πŸ“Œ When Is a Log Model Appropriate?

A logarithmic model is appropriate when data shows a large initial rate of change that gradually decreases β€” rapid growth at first, then slowing down. Real-world examples: salaries, earthquakes (Richter scale), sound (decibels), acidity (pH).

Key signal in a table: If the input values appear to change proportionally (multiplicatively) over equal-length output value intervals, then a logarithmic model is appropriate. (This is the reverse of what we look for in an exponential model.)
y = a + b ln x   or   y = a + b log x

where a and b are constants and b β‰  0. Use ln for natural base models, log for base-10 models.

1
Substitute each (x, y) data point into the model to get two equations
2
Subtract one equation from the other to eliminate a
3
Solve for b using log properties (factor out b)
4
Back-substitute to find a

L(x) = a + b ln x   with L(2) = 3 and L(5) = 7

xL(x)
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Step 1 β€” Write two equations:
L(2) = a + b ln 2 = 3
L(5) = a + b ln 5 = 7

Step 2 β€” Subtract to eliminate a:
(a + b ln 5) βˆ’ (a + b ln 2) = 7 βˆ’ 3
b(ln 5 βˆ’ ln 2) = 4

Step 3 β€” Solve for b:
b = 4 / (ln 5 βˆ’ ln 2) = 4 / ln(5/2) β‰ˆ 4.3654

Step 4 β€” Back-substitute for a:
a = 3 βˆ’ b ln 2 β‰ˆ 3 βˆ’ (4.3654)(0.6931) β‰ˆ βˆ’0.0258

S(p) = a + b ln p β€” Church Size vs Average Salary

Church Size (p)75120250300450650900150025005000
Avg Salary ($1000s)425870798895110125138175
(a) Regression on calculator (LnReg):  a β‰ˆ βˆ’91.54   b β‰ˆ 29.91
S(p) = βˆ’91.54 + 29.91 ln p

(b) Predicted salary for church size 500:
S(500) = βˆ’91.54 + 29.91 ln(500) β‰ˆ $94,330 (β‰ˆ 94.3 thousand dollars)
Calculator steps: Enter data in L1 and L2 β†’ STAT β†’ CALC β†’ 9:LnReg β†’ Enter L1, L2, Y₁ β†’ Calculate

Ξ²(I) = a + b log(I) β€” Sound Intensity Model

Noisy traffic: I = 1Γ—10⁻⁡ W/mΒ² β†’ 70 dB. Loud concert: I = 1 W/mΒ² β†’ 120 dB.

Step 1 β€” Write two equations:
Ξ²(1Γ—10⁻⁡) = a + b log(10⁻⁡) = a + b(βˆ’5) = 70
Ξ²(1) = a + b log(1) = a + b(0) = 120  β†’  a = 120

Step 2 β€” Substitute a = 120 into first equation:
120 βˆ’ 5b = 70  β†’  βˆ’5b = βˆ’50  β†’  b = 10

Model: Ξ²(I) = 120 + 10 log(I)

Step 3 β€” Predict: eardrum bursts at I = 1Γ—10⁴ W/mΒ²:
β(10⁴) = 120 + 10 log(10⁴) = 120 + 10(4) = 160 dB
🎡 Fun Fact β€” The Word "Decibel"

deci- refers to the fact that the sound level is multiplied by 10 in the formula. -bel references Alexander Graham Bell, inventor of the telephone, for whom decibels are named.

Pattern recap: log(1) = 0 is a useful trick β€” when you substitute a data point where x = 1, the log term vanishes and you can immediately read off the value of a. Then substitute back to find b.
Card 1 of 6
Concept
When is a logarithmic model appropriate for a data set?
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Answer
When input values change proportionally over equal-length output intervals β€” rapid initial growth that gradually slows
The reverse of an exponential: x values multiply while y values add equally. Data curves steeply at first then flattens.
Logarithmic Function Context & Data Modeling
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Question 1 of 5
L(x) = a + b ln x, with L(2) = 3 and L(5) = 7. What equations can be used to find a and b?
Question 2 of 5
Using L(2) = a + b ln 2 = 3 and L(5) = a + b ln 5 = 7, which expression gives the value of b?
Subtract the two equations to eliminate a
Question 3 of 5
The sound intensity model is Ξ²(I) = a + b log(I). A loud concert at I = 1 W/mΒ² corresponds to 120 dB. What is the value of a?
log(1) = 0
Question 4 of 5
Using Ξ²(I) = 120 + 10 log(I), what is the predicted sound level in decibels for I = 1Γ—10⁴ W/mΒ²?
log(1Γ—10⁴) = log(10⁴) = 4
Question 5 of 5
A logarithmic regression gives S(p) = βˆ’91.54 + 29.91 ln p. What is the predicted average salary (in thousands) for a church size of 500?
Use a calculator: ln(500) β‰ˆ 6.2146
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