 2^{30} = 1,073,741,824 f ( 30 ) = 2 30 = 1 , 073 , 741 , 824 Irrational Exponents: To define a x a^x a x when x x x is an irrational number, x x x is approximated by rational numbers.
For example, since 3 ≈ 1.73205 … \sqrt{3} \approx 1.73205\dots 3 ≈ 1.73205 … is an irrational number, a 3 a^{\sqrt{3}} a 3 is successively approximated using rational powers: a 1.7 , a 1.73 , a 1.732 , a 1.7320 , a 1.73205 , … a^{1.7}, a^{1.73}, a^{1.732}, a^{1.7320}, a^{1.73205}, \dots a 1.7 , a 1.73 , a 1.732 , a 1.7320 , a 1.73205 , …
Evaluating 5 3 5^{\sqrt{3}} 5 3 using calculator approximations: 5 3 ≈ 5 1.732 ≈ 16.2411 … 5^{\sqrt{3}} \approx 5^{1.732} \approx 16.2411\dots 5 3 ≈ 5 1.732 ≈ 16.2411 …
Using more decimal places of 3 \sqrt{3} 3 yields a more precise approximation of 5 3 5^{\sqrt{3}} 5 3 .
Evaluating Exponential Functions: For f ( x ) = 3 x f(x) = 3^x f ( x ) = 3 x , specific function evaluations yield:
f ( 5 ) = 3 5 = 243 f(5) = 3^5 = 243 f ( 5 ) = 3 5 = 243 (Calculator keystrokes: 3 ^ 5 ENTER ; Output: 243)
f ( − 2 3 ) = 3 − 2 / 3 ≈ 0.4807 f\left(-\frac{2}{3}\right) = 3^{-2/3} \approx 0.4807 f ( − 3 2 ) = 3 − 2/3 ≈ 0.4807 (Calculator keystrokes: 3 ^ ( (-) 2 ÷ 3 ) ENTER ; Output: 0.4807498)
f ( π ) = 3 π ≈ 31.544 f(\pi) = 3^{\pi} \approx 31.544 f ( π ) = 3 π ≈ 31.544 (Calculator keystrokes: 3 ^ π ENTER ; Output: 31.5442807)
f ( 2 ) = 3 2 ≈ 4.7288 f(\sqrt{2}) = 3^{\sqrt{2}} \approx 4.7288 f ( 2 ) = 3 2 ≈ 4.7288 (Calculator keystrokes: 3 ^ √ 2 ENTER ; Output: 4.7288043)
Graphs of Exponential Functions:
Graphing f ( x ) = 3 x f(x) = 3^x f ( x ) = 3 x and g ( x ) = ( 1 3 ) x g(x) = \left(\frac{1}{3}\right)^x g ( x ) = ( 3 1 ) x by plotting points:
| x x x | f ( x ) = 3 x f(x) = 3^x f ( x ) = 3 x | g ( x ) = ( 1 3 ) x g(x) = \left(\frac{1}{3}\right)^x g ( x ) = ( 3 1 ) x |
| :---: | :---: | :---: |
| − 3 -3 − 3 | 1 27 \frac{1}{27} 27 1 | 27 27 27 |
| − 2 -2 − 2 | 1 9 \frac{1}{9} 9 1 | 9 9 9 |
| − 1 -1 − 1 | 1 3 \frac{1}{3} 3 1 | 3 3 3 |
| 0 0 0 | 1 1 1 | 1 1 1 |
| 1 1 1 | 3 3 3 | 1 3 \frac{1}{3} 3 1 |
| 2 2 2 | 9 9 9 | 1 9 \frac{1}{9} 9 1 |
| 3 3 3 | 27 27 27 | 1 27 \frac{1}{27} 27 1 |
Compound Interest Derivation of the Compound Interest Formula: If an amount of money P P P (the principal) is invested at an interest rate i i i per time period, the interest after one time period is P i Pi P i , and the total amount A A A is: A = P + P i = P ( 1 + i ) A = P + Pi = P(1 + i) A = P + P i = P ( 1 + i )
If the interest is reinvested, the new principal is P ( 1 + i ) P(1 + i) P ( 1 + i ) . The amount after a second time period is: A = P ( 1 + i ) ( 1 + i ) = P ( 1 + i ) 2 A = P(1 + i)(1 + i) = P(1 + i)^2 A = P ( 1 + i ) ( 1 + i ) = P ( 1 + i ) 2
After a third time period, the amount is: A = P ( 1 + i ) 3 A = P(1 + i)^3 A = P ( 1 + i ) 3
In general, after k k k time periods, the amount is: A = P ( 1 + i ) k A = P(1 + i)^k A = P ( 1 + i ) k
This represents an exponential function with base ( 1 + i ) (1 + i) ( 1 + i ) .
