TUI University Math 101 Nov 2012 Module 5 Professor Dr Karon
TUI Universitymat 101 Nov 2012module 5 Slpprofessor Dr Karonika1
TUI University MAT 101 Nov 2012 Module 5 - SLP Professor: Dr. Karonika 1. The cost of getting new life insurance depends on how old you are, and how old you are depends on what year you were born. Provide an example of a composite function using these variables. 2. The amount of time it takes to get to work depends on how much traffic there is, and the amount of traffic there is depends on what time of day it is. If we call the amount of traffic C and the time of day t, then C is a function of t. If we call the time it takes to get to work W, then W is a function of C. Provide an example of a composite function using these variables. 3. Make up your own example of a composite function. Be sure to explain (1) what your variables are, (2) how they are represented in the function, and (3) which elementary functions are combined to form the composite function. 4. Submit a one to two page paper describing which savings instrument you would prefer and why by the end of the module.
Paper For Above instruction
Composite functions are fundamental concepts in mathematics that demonstrate how different functions can be combined to model real-world scenarios. They are formed by applying one function to the results of another, creating a layered or nested function. Below, I explore examples relevant to insurance, traffic, and a personal scenario, illustrating how composite functions can be constructed and interpreted.
Example 1: Life Insurance Cost Based on Age
Consider a person’s age, which directly influences the cost of purchasing a new life insurance policy. The age, denoted as \(A\), depends on the year of birth, represented as \(Y_b\). Assume that the current year is fixed at 2012 for this context. The age of an individual can then be expressed as a function of the year of birth:
\(A = 2012 - Y_b\)
This simple linear function shows that if someone was born in 1980, their age in 2012 would be \(2012 - 1980 = 32\).
Next, suppose the cost of life insurance, \(C_i\), depends on age, and this relationship can be modeled through another function:
\(C_i = f(A)\)
Where \(f\) could be an increasing function, for example, \(f(A) = 50 + 2A\), meaning that as age increases, so does the insurance cost. The composite function combining these is:
\(C = f(2012 - Y_b)\)
This function calculates the insurance cost directly based on the year of birth variable, making it a composite function that links year of birth to insurance cost through age.
Example 2: Travel Time Based on Traffic and Traffic Based on Time of Day
In the second scenario, the journey duration \(W\) depends on the amount of traffic \(C\), which in turn depends on the time of day \(t\). We can express traffic as a function of time:
\(C = g(t)\)
Where \(g\) might be modeled based on typical rush hours, for example:
\(g(t) = 30 + 20 \sin\left(\frac{\pi t}{12}\right)\)
This models traffic fluctuations throughout the day, peaking during certain hours.
The travel time \(W\) relies on the traffic:
\(W = h(C)\)
Where \(h\) could be a linear function indicating longer travel times with increased traffic:
\(h(C) = 10 + 0.5C\)
The composite function is then:
\(W = h(g(t)) = 10 + 0.5 \times \left(30 + 20 \sin\left(\frac{\pi t}{12}\right)\right)\)
This combined function provides the travel time based on the time of day, capturing the layered dependency.
Example 3: Custom Composite Function
Suppose I want to model the relationship between the number of hours studied (\(s\)) and the performance score (\(P\)). First, I consider that the effectiveness of studying depends on the number of hours, but also on the quality of study material (\(q\)). Let’s define:
- Quality of study material: \(q\), a fixed parameter between 0 and 1.
- Hours studied: \(s\).
- Performance score: \(P\).
The effectiveness of studying, \(E\), could be modeled as:
\(E = s \times q\)
The performance score \(P\) then depends on \(E\):
\(P = \sqrt{E}\) // assuming diminishing returns with increasing effectiveness
The composite function becomes:
\(P = \sqrt{s \times q}\)
This layered function combines a linear component (hours and quality) with a nonlinear transformation (square root), illustrating how different elementary functions (multiplication and square root) create a composite structure.
Conclusion
Composite functions elegantly demonstrate the interconnectedness of real-world variables and the layered relationships among them. By analyzing the insurance cost, traffic, and personal study efficiency, we see how mathematical functions can model complex scenarios, offering insights into the dependencies and effects of different factors. Understanding these constructs enables better decision-making and predictions based on multiple variables.
In the context of personal financial planning, such as choosing savings instruments, understanding how various factors influence outcomes is vital. For example, selecting between a savings account, a certificate of deposit, or an individual retirement account depends on factors like interest rates, liquidity, risk, and time horizons—each with their own underlying functions and variables.
References
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