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marshall27 [118]
3 years ago
15

solo savings bank received an initial deposit of $6000 it kept a percentage of this money in reserve based on the reserve rate a

nd loaned out the rest the amount it loaned out was eventually all deposited back in the bank if the cycle continued indefinitely and eventually the $6000 turned into $200000 what was the reserve rate?
Mathematics
1 answer:
iogann1982 [59]3 years ago
8 0

Answer:

Reserve rate = 3%

Step-by-step explanation:

Reserve Ratio = Reserve Maintained with Central Bank / Deposit Liabilities × 100

Reserve maintained = $6,000

Deposit liabilities = $200,000

Reserve Rate = Reserve Maintained with Central Bank / Deposit Liabilities × 1000

=$6,000 / $200,000 × 100

=0.03 × 100

r=0.03 × 100

=3%

Therefore,

Reserve Rate =3%

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Helpp pls fastttttttttttttttttttt
Aleksandr [31]

Answer:

35 square inches

Step-by-step explanation:

S = ( 1/3 x 15 ) x ( 1/3 x 21 ) = 5x7= 35 square inches.

Hope this helps you.

6 0
9 months ago
The graph shows the functions f(x), p(x), and g(x): Graph of function g of x is y is equal to 1 plus the quantity 1.5 raised to
satela [25.4K]
Part A:

Given that the <span>straight line p(x) joins the ordered pairs (0, 2) and (1, -5), thus the equation of the line joining ordered pairs (0, 2) and (1, -5) is given by

\frac{y-2}{x} = \frac{-5-2}{1} =-7 \\  \\ \Rightarrow y-2=-7x \\  \\ \Rightarrow y=-7x+2

Thus, p(x) = -7x + 2

</span>Given that the <span>straight line f(x) joins the ordered pairs (4, 1) and (2, -3), thus the equation of the line joining ordered pairs (4, 1) and (2, -3) is given by

\frac{y-1}{x-4} = \frac{-3-1}{2-4} =\frac{-4}{-2}=2 \\  \\ \Rightarrow y-1=2(x-4)=2x-8 \\  \\ \Rightarrow y=2x-7

Thus, f(x) = 2x - 7
</span>
The solution to the pair of equations represented by p(x) and f(x) is given by

p(x) = f(x)
⇒ -7x + 2 = 2x - 7
⇒ -7x - 2x = -7 - 2
⇒ -9x = -9
⇒ x = -9 / -9 = 1

Substituting for x into p(x), we have

p(1) = -7(1) + 2 = -7 + 2 = -5

Therefore, the solution to the pair of equations represented by p(x) and f(x) is  (1, -5)



Part B:

From part A, we have that f(x) = 2x - 7

when x = -8

f(-8) = 2(-8) - 7 = -23

Thus, (-8, -23) is a solution to f(x).

When x = -10

f(-10) = 2(-10) - 7 = -27

Thus, (-10, -27) is a solution to f(x).

Therefore, two solutions of f(x) are (-8, -23) and (-10, -27).



Part C:

From part A, we have that p(x) = -7x + 2, given that g(x) = 1 + 1.5^x

From the graphs of p(x) and g(x), we can see that the two graphs intersected at the point (0, 2).

Therefore, the solution to the equation p(x) = g(x) is (0, 2).

3 0
3 years ago
If someone understands this please help
katrin [286]

Answer:

A= 4

B= 4

C= -1

D= 4

E= -1

F= 4

G= -1

Step-by-step explanation:

The expected value equation is the probability of something happening multiplied by the amount of times it happens. In this case you have four equal sized sections, so you have a one in four chance to land in any of these sections. A, B, D, and F represent the four for this one in four chance. C, E, and G represent the amount of points you get when you land on those sections, in this case -1

3 0
3 years ago
The sum of four consecutive
Firdavs [7]

Answer:

42 is the smallest of the 4 numbers.

Step-by-step explanation:

The 4 consecutive integers that total 174 are 42,43,44, and 45. Therefore, 42 is the smallest out of all 4 integers.

4 0
2 years ago
Real Estate One conducted a recent survey of house prices for properties located on the shores of Tawas Bay. Data on 26 recent s
Ivanshal [37]

Answer:

Step-by-step explanation:

Hello!

Given the data for the variables:

Y: Selling price of a house on the shore of Tawas Bay

X₁: Number of bathrooms of a house on the shore of Tawas Bay.

X₂: Square feet of a house on the shore of Tawas Bay.

X₃: Number of bedrooms of a house on the shore of Tawas Bay.

The multiple regression model is Y= α + β₁X₁ + β₂X₂ + β₃X₃ + εi

a. Using software I've entered the raw data and estimated the regression coefficients:

^α= a= -5531.01

Represents the mean selling price of the houses when 0 bathrooms, 0 square feet and 0 bedrooms.

^β₁= b₁= -1386.21

Represents the modification of the mean selling price of the houses when the number of bathrooms increases in one unit and the square feet and number of bedrooms remain unchanged.

^β₂= b₂= 60.28

Represents the modification of the mean selling price of the houses when the square feet increase in one unit and the number of bathrooms and bedrooms remain unchanged.

^ β₃= b₃= 54797.08

Represents the modification of the mean selling price of the houses when the number of bedrooms increase in one unit and the number of bathrooms and square feet of the houses remain unchanged.

^Y= -5531.01 -1386.21X₁ + 60.28X₂ + 54797.08X₃

b)

R²= 0.55

R²Aj= 0.49

The coefficient of determination gives you an idea of how much of the variability of the dependent variable (Y) is due to the explanatory variables. Each time you add another explanatory variable to the regression the coefficient increases regarding of real contribution of the new variable. This could lead to thinking (wrongly) that the new variables are good to explain the dependent variable.  

The adjusted coefficient of determination is a correction made to the raw coefficient of determination to have a more unbiased estimation of the effect the independent variables have over the dependent variable.

⇒ As you can see both coefficient are around 50%, which means that these explanatory variables

c)

The standard error estimate, this is the estimate of the population variance of the errors. In the ANOVA is represented by the Mean Square of the errors (MME)

Se²= MME= 3837640577.01

Se= 61948.6931

d) and f)

For the hypotheses tests for each slope the t- and p-values are:

α: 0.05

β₁: t_{H_0}= \frac{b_1-\beta_1 }{Sb_1} t= -0.06; p-value: 0.9528 ⇒ Do not reject H₀, the test is not significant.

β₂: t_{H_0}= \frac{b_2-\beta_2 }{Sb_2} t= 2.56; p-value: 0.0180 ⇒ Reject H₀, the test is significant.

β₃: t_{H_0}= \frac{b_3-\beta_3 }{Sb_3} t= 2.28; p-value: 0.0326 ⇒ Reject H₀, the test is significant.

e)

H₀: β₁= β₂= β₃

H₁: At least one βi is different from the others ∀ i=1, 2, 3

α: 0.05

F= 9.03

p-value: 0.0004

⇒ Reject H₀, the test is significant.

I hope it helps!

5 0
3 years ago
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