General Compound Interest Formula: If the annual interest rate is r r r and interest is compounded n n n times per year, the rate per time period is i = r n i = \frac{r}{n} i = n r , and the number of periods in t t t years is n t nt n t : A ( t ) = P ( 1 + r n ) n t A(t) = P\left(1 + \frac{r}{n}\right)^{nt} A ( t ) = P ( 1 + n r ) n t
| Compounding | n n n | Amount after 3 years |
| :--- | :---: | :--- |
| Annual | 1 1 1 | 1000 ( 1 + 0.12 1 ) 1 ( 3 ) = $ 1404.93 1000\left(1 + \frac{0.12}{1}\right)^{1(3)} = \$1404.93 1000 ( 1 + 1 0.12 ) 1 ( 3 ) = $1404.93 |
| Semiannual | 2 2 2 | 1000 ( 1 + 0.12 2 ) 2 ( 3 ) = $ 1418.52 1000\left(1 + \frac{0.12}{2}\right)^{2(3)} = \$1418.52 1000 ( 1 + 2 0.12 ) 2 ( 3 ) = $1418.52 |
| Quarterly | 4 4 4 | 1000 ( 1 + 0.12 4 ) 4 ( 3 ) = $ 1425.76 1000\left(1 + \frac{0.12}{4}\right)^{4(3)} = \$1425.76 1000 ( 1 + 4 0.12 ) 4 ( 3 ) = $1425.76 |
| Monthly | 12 12 12 | 1000 ( 1 + 0.12 12 ) 12 ( 3 ) = $ 1430.77 1000\left(1 + \frac{0.12}{12}\right)^{12(3)} = \$1430.77 1000 ( 1 + 12 0.12 ) 12 ( 3 ) = $1430.77 |
| Daily | 365 365 365 | 1000 ( 1 + 0.12 365 ) 365 ( 3 ) = $ 1433.24 1000\left(1 + \frac{0.12}{365}\right)^{365(3)} = \$1433.24 1000 ( 1 + 365 0.12 ) 365 ( 3 ) = $1433.24 |
The Natural Exponential Function Definition of the Number e e e : The number e e e is defined as the limiting value that the expression ( 1 + 1 n ) n \left(1 + \frac{1}{n}\right)^n ( 1 + n 1 ) n approaches as n n n becomes arbitrarily large. | n n n | ( 1 + 1 n ) n \left(1 + \frac{1}{n}\right)^n ( 1 + n 1 ) n |
| :---: | :---: |
| 1 1 1 | 2.00000 2.00000 2.00000 |
| 5 5 5 | 2.48832 2.48832 2.48832 |
| 10 10 10 | 2.59374 2.59374 2.59374 |
| 100 100 100 | 2.70481 2.70481 2.70481 |
| 1000 1000 1000 | 2.71692 2.71692 2.71692 |
| 10 , 000 10,000 10 , 000 | 2.71815 2.71815 2.71815 |
| 100 , 000 100,000 100 , 000 | 2.71827 2.71827 2.71827 |
| 1 , 000 , 000 1,000,000 1 , 000 , 000 | 2.71828 2.71828 2.71828 |
Rounded to 5 decimal places: e ≈ 2.71828 e \approx 2.71828 e ≈ 2.71828 .
Rounded to 20 decimal places: e ≈ 2.71828182845904523536 e \approx 2.71828182845904523536 e ≈ 2.71828182845904523536 .
The number e e e is an irrational number; its exact value cannot be written in decimal form.
