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Reil [10]
4 years ago
15

We must use substitution to do this second integral. We can use the substitution t = 7x, which will give dx = Correct: Your answ

er is correct. dt. Ignoring the constant of integration, we have sin(7x) dx =
Mathematics
1 answer:
tankabanditka [31]4 years ago
6 0

Answer:

Therefore, the solution is:

\boxed{\int \sin 7x\, dx=-\frac{\cos 7x}{7}}

Step-by-step explanation:

We calculate the given integral.  We use the substitution t = 7x.

\int \sin 7x\, dx=\begin{vmatrix} 7x=t\\ 7\, dx=dt\\ dx=\frac{dt}{7} \end{vmatrix}\\\\=\int \sin t \cdot \frac{1}{7}\, dt\\\\=\frac{1}{7}\cdot (-\cos t)\\\\=-\frac{\cos 7x}{7}

Therefore, the solution is:

\boxed{\int \sin 7x\, dx=-\frac{\cos 7x}{7}}

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kolezko [41]
B.0 because integers cannot be decimals.
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4 years ago
105. Suppose that the probability that an adult in America will watch the Super Bowl is 40%. Each person is considered independe
Ainat [17]

Answer:

a. X is the number of adults in America that need to be surveyed until finding the first one that will watch the Super Bowl.

b. X can take any integer that is greater than or equal to 1. \rm X\in \mathbb{Z}^{+}.

c. \rm X \sim NB(1, 0.40).

d. E(\rm X) = 2.5.

e. P(\rm X = 7) = 0.0187.

f. P(\text{X} = 3) +P(\text{X} = 4) = 0.230.

Step-by-step explanation:

<h3>a.</h3>

In this setting, finding an adult in America that will watch the Super Bowl is a success. The question assumes that the chance of success is constant for each trial. The question is interested in the number of trials before the first success. Let X be the number of adults in America that needs to be surveyed until finding the first one who will watch the Super Bowl.

<h3>b.</h3>

It takes at least one trial to find the first success. However, there's rare opportunity that it might take infinitely many trials. Thus, X may take any integer value that is greater than or equal to one. In other words, X can be any positive integer: \rm X\in \mathbb{Z}^{+}.

<h3>c.</h3>

There are two discrete distributions that may model X:

  • The geometric distribution. A geometric random variable measures the number of trials before the first success. This distribution takes only one parameter: the chance of success on each trial.
  • The negative binomial distribution. A negative binomial random variable measures the number of trials before the r-th success. This distribution takes two parameters: the number of successes r and the chance of success on each trial p.

\rm NB(1, p) (note that r=1) is equivalent to \sim Geo(p). However, in this question the distribution of \rm X takes two parameters, which implies that \rm X shall follow the negative binomial distribution rather than the geometric distribution. The probability of success on each trial is 40\% = 0.40.

\rm X\sim NB(1, 0.40).

<h3>d.</h3>

The expected value of a negative binomial random variable is equal to the number of required successes over the chance of success on each trial. In other words,

\displaystyle E(\text{X}) = \frac{r}{p} = \frac{1}{0.40} = 2.5.

<h3>e.</h3>

P(\rm X = 7) = 0.0187.

Some calculators do not come with support for the negative binomial distribution. There's a walkaround for that as long as the calculator supports the binomial distribution. The r-th success occurs on the n-th trial translates to (r-1) successes on the first (n-1) trials, plus another success on the n-th trial. Find the chance of (r-1) successes in the first (n-1) trials and multiply that with the chance of success on the n-th trial.

<h3>f.</h3>

P(\text{X} = 3)+P(\text{X} = 4) = 0.230.

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Answer:

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Answer:

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Step-by-step explanation:

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