The exponential function models the value v of the car after t years is V = 27000 * (0.93)^t
<h3>How to determine the exponential model?</h3>
The given parameters are:
Initial value, a = $27,000
Depreciation rate, r = 7%
The value of the car is then calculated as:
V = a * (1 -r)^t
Substitute known values
V = 27000 * (1 - 7%)^t
Evaluate the difference
V = 27000 * (0.93)^t
Hence, the exponential function models the value v of the car after t years is V = 27000 * (0.93)^t
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Think about it do you think it's subtraction or addition?
Answer:
p(2) =147 and p(4) = 1791
Step-by-step explanation:
We are given p(x)= 6x^4 + 4x^3 – 3x^2 + 8x + 15.
Now we need to find value of p(2) and p(4)
Put x =2,
p(2) = 6(2)^4 + 4(2)^3 – 3(2)^2 + 8(2) + 15
p(2) = 6(16)+4(8)-3(4)+8(2)+15
p(2) = 96+32-12+16+15
p(2) = 147
Now put x = 4
p(4) = 6(4)^4 + 4(4)^3 – 3(4)^2 + 8(4) + 15
p(4) = 6(256)+4(64)-3(16)+8(4)+15
p(4) = 1536+256-48+32+15
p(4) = 1791
By the Pythagoras theorem, in a right triangle with the sides being a and b,
a² + b² = Hypotenuse²
Hypotenuse² = 4² + 4²
Hypotenuse² = 16 + 16 = 2*16
Hypotenuse = √2 * √16
Thus, hypotenuse = 4√2
Answer:
Test statistic Z= 0.13008 < 1.96 at 0.10 level of significance
null hypothesis is accepted
There is no difference proportion of positive tests among men is different from the proportion of positive tests among women
Step-by-step explanation:
<em>Step(I)</em>:-
Given surveyed two random samples of 390 men and 360 women who were tested
first sample proportion

second sample proportion

Step(ii):-
Null hypothesis : H₀ : There is no difference proportion of positive tests among men is different from the proportion of positive tests among women
Alternative Hypothesis:-
There is difference between proportion of positive tests among men is different from the proportion of positive tests among women

where

P = 0.920

Test statistic Z = 0.13008
Level of significance = 0.10
The critical value Z₀.₁₀ = 1.645
Test statistic Z=0.13008 < 1.645 at 0.1 level of significance
Null hypothesis is accepted
There is no difference proportion of positive tests among men is different from the proportion of positive tests among women