The Natural Exponential Function: Defined as the exponential function with base e e e :
f ( x ) = e x f(x) = e^x f ( x ) = e x
Since 2 < e < 3 2 < e < 3 2 < e < 3 , the graph of y = e x y = e^x y = e x lies strictly between the graphs of y = 2 x y = 2^x y = 2 x and y = 3 x y = 3^x y = 3 x
Exponential Model for the Spread of a Virus: In a city of population 10 , 000 10,000 10 , 000 , the number of infected people after t t t days is modeled by: v ( t ) = 10 , 000 5 + 1245 e − 0.97 t v(t) = \frac{10,000}{5 + 1245e^{-0.97t}} v ( t ) = 5 + 1245 e − 0.97 t 10 , 000
Initial infected count (t = 0 t = 0 t = 0 ): v ( 0 ) = 10 , 000 5 + 1245 e 0 = 10 , 000 1250 = 8 people v(0) = \frac{10,000}{5 + 1245e^0} = \frac{10,000}{1250} = 8\text{ people} v ( 0 ) = 5 + 1245 e 0 10 , 000 = 1250 10 , 000 = 8 people
Infections over time:After 1 day (t = 1 t = 1 t = 1 ): 21 people 21\text{ people} 21 people After 2 days (t = 2 t = 2 t = 2 ): 54 people 54\text{ people} 54 people After 5 days (t = 5 t = 5 t = 5 ): 678 people 678\text{ people} 678 people Graphical behavior: The number of infected individuals rises slowly initially, increases rapidly between Day 3 and Day 8, and then levels off near 2000 people 2000\text{ people} 2000 people .
Continuously Compounded Interest: As the compounding frequency n → ∞ n \to \infty n → ∞ , let m = n r m = \frac{n}{r} m = r n . The compound interest formula transforms as follows: A ( t ) = P ( 1 + r n ) n t = P [ ( 1 + r n ) n / r ] r t = P [ ( 1 + 1 m ) m ] r t A(t) = P\left(1 + \frac{r}{n}\right)^{nt} = P\left[\left(1 + \frac{r}{n}\right)^{n/r}\right]^{rt} = P\left[\left(1 + \frac{1}{m}\right)^m\right]^{rt} A ( t ) = P ( 1 + n r ) n t = P [ ( 1 + n r ) n / r ] r t = P [ ( 1 + m 1 ) m ] r t
Since ( 1 + 1 m ) m → e \left(1 + \frac{1}{m}\right)^m \to e ( 1 + m 1 ) m → e as m → ∞ m \to \infty m → ∞ , the amount compounded at "every instant" is given by: A ( t ) = P e r t A(t) = Pe^{rt} A ( t ) = P e r t
Example: For P = $ 1000 P = \$1000 P = $1000 , r = 0.12 r = 0.12 r = 0.12 (12 % 12\% 12% ), and t = 3 t = 3 t = 3 years compounded continuously: A ( 3 ) = 1000 e ( 0.12 ) ( 3 ) = 1000 e 0.36 ≈ $ 1433.33 A(3) = 1000e^{(0.12)(3)} = 1000e^{0.36} \approx \$1433.33 A ( 3 ) = 1000 e ( 0.12 ) ( 3 ) = 1000 e 0.36 ≈ $1433.33
Logarithmic Functions Definition of Logarithmic Functions: Every exponential function f ( x ) = a x f(x) = a^x f ( x ) = a x (a > 0 , a ≠ 1 a > 0, a \neq 1 a > 0 , a = 1 ) passes the Horizontal Line Test and is one-to-one, possessing an inverse function f − 1 f^{-1} f − 1 . The inverse function f − 1 f^{-1} f − 1 is the logarithmic function with base a a a , denoted log a \log_a log a : f − 1 ( x ) = y ⟺ f ( y ) = x f^{-1}(x) = y \iff f(y) = x f − 1 ( x ) = y ⟺ f ( y ) = x
log a x = y ⟺ a y = x \log_a x = y \iff a^y = x log a x = y ⟺ a y = x
log a x \log_a x log a x is the exponent to which the base a a a must be raised to produce x x x .
