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3 years ago

-4x - 2 - x - 9 = -1 show your work

2 answers:

7 0

$-4x-2-x-9=-1\\\\(-4x-x)-2-9=-1\\\\-5x-11=-1\quad \Big|\text{ Add 11 to both sides}\\\\-5x=10 \quad \Big|\text{ Divide both sides by }-5\\\\x=-2$

faust18 [17]3 years ago

3 0

-4x-x-2-9=-1
or,-5x=10
or,x=-2

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RoseWind [281]

terms is x first then terms in y and constant after the equals

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3 years ago

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Bezzdna [24]

Answer:

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Step-by-step explanation:

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3 years ago

What is sandwich theorem?

nydimaria [60]

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3 years ago

Read 2 more answers

Suppose that lithium calculator battery with a charge of 3 volts, actually has a voltage with uniform distribution between 2.93

Dmitrij [34]

Answer:

b. E(X) = 3.015, STDEV(X)= 0.049, P (X ≤ 2.98) = 0.2941

Step-by-step explanation:

An uniform probability is a case of probability in which each outcome is equally as likely.

For this situation, we have a lower limit of the distribution that we call a and an upper limit that we call b.

The mean of the uniform probability distribution is:

$M = \frac{a + b}{2}$

The standard deviation of the uniform distribution is:

$S = \sqrt{\frac{(b-a)^{2}}{12}}$

The probability that we find a value X lower than x is given by the following formula.

$P(X \leq x) = \frac{x - a}{b-a}$

Uniform distribution between 2.93 and 3.1 volts

This means that $a = 2.93, b = 3.1$ . So

Mean:

$M = \frac{2.93 + 3.1}{2} = 3.015$

Standard deviation:

$S = \sqrt{\frac{(3.1 - 2.93)^{2}}{12}} = 0.049$

What is the probability that a battery has a voltage less than 2.98?

$P(X \leq 2.98) = \frac{2.98 - 2.93}{3.1 - 2.93} = 0.2941$

So the correct answer is:

b. E(X) = 3.015, STDEV(X)= 0.049, P (X ≤ 2.98) = 0.2941

6 0

3 years ago

Two studies were done on the same set of data, where study I was a one-sided test and study II was a two-sided test. The p-value

mixer [17]

Answer:

$0.060$

Step-by-step explanation:

In a two tailed test the probability of occurrence is the total area under the critical range of values on both the sides of the curve (negative side and positive side)

Thus, the probability values for a two tailed test as compared to a one tailed test is given by the under given relation -

$p-value = P(Z< -\frac{\alpha }{2} )+P(Z >\frac{\alpha}{2})$ \

Here $P\frac{\alpha}{2} = 0.030$

Substituting the given value in above equation, we get -

probability values for a two tailed test

= $0.030 + 0.030\\= 0.060$

4 0

3 years ago