/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 5 You currently have $$\$ 5000$$ i... [FREE SOLUTION] | 91Ó°ÊÓ

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You currently have $$\$ 5000$$ in a savings account that pays \(0.5 \%\) interest each month. You add $$\$ 200$$ each month. Build a numerical solution to determine when the account reaches $$\$ 20,000$$.

Short Answer

Expert verified
It takes 61 months for the account to reach $20,000.

Step by step solution

01

Understand the account growth formula

Our savings account grows each month due to the monthly interest rate and the addition of a fixed deposit. The formula to calculate the account balance for the next month is:\[B_{next} = B_{current} + (B_{current} \times \text{interest rate}) + \text{monthly deposit}\]where \(B_{current}\) is the balance at the start of the month, the interest rate is \(0.5\%\) (or \(0.005)\) per month, and the monthly deposit is \$200.
02

Initialize variables

Let's start by setting the initial balance and the parameters for the calculations:- Initial balance: \(B = 5000\)- Monthly interest rate: \(r = 0.005\)- Monthly deposit: \(D = 200\)- Target balance: \(20000\)- Month counter: \(0\)
03

Calculate the balance month by month

Iteratively calculate the balance for each month using the growth formula:\[B = B + (B \times r) + D\]Increase the month counter by one after each calculation until the balance \(B\) reaches or exceeds \$20000.
04

Track the number of months needed

Continue the calculations from Step 3:- Month 1: \(B = 5000 + (5000 \times 0.005) + 200 = 5225\)- Month 2: \(B = 5225 + (5225 \times 0.005) + 200 = 5451.125\)- Repeat until \(B \geq 20000\).Count how many months it took for the account to reach \(20000\).
05

Check the condition

After each iteration, check if \(B\) is at least \$20000. If yes, then record the month as the solution.

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Key Concepts

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

Savings Account Growth
Managing the growth of a savings account involves understanding how the balance increases over time due to interest and any additional deposits. The specific example we examine involves starting with a balance of $5000 in a savings account. Each month, an interest rate of 0.5% is applied which contributes to the overall growth of the account.
Additionally, $200 is deposited every month, which further boosts the balance significantly over time. This growth process combines both interest and manual deposits to achieve a target balance, in this case, reaching $20,000.
  • Interest rates increase the account balance without additional deposits.
  • Consistent deposits help reach your financial goal faster.
  • Both methods work together to increase savings significantly over time.
This dual approach results in compound growth, leading to an account balance that grows at an accelerating rate each month. Understanding the dynamics between the starting balance, interest, and regular deposits is essential for planning savings account growth effectively.
Iterative Calculation
Iterative calculation involves repeating a specific calculation process in steps until a desired outcome is achieved. For our savings account scenario, this means calculating the new balance for each month iteratively until the account balance reaches \(20,000.
Initially, we know:
  • Starting balance: \)5000
  • Monthly interest rate: 0.5%
  • Monthly deposit: \(200
These values set the initial conditions for our iterations. The calculation for each month is performed by applying the interest rate to the current balance, adding the monthly deposit, and updating the balance accordingly:
\[ B_{next} = B_{current} + (B_{current} \times 0.005) + 200 \]
Each calculation is one step closer to reaching the target balance. We continue this process month by month, updating the balance and checking if it has reached or surpassed \)20,000. The iterative nature of this process makes it highly systematic and reliable for projecting future balances.
Interest Rate Modeling
Interest rate modeling is a crucial part of predicting how quickly a savings account balance will grow. In our example, a modest interest rate of 0.5% is applied monthly. This seemingly small rate can contribute massively over time due to compound interest effects.
Compound interest works by applying the interest to not just the original balance but also any accumulated interest from previous periods. Each month, the account balance grows by a small amount due to the interest, but because the balance keeps increasing, the interest amount gets larger each month.
  • The interest rate is a percentage of the current balance, not a fixed dollar amount.
  • Small interest rates can build substantial savings over many months or years if compounded.
  • Higher initial balances or interest rates will increase the growth effect exponentially.
The model helps in anticipating the future value of a savings account by considering all these factors. Understanding this concept allows individuals to optimize their savings strategies by leveraging both consistent contributions and the power of interest.