Logarithmic form: log a x = y \log_a x = y log a x = y
Exponential form: a y = x a^y = x a y = x
Both forms share the exact same base a a a .
| Logarithmic Form | Exponential Form |
| :--- | :--- |
| log 10 100 , 000 = 5 \log_{10} 100,000 = 5 log 10 100 , 000 = 5 | 10 5 = 100 , 000 10^5 = 100,000 1 0 5 = 100 , 000 |
| log 2 8 = 3 \log_2 8 = 3 log 2 8 = 3 | 2 3 = 8 2^3 = 8 2 3 = 8 |
| log 2 ( 1 8 ) = − 3 \log_2\left(\frac{1}{8}\right) = -3 log 2 ( 8 1 ) = − 3 | 2 − 3 = 1 8 2^{-3} = \frac{1}{8} 2 − 3 = 8 1 |
| log 5 s = r \log_5 s = r log 5 s = r | 5 r = s 5^r = s 5 r = s |
Evaluating Logarithms Examples:
log 10 1000 = 3 \log_{10} 1000 = 3 log 10 1000 = 3 because 10 3 = 1000 10^3 = 1000 1 0 3 = 1000 log 2 32 = 5 \log_2 32 = 5 log 2 32 = 5 because 2 5 = 32 2^5 = 32 2 5 = 32 log 10 0.1 = − 1 \log_{10} 0.1 = -1 log 10 0.1 = − 1 because 10 − 1 = 0.1 10^{-1} = 0.1 1 0 − 1 = 0.1 log 16 4 = 1 2 \log_{16} 4 = \frac{1}{2} log 16 4 = 2 1 because 16 1 / 2 = 4 16^{1/2} = 4 1 6 1/2 = 4 Properties of Logarithms:
log a 1 = 0 \log_a 1 = 0 log a 1 = 0 (Reason: a 0 = 1 a^0 = 1 a 0 = 1 )log a a = 1 \log_a a = 1 log a a = 1 (Reason: a 1 = a a^1 = a a 1 = a )log a ( a x ) = x \log_a(a^x) = x log a ( a x ) = x for all x ∈ R x \in \mathbb{R} x ∈ R (Reason: a a a must be raised to power x x x to get a x a^x a x )a log a x = x a^{\log_a x} = x a l o g a x = x for all x > 0 x > 0 x > 0 (Reason: log a x \log_a x log a x is the power to which a a a must be raised to get x x x )Graphs, Domain, and Range of Logarithmic Functions:
For f ( x ) = a x f(x) = a^x f ( x ) = a x (a > 1 a > 1 a > 1 ), Domain = R \mathbb{R} R and Range = ( 0 , ∞ ) (0, \infty) ( 0 , ∞ ) . For f − 1 ( x ) = log a x f^{-1}(x) = \log_a x f − 1 ( x ) = log a x , Domain = ( 0 , ∞ ) (0, \infty) ( 0 , ∞ ) and Range = R \mathbb{R} R . The graph of y = log a x y = \log_a x y = log a x is obtained by reflecting y = a x y = a^x y = a x across the line y = x y = x y = x . The x x x -intercept is 1 1 1 (since log a 1 = 0 \log_a 1 = 0 log a 1 = 0 ). The y y y -axis (x = 0 x = 0 x = 0 ) is a vertical asymptote because log a x → − ∞ \log_a x \to -\infty log a x → − ∞ as x → 0 + x \to 0^+ x → 0 + .
Common Logarithms: The logarithm with base 10 10 10 is called the common logarithm and is denoted by omitting the base: log x = log 10 x \log x = \log_{10} x log x = log 10 x
Key values: log 10 = 1 \log 10 = 1 log 10 = 1 , log 100 = 2 \log 100 = 2 log 100 = 2 .
Approximating log 50 \log 50 log 50 : Since 10 1 = 10 10^1 = 10 1 0 1 = 10 and 10 2 = 100 10^2 = 100 1 0 2 = 100 , 1 < log 50 < 2 1 < \log 50 < 2 1 < log 50 < 2 .
