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Elis [28]
1 year ago
13

Assume a bank loan requires an interest payment of $85 per year and a principal payment of $1,000 at the end of the loan's eight

-year life. What would be the present value of this loan if it carried a 10% interest rate?
Mathematics
1 answer:
lapo4ka [179]1 year ago
3 0

Answer:

The present value is  PV  = \$ 396,987

Step-by-step explanation:

From the question we are told that

   The  interest payment per year is  C =  \$ 85

    The principal payment is  P =  \$ 1000

     The  duration is  n =  8   years

      The  interest rate is  r =  10\%  =  0.10

The present value is  mathematically represented as

      PV  =  [ \frac{C}{r} *  [1 - \frac{1 }{ (1 +r)^n} ] + \frac{P}{(1 + r)^n}  ]

substituting values

      PV  =  [ \frac{85}{0.10} *  [1 - \frac{1 }{ (1 +0.10)^8} ] + \frac{1000}{(1 + 0.10)^ 8}  ]

      PV  = \$ 396,987

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Answer:

a 2.68

b 2.01

Step-by-step explanation:

1.34/2 =( 0.67 (F) )

(F)*4 = A

(F)*3 = B

6 0
1 year ago
Sam is observing the velocity of a car at different times. After two hours, the velocity of the car is 50 km/h. After six hours,
Eva8 [605]
Let:
x = hours of travel
y = velocity

slope= rise/run slope=(y2-y1)/(x2-x1) 
(x1,y1) = (2,50) (x2,y2) = (6,54) 
sub values back into the equation m = (54-50)/(6-2) m = 1 
POINT SLOPE FORMy-y1 = m(x-x1) y-50= 1(x-2) y = x -2 +50
y = x + 48

B) 

the graph within the first seven hours can be obtained at point B

x = 7

y = 7+48 = 55
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4 0
1 year ago
A local cable company claims that the proportion of people who have Internet access is less than 63%. To test this claim, a rand
MaRussiya [10]

Answer:

Step-by-step explanation:

For the null hypothesis,

H0 : p = 0.63

For the alternative hypothesis,

Ha : p < 0.63

This is a left tailed test

Considering the population proportion, probability of success, p = 0.63

q = probability of failure = 1 - p

q = 1 - 0.63 = 0.37

Considering the sample,

Sample proportion, P = x/n

Where

x = number of success = 478

n = number of samples = 800

P = 478/800 = 0.6

We would determine the test statistic which is the z score

z = (P - p)/√pq/n

z = (0.6 - 0.63)/√(0.63 × 0.37)/800 = - 1.76

From the normal distribution table, the area below the test z score in the left tail 0.039

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7 0
1 year ago
The factory quality control department discovers that the conditional probability of making a manufacturing mistake in its preci
Anni [7]

Answer:

The probability that a defective ball bearing was manufactured on a Friday = 0.375

Step-by-step explanation:

Let the event of making a mistake = M

The event of making a precision ball bearing production on Monday = Mo

The event of making a precision ball bearing production on Tuesday = T

The event of making a precision ball bearing production on Wednesday = W

The event of making a precision ball bearing production on Thursday = Th

The event of making a precision ball bearing production on Friday = F

the conditional probability of making a manufacturing mistake in its precision ball bearing production is 4% on Tuesday, P(M|T) = 4% = 0.04

4% on Wednesday, P(M|W) = 0.04

4% on Thursday, P(M|Th) = 0.04

8% on Monday, P(M|Mo) = 0.08

and 12% on Friday = P(M|F) = 0.12

The Company manufactures an equal amount of ball bearings (20 %) on each weekday, Hence, the probability that a random precision ball bearing was made on a particular day of the week, is mostly the same for all the five working days.

P(Mo) = 0.20

P(T) = 0.20

P(W) = 0.20

P(Th) = 0.20

P(F) 0.20

The probability that a defective ball bearing was manufactured on a Friday = P(F|M)

P(F|M) = P(F n M) ÷ P(M)

P(F n M) = P(M n F)

P(M) = P(Mo n M) + P(T n M) + P(W n M) + P(Th n M) + P(F n M)

We can obtain each of these probabilities by using the expression for conditional probability.

P(Mo n M) = P(M|Mo) × P(Mo) = 0.08 × 0.20 = 0.016

P(T n M) = P(M|T) × P(T) = 0.04 × 0.20 = 0.008

P(W n M) = P(M|W) × P(W) = 0.04 × 0.20 = 0.008

P(Th n M) = P(M|Th) × P(Th) = 0.04 × 0.20 = 0.008

P(F n M) = P(M|F) × P(F) = 0.12 × 0.20 = 0.024

P(M) = P(Mo n M) + P(T n M) + P(W n M) + P(Th n M) + P(F n M)

P(M) = 0.016 + 0.008 + 0.008 + 0 008 + 0.024 = 0.064

P(F|M) = P(F n M) ÷ P(M)

P(F n M) = P(M n F) = 0.024

P(M) = 0.064

P(F|M) = P(F n M) ÷ P(M) = (0.024/0.064) = 0.375

Hope this Helps!

4 0
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1 year ago
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