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Most popular questions from this chapter

By substituting \(n=0,1,2,3\), write out the first four algebraic equations represented by the following dynamical systems: a. \(a_{n+1}=3 a_{n}, \quad a_{0}=1\) b. \(a_{n+1}=2 a_{n}+6, \quad a_{0}=0\) c. \(a_{n+1}=2 a_{n}\left(a_{n}+3\right), \quad a_{0}=4\) d. \(a_{n+1}=a_{n}^{2}, \quad a_{0}=1\)

The data in the accompanying table show the speed \(n\) (in increments of \(5 \mathrm{mph}\) ) of an automobile and the associated distance \(a_{n}\) in feet required to stop it once the brakes are applied. For instance, \(n=6\) (representing \(6 \times 5=30 \mathrm{mph}\) ) requires a stopping distance of \(a_{6}=47 \mathrm{ft}\). a. Calculate and plot the change \(\Delta a_{n}\) versus \(n\). Does the graph reasonably approximate a linear relationship? b. Based on your conclusions in part (a), find a difference equation model for the stopping distance data. Test your model by plotting the errors in the predicted values against \(n .\) Discuss the appropriateness of the model. $$ \begin{array}{l|llllllllllllllll} \hline n & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 & 11 & 12 & 13 & 14 & 15 & 16 \\ \hline a_{n} & 3 & 6 & 11 & 21 & 32 & 47 & 65 & 87 & 112 & 140 & 171 & 204 & 241 & 282 & 325 & 376 \\ \hline \end{array} $$

For the following problems, find an equilibrium value if one exists. Classify the equilibrium value as stable or unstable. a. \(a_{n+1}=1.1 a_{n}\) b. \(a_{n+1}=0.9 a_{n}\) c. \(a_{n+1}=-0.9 a_{n}\) d. \(a_{n+1}=a_{n}\) e. \(a_{n+1}=-1.2 a_{n}+50\) f. \(a_{n+1}=1.2 a_{n}-50\) g. \(a_{n+1}=0.8 a_{n}+100\) h. \(a_{n+1}=0.8 a_{n}-100\) i. \(a_{n+1}=-0.8 a_{n}+100\) j. \(a_{n+1}=a_{n}-100\) k. \(a_{n+1}=a_{n}+100\)

The following data represent the U.S. population from 1790 to 2010 . Find a dynamical system model that fits the data fairly well. Test your model by plotting the predictions of the model against the data. $$ \begin{array}{lrrrrr} \hline \text { Year } & \text { Population } & \text { Year } & \text { Population } & \text { Year } & \text { Population } \\ \hline 1790 & 3,929,000 & 1870 & 38,558,000 & 1950 & 150,697,000 \\ 1800 & 5,308,000 & 1880 & 50,156,000 & 1960 & 179,323,000 \\ 1810 & 7,240,000 & 1890 & 62,948,000 & 1970 & 203,212,000 \\ 1820 & 9,638,000 & 1900 & 75,995,000 & 1980 & 226,505,000 \\ 1830 & 12,866,000 & 1910 & 91,972,000 & 1990 & 248,710,000 \\ 1840 & 17,069,000 & 1920 & 105,711,000 & 2000 & 281,416,000 \\ 1850 & 23,192,000 & 1930 & 122,755,000 & 2010 & 308,746,000 \\ 1860 & 31,443,000 & 1940 & 131,669,000 & & \\ \hline \end{array} $$

Place a cold can of soda in a room. Measure the temperature of the room, and periodically measure the temperature of the soda. Formulate a model to predict the change in the temperature of the soda. Estimate any constants of proportionality from your data. What are some of the sources of error in your model?

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