Logarithmic Scales Application (Sound Loudness): Loudness B B B in decibels (dB) of a sound with physical intensity I I I (in W/m 2 \text{W/m}^2 W/m 2 ) is modeled by:
B = 10 log ( I I 0 ) B = 10\log\left(\frac{I}{I_0}\right) B = 10 log ( I 0 I )
where I 0 I_0 I 0 is the intensity of a barely audible sound.
Decibel level for a sound with intensity I = 100 I 0 I = 100I_0 I = 100 I 0 : B = 10 log ( 100 I 0 I 0 ) = 10 log ( 100 ) = 10 × 2 = 20 dB B = 10\log\left(\frac{100I_0}{I_0}\right) = 10\log(100) = 10 \times 2 = 20\text{ dB} B = 10 log ( I 0 100 I 0 ) = 10 log ( 100 ) = 10 × 2 = 20 dB
Natural Logarithms: Logarithm with base e e e is called the natural logarithm and is denoted by ln \ln ln : ln x = log e x \ln x = \log_e x ln x = log e x
ln x = y ⟺ e y = x \ln x = y \iff e^y = x ln x = y ⟺ e y = x
Properties of Natural Logarithms: ln 1 = 0 \ln 1 = 0 ln 1 = 0 ln e = 1 \ln e = 1 ln e = 1 ln e x = x \ln e^x = x ln e x = x e ln x = x e^{\ln x} = x e l n x = x
Finding the Domain of a Logarithmic Function Example: Find the domain of f ( x ) = ln ( 4 − x 2 ) f(x) = \ln(4 - x^2) f ( x ) = ln ( 4 − x 2 ) . Solution: ln x \ln x ln x is defined only when its input is strictly positive: { x ∣ 4 − x 2 > 0 } = { x ∣ x 2 < 4 } = { x ∣ ∣ x ∣ < 2 } = { x ∣ − 2 < x < 2 } = ( − 2 , 2 ) \{x \mid 4 - x^2 > 0\} = \{x \mid x^2 < 4\} = \{x \mid |x| < 2\} = \{x \mid -2 < x < 2\} = (-2, 2) { x ∣ 4 − x 2 > 0 } = { x ∣ x 2 < 4 } = { x ∣ ∣ x ∣ < 2 } = { x ∣ − 2 < x < 2 } = ( − 2 , 2 )
Laws of Logarithms log a ( A B ) = log a ( a u a v ) = log a ( a u + v ) = u + v = log a A + log a B \log_a(AB) = \log_a(a^u a^v) = \log_a(a^{u+v}) = u + v = \log_a A + \log_a B log a ( A B ) = log a ( a u a v ) = log a ( a u + v ) = u + v = log a A + log a B
Proof of Law 2: Using Law 1:log a A = log a [ ( A B ) B ] = log a ( A B ) + log a B \log_a A = \log_a\left[\left(\frac{A}{B}\right)B\right] = \log_a\left(\frac{A}{B}\right) + \log_a B log a A = log a [ ( B A ) B ] = log a ( B A ) + log a B
log a ( A B ) = log a A − log a B \log_a\left(\frac{A}{B}\right) = \log_a A - \log_a B log a ( B A ) = log a A − log a B
Proof of Law 3: Let u = log a A u = \log_a A u = log a A , so a u = A a^u = A a u = A . Thus:log a ( A C ) = log a ( ( a u ) C ) = log a ( a u C ) = u C = C log a A \log_a(A^C) = \log_a\left((a^u)^C\right) = \log_a(a^{uC}) = uC = C\log_a A log a ( A C ) = log a ( ( a u ) C ) = log a ( a u C ) = u C = C log a A
Evaluating Expressions Using Laws of Logarithms Examples:
