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AveGali [126]
1 year ago
6

Sally Sue had spent all day preparing for the prom. All the glitz and the glamour of the evening fell apart as she stepped out o

f the limousine and her heel broke and she fell to the ground. Within minutes, news of her crashing fall had spread to the 550 people already at the prom. The function, p(t) = 550(1-e^-0.039t) where t represents the number of minutes after the fall, models the number of people who were already at the prom who heard the news.How many minutes does it take before all 550 people already at the prom hear the news ofthe great fall? Show your work.
Mathematics
1 answer:
Nuetrik [128]1 year ago
7 0

We have the function

p(t)=550(1-e^{-0.039t})

Therefore we want to determine when we have

p(t_0)=550

It means that the term

e^{-0.039t}

Must go to zero, then let's forget the rest of the function for a sec and focus only on this term

e^{-0.039t}\rightarrow0

But for which value of t? When we have a decreasing exponential, it's interesting to input values that are multiples of the exponential coefficient, if we have 0.039 in the exponential, let's define that

\alpha=\frac{1}{0.039}

The inverse of the number, but why do that? look what happens when we do t = α

e^{-0.039t}\Rightarrow e^{-0.039\alpha}\Rightarrow e^{-1}=\frac{1}{e}

And when t = 2α

e^{-0.039t}\Rightarrow e^{-0.039\cdot2\alpha}\Rightarrow e^{-2}=\frac{1}{e^2}

We can write it in terms of e only.

And we can find for which value of α we have a small value that satisfies

e^{-0.039t}\approx0

Only using powers of e

Let's write some inverse powers of e:

\begin{gathered} \frac{1}{e}=0.368 \\  \\ \frac{1}{e^2}=0.135 \\  \\ \frac{1}{e^3}=0.05 \\  \\ \frac{1}{e^4}=0.02 \\  \\ \frac{1}{e^5}=0.006 \end{gathered}

See that at t = 5α we have a small value already, then if we input p(5α) we can get

\begin{gathered} p(5\alpha)=550(1-e^{-0.039\cdot5\alpha}) \\  \\ p(5\alpha)=550(1-0.006) \\  \\ p(5\alpha)=550(1-0.006) \\  \\ p(5\alpha)=550\cdot0.994 \\  \\ p(5\alpha)\approx547 \end{gathered}

That's already very close to 550, if we want a better approximation we can use t = 8α, which will result in 549.81, which is basically 550.

Therefore, we can use t = 5α and say that 3 people are not important for our case, and say that it's basically 550, or use t = 8α and get a very close value.

In both cases, the decimal answers would be

\begin{gathered} 5\alpha=\frac{5}{0.039}=128.2\text{ minutes (good approx)} \\  \\ 8\alpha=\frac{8}{0.039}=205.13\text{ minutes (even better approx)} \end{gathered}

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3 years ago
Read 2 more answers
Consider w=sqrrt2/2(cos(225°) + isin(225°)) and z = 1(cos(60°) + isin(60°)). What is w+ z expressed in rectangular form?
SVETLANKA909090 [29]

Answer:

Option (3)

Step-by-step explanation:

w = \frac{\sqrt{2}}{2}[\text{cos}(225) + i\text{sin}(225)]

Since, cos(225) = cos(180 + 45)

                          = -cos(45) [Since, cos(180 + θ) = -cosθ]

                          = -\frac{\sqrt{2}}{2}

sin(225) = sin(180 + 45)

             = -sin(45)

             = -\frac{\sqrt{2}}{2}

Therefore, w = \frac{\sqrt{2}}{2}[-\frac{\sqrt{2}}{2}+i(-\frac{\sqrt{2}}{2})]

                      = -\frac{2}{4}(1+i)

                      = -\frac{1}{2}(1+i)

z = 1[cos(60) + i(sin(60)]

  = [\frac{1}{2}+i(\frac{\sqrt{3}}{2})

  = \frac{1}{2}(1+i\sqrt{3})

Now (w + z) = -\frac{1}{2}(1+i)+\frac{1}{2}(1+i\sqrt{3})

                   = -\frac{1}{2}-\frac{i}{2}+\frac{1}{2}+i\frac{\sqrt{3}}{2}

                   = \frac{(i\sqrt{3}-i)}{2}

                   = \frac{(\sqrt{3}-1)i}{2}

Therefore, Option (3) will be the correct option.

3 0
3 years ago
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The following probability distributions of job satisfaction scores for a sample of information systems (IS) senior executives an
shutvik [7]

Answer:

Kindly see explanation

Step-by-step explanation:

Given the data:

JOB satisfaction (x) : 1, 2, 3, 4, 5

IS Senior ; p(x) : 0.05, 0.09, 0.03, 0.42, 0.41

IS Middle ; p(x) : 0.04, 0.10, 0.12, 0.46, 0.28

Expected value of job satisfaction for senior executives :

E(x) = Σp(x) * x = [(1*0.05) + (2*0.09) + (3*0.03) + (4*0.42) + (5*0.41)]

= 4.05

B) Σp(x) * x = [(1*0.04) + (2*0.10) + (3*0.12) + (4*0.46) + (5*0.28)]

= 3.84

C.) Job variance for executives:

Σ(x - E(x))² * p(x) :

((1 - 4.05)^2 * 0.05) + ((2 - 4.05)^2 * 0.09) + ((3 - 4.05)^2 * 0.03) + ((4 - 4.05)^2 * 0.42) + ((5 - 4.05)^2 * 0.41)

= 1.2475 = 1.25 ( using calculator)

job variance for middle managers :

Σ(x - E(x))² * p(x) :

((1 - 3.84)^2 * 0.04) + ((2 - 3.84)^2 * 0.10) + ((3 - 3.84)^2 * 0.12) + ((4 - 3.84)^2 * 0.46) + ((5 - 3.84)^2 * 0.28)

= 1.1344 = 1.13 (using calculator)

Standard deviation(sd) for (senior managers) :

sd = √variance

sd = √1.25 = 1.118 = 1.12

Standard deviation(sd) for (middle managers) :

sd = √variance

sd = √1.13 = 1.063 = 1.06

The expected value (mean) for senior executives (4.05) is slightly higher Than obtained for middle managers (3.84). Similarly the measure of Variation in job satisfaction ; standard deviation and variance is also higher for senior managers than in middle managers.

6 0
3 years ago
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