log 4 2 + log 4 32 = log 4 ( 2 ⋅ 32 ) = log 4 64 = 3 \log_4 2 + \log_4 32 = \log_4(2 \cdot 32) = \log_4 64 = 3 log 4 2 + log 4 32 = log 4 ( 2 ⋅ 32 ) = log 4 64 = 3 (since 4 3 = 64 4^3 = 64 4 3 = 64 )log 2 80 − log 2 5 = log 2 ( 80 5 ) = log 2 16 = 4 \log_2 80 - \log_2 5 = \log_2\left(\frac{80}{5}\right) = \log_2 16 = 4 log 2 80 − log 2 5 = log 2 ( 5 80 ) = log 2 16 = 4 (since 2 4 = 16 2^4 = 16 2 4 = 16 )− 1 3 log 8 = log ( 8 − 1 / 3 ) = log ( 1 2 ) ≈ − 0.301 -\frac{1}{3}\log 8 = \log(8^{-1/3}) = \log\left(\frac{1}{2}\right) \approx -0.301 − 3 1 log 8 = log ( 8 − 1/3 ) = log ( 2 1 ) ≈ − 0.301 Expanding Logarithmic Expressions Examples:
log 2 ( 6 x ) = log 2 6 + log 2 x \log_2(6x) = \log_2 6 + \log_2 x log 2 ( 6 x ) = log 2 6 + log 2 x log 5 ( x 3 y 6 ) = log 5 x 3 + log 5 y 6 = 3 log 5 x + 6 log 5 y \log_5(x^3 y^6) = \log_5 x^3 + \log_5 y^6 = 3\log_5 x + 6\log_5 y log 5 ( x 3 y 6 ) = log 5 x 3 + log 5 y 6 = 3 log 5 x + 6 log 5 y ln ( a b c 3 ) = ln ( a b ) − ln c 3 = ln a + ln b − ln ( c 1 / 3 ) = ln a + ln b − 1 3 ln c \ln\left(\frac{ab}{\sqrt[3]{c}}\right) = \ln(ab) - \ln \sqrt[3]{c} = \ln a + \ln b - \ln(c^{1/3}) = \ln a + \ln b - \frac{1}{3}\ln c ln ( 3 c ab ) = ln ( ab ) − ln 3 c = ln a + ln b − ln ( c 1/3 ) = ln a + ln b − 3 1 ln c Psychological Application (The Law of Forgetting):
Formulated by Hermann Ebbinghaus (1850–1909): log P = log P 0 − c log ( t + 1 ) \log P = \log P_0 - c\log(t + 1) log P = log P 0 − c log ( t + 1 )
where P 0 P_0 P 0 is the initial performance score, P P P is the retained performance level after t t t months, and c c c is a task-dependent constant.
Solving for P P P algebraically: log P = log P 0 − log ( t + 1 ) c \log P = \log P_0 - \log(t + 1)^c log P = log P 0 − log ( t + 1 ) c
log P = log ( P 0 ( t + 1 ) c ) \log P = \log\left(\frac{P_0}{(t + 1)^c}\right) log P = log ( ( t + 1 ) c P 0 )
P = P 0 ( t + 1 ) c P = \frac{P_0}{(t + 1)^c} P = ( t + 1 ) c P 0
Calculations for P 0 = 90 P_0 = 90 P 0 = 90 and c = 0.2 c = 0.2 c = 0.2 :After 2 months (t = 2 t = 2 t = 2 ): P = 90 ( 2 + 1 ) 0.2 = 90 3 0.2 ≈ 72 P = \frac{90}{(2 + 1)^{0.2}} = \frac{90}{3^{0.2}} \approx 72 P = ( 2 + 1 ) 0.2 90 = 3 0.2 90 ≈ 72
- After 1 year (t = 12 t = 12 t = 12 ):
P = 90 ( 12 + 1 ) 0.2 = 90 13 0.2 ≈ 54 P = \frac{90}{(12 + 1)^{0.2}} = \frac{90}{13^{0.2}} \approx 54 P = ( 12 + 1 ) 0.2 90 = 1 3 0.2 90 ≈ 54
Change of Base Formula: Derivation: To convert log b x \log_b x log b x to base a a a , let y = log b x y = \log_b x y = log b x . Express in exponential form b y = x b^y = x b y = x , take log a \log_a log a of both sides, apply Law 3, and solve for y y y : log a ( b y ) = log a x \log_a(b^y) = \log_a x log a ( b y ) = log a x
y log a b = log a x y\log_a b = \log_a x y log a b = log a x
y = log a x log a b y = \frac{\log_a x}{\log_a b} y = l o g a b l o g a x
log b x = log a x log a b \log_b x = \frac{\log_a x}{\log_a b} log b x = l o g a b l o g a x
Special Case (x = a x = a x = a ): log b a = 1 log a b \log_b a = \frac{1}{\log_a b} log b a = l o g a b 1
Change of Base Examples:Evaluate log 8 5 \log_8 5 log 8 5 using common logarithms (a = 10 a = 10 a = 10 ): log 8 5 = log 10 5 log 10 8 ≈ 0.77398 \log_8 5 = \frac{\log_{10} 5}{\log_{10} 8} \approx 0.77398 log 8 5 = l o g 10 8 l o g 10 5 ≈ 0.77398
- Evaluate log 9 20 \log_9 20 log 9 20 using natural logarithms (a = e a = e a = e ):
log 9 20 = ln 20 ln 9 ≈ 1.36342 \log_9 20 = \frac{\ln 20}{\ln 9} \approx 1.36342 log 9 20 = l n 9 l n 20 ≈ 1.36342
Exponential and Logarithmic Equations Solving Exponential Equations Using the One-to-One Property: Since f ( x ) = a x f(x) = a^x f ( x ) = a x is one-to-one, a x = a y ⟺ x = y a^x = a^y \iff x = y a x = a y ⟺ x = y Example 1(a): Solve 5 x = 125 5^x = 125 5 x = 125 5 x = 5 3 ⟹ x = 3 5^x = 5^3 \implies x = 3 5 x = 5 3 ⟹ x = 3
Example 1(b): Solve 5 2 x = 5 x + 1 5^{2x} = 5^{x+1} 5 2 x = 5 x + 1 2 x = x + 1 ⟹ x = 1 2x = x + 1 \implies x = 1 2 x = x + 1 ⟹ x = 1
log ( 3 x + 2 ) = log 7 \log(3^{x+2}) = \log 7 log ( 3 x + 2 ) = log 7
( x + 2 ) log 3 = log 7 (x + 2)\log 3 = \log 7 ( x + 2 ) log 3 = log 7
x + 2 = log 7 log 3 x + 2 = \frac{\log 7}{\log 3} x + 2 = l o g 3 l o g 7
x = log 7 log 3 − 2 ( Exact solution ) x = \frac{\log 7}{\log 3} - 2 \quad (\text{Exact solution}) x = l o g 3 l o g 7 − 2 ( Exact solution )
- Calculator approximation: x ≈ − 0.228756 x \approx -0.228756 x ≈ − 0.228756 Example 3: Solve 8 e 2 x = 20 8e^{2x} = 20 8 e 2 x = 20 Isolate exponential term by dividing by 8: e 2 x = 20 8 = 2.5 e^{2x} = \frac{20}{8} = 2.5 e 2 x = 8 20 = 2.5
ln ( e 2 x ) = ln 2.5 \ln(e^{2x}) = \ln 2.5 ln ( e 2 x ) = ln 2.5
2 x = ln 2.5 2x = \ln 2.5 2 x = ln 2.5
x = ln 2.5 2 ≈ 0.458 x = \frac{\ln 2.5}{2} \approx 0.458 x = 2 l n 2.5 ≈ 0.458
Example 4: Solve e 3 − 2 x = 4 e^{3-2x} = 4 e 3 − 2 x = 4 ln ( e 3 − 2 x ) = ln 4 \ln(e^{3-2x}) = \ln 4 ln ( e 3 − 2 x ) = ln 4
3 − 2 x = ln 4 3 - 2x = \ln 4 3 − 2 x = ln 4
− 2 x = − 3 + ln 4 -2x = -3 + \ln 4 − 2 x = − 3 + ln 4
x = 1 2 ( 3 − ln 4 ) ≈ 0.807 x = \frac{1}{2}(3 - \ln 4) \approx 0.807 x = 2 1 ( 3 − ln 4 ) ≈ 0.807
- Graphical Solution: Graph y = e 3 − 2 x y = e^{3-2x} y = e 3 − 2 x and y = 4 y = 4 y = 4 . The intersection point gives x ≈ 0.81 x \approx 0.81 x ≈ 0.81 .
Example 5 (Quadratic Type): Solve e 2 x − e x − 6 = 0 e^{2x} - e^x - 6 = 0 e 2 x − e x − 6 = 0 Rewrite and factor quadratic in e x e^x e x : ( e x ) 2 − e x − 6 = 0 (e^x)^2 - e^x - 6 = 0 ( e x ) 2 − e x − 6 = 0
( e x − 3 ) ( e x + 2 ) = 0 (e^x - 3)(e^x + 2) = 0 ( e x − 3 ) ( e x + 2 ) = 0
- Zero-Product Property:
e x − 3 = 0 ⟹ e x = 3 ⟹ x = ln 3 ≈ 1.0986 e^x - 3 = 0 \implies e^x = 3 \implies x = \ln 3 \approx 1.0986 e x − 3 = 0 ⟹ e x = 3 ⟹ x = ln 3 ≈ 1.0986
e x + 2 = 0 ⟹ e x = − 2 ( No solution because e x > 0 for all x ) e^x + 2 = 0 \implies e^x = -2 \quad (\text{No solution because } e^x > 0 \text{ for all } x) e x + 2 = 0 ⟹ e x = − 2 ( No solution because e x > 0 for all x )
- The only valid solution is x = ln 3 ≈ 1.0986 x = \ln 3 \approx 1.0986 x = ln 3 ≈ 1.0986 Example 6 (Factoring Common Terms): Solve 3 x e x + x 2 e x = 0 3xe^x + x^2e^x = 0 3 x e x + x 2 e x = 0 x ( 3 + x ) e x = 0 x(3 + x)e^x = 0 x ( 3 + x ) e x = 0
- Divide by e x e^x e x (since e x ≠ 0 e^x \neq 0 e x = 0 for all real x x x ):
x ( 3 + x ) = 0 x(3 + x) = 0 x ( 3 + x ) = 0
- Solutions: x = 0 x = 0 x = 0 and x = − 3 x = -3 x = − 3 Solving Logarithmic Equations: Logarithmic functions are one-to-one: log a x = log a y ⟹ x = y \log_a x = \log_a y \implies x = y log a x = log a y ⟹ x = y
Example 7: Solve log 5 ( x 2 + 1 ) = log 5 ( x − 2 ) + log 5 ( x + 3 ) \log_5(x^2 + 1) = \log_5(x - 2) + \log_5(x + 3) log 5 ( x 2 + 1 ) = log 5 ( x − 2 ) + log 5 ( x + 3 ) Combine right-hand side using Law 1: log 5 ( x 2 + 1 ) = log 5 [ ( x − 2 ) ( x + 3 ) ] \log_5(x^2 + 1) = \log_5[(x - 2)(x + 3)] log 5 ( x 2 + 1 ) = log 5 [( x − 2 ) ( x + 3 )]
log 5 ( x 2 + 1 ) = log 5 ( x 2 + x − 6 ) \log_5(x^2 + 1) = \log_5(x^2 + x - 6) log 5 ( x 2 + 1 ) = log 5 ( x 2 + x − 6 )
- Apply one-to-one property:
x 2 + 1 = x 2 + x − 6 x^2 + 1 = x^2 + x - 6 x 2 + 1 = x 2 + x − 6
1 = x − 6 ⟹ x = 7 1 = x - 6 \implies x = 7 1 = x − 6 ⟹ x = 7
25 − x = 2 3 25 - x = 2^3 25 − x = 2 3
25 − x = 8 25 - x = 8 25 − x = 8
x = 25 − 8 = 17 x = 25 - 8 = 17 x = 25 − 8 = 17
Example 9: Solve 4 + 3 log ( 2 x ) = 16 4 + 3\log(2x) = 16 4 + 3 log ( 2 x ) = 16 Isolate logarithmic expression: 3 log ( 2 x ) = 12 3\log(2x) = 12 3 log ( 2 x ) = 12
log ( 2 x ) = 4 \log(2x) = 4 log ( 2 x ) = 4
- Convert to exponential form:
2 x = 10 4 2x = 10^4 2 x = 1 0 4
2 x = 10 , 000 2x = 10,000 2 x = 10 , 000
x = 5000 x = 5000 x = 5000