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almond37 [142]
3 years ago
9

If f (x) = StartFraction x minus 3 Over x EndFraction and g(x) = 5x – 4, what is the domain of (f circle g) (x)?

Mathematics
2 answers:
dusya [7]3 years ago
8 0

Answer:

The domain is all real values of x except .4/5

Step-by-step explanation:

alexandr1967 [171]3 years ago
5 0

Answer:

<h2>The domain is all real values of x except \frac{4}{5}.</h2>

Step-by-step explanation:

The function, f(x) = \frac{x - 3}{x}.

g(x) = 5x - 4.

Hence, (f circle g) (x) = \frac{5x - 4 - 3}{5x - 4}.

We need to find the domain of (f circle g) (x) .

The domain means the set of values of x, for which we will get a real value of (f circle g) (x).

The function will not give a real value when, 5x - 4 = 0 that is x = \frac{4}{5}.

Hence, the domain of the function will be all real values of x rather than \frac{4}{5}.

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Suppose a geyser has a mean time between irruption’s of 75 minutes. If the interval of time between the eruption is normally dis
lesya [120]

Answer:

(a) The probability that a randomly selected Time interval between irruption is longer than 84 minutes is 0.3264.

(b) The probability that a random sample of 13 time intervals between irruption has a mean longer than 84 minutes is 0.0526.

(c) The probability that a random sample of 20 time intervals between irruption has a mean longer than 84 minutes is 0.0222.

(d) The probability decreases because the variability in the sample mean decreases as we increase the sample size

(e) The population mean may be larger than 75 minutes between irruption.

Step-by-step explanation:

We are given that a geyser has a mean time between irruption of 75 minutes. Also, the interval of time between the eruption is normally distributed with a standard deviation of 20 minutes.

(a) Let X = <u><em>the interval of time between the eruption</em></u>

So, X ~ Normal(\mu=75, \sigma^{2} =20)

The z-score probability distribution for the normal distribution is given by;

                            Z  =  \frac{X-\mu}{\sigma}  ~ N(0,1)

where, \mu = population mean time between irruption = 75 minutes

           \sigma = standard deviation = 20 minutes

Now, the probability that a randomly selected Time interval between irruption is longer than 84 minutes is given by = P(X > 84 min)

 

    P(X > 84 min) = P( \frac{X-\mu}{\sigma} > \frac{84-75}{20} ) = P(Z > 0.45) = 1 - P(Z \leq 0.45)

                                                        = 1 - 0.6736 = <u>0.3264</u>

The above probability is calculated by looking at the value of x = 0.45 in the z table which has an area of 0.6736.

(b) Let \bar X = <u><em>sample time intervals between the eruption</em></u>

The z-score probability distribution for the sample mean is given by;

                            Z  =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }  ~ N(0,1)

where, \mu = population mean time between irruption = 75 minutes

           \sigma = standard deviation = 20 minutes

           n = sample of time intervals = 13

Now, the probability that a random sample of 13 time intervals between irruption has a mean longer than 84 minutes is given by = P(\bar X > 84 min)

 

    P(\bar X > 84 min) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{84-75}{\frac{20}{\sqrt{13} } } ) = P(Z > 1.62) = 1 - P(Z \leq 1.62)

                                                        = 1 - 0.9474 = <u>0.0526</u>

The above probability is calculated by looking at the value of x = 1.62 in the z table which has an area of 0.9474.

(c) Let \bar X = <u><em>sample time intervals between the eruption</em></u>

The z-score probability distribution for the sample mean is given by;

                            Z  =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }  ~ N(0,1)

where, \mu = population mean time between irruption = 75 minutes

           \sigma = standard deviation = 20 minutes

           n = sample of time intervals = 20

Now, the probability that a random sample of 20 time intervals between irruption has a mean longer than 84 minutes is given by = P(\bar X > 84 min)

 

    P(\bar X > 84 min) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{84-75}{\frac{20}{\sqrt{20} } } ) = P(Z > 2.01) = 1 - P(Z \leq 2.01)

                                                        = 1 - 0.9778 = <u>0.0222</u>

The above probability is calculated by looking at the value of x = 2.01 in the z table which has an area of 0.9778.

(d) When increasing the sample size, the probability decreases because the variability in the sample mean decreases as we increase the sample size which we can clearly see in part (b) and (c) of the question.

(e) Since it is clear that the probability that a random sample of 20 time intervals between irruption has a mean longer than 84 minutes is very slow(less than 5%0 which means that this is an unusual event. So, we can conclude that the population mean may be larger than 75 minutes between irruption.

8 0
3 years ago
AM I CORRECT?? answer for 10 points
OverLord2011 [107]

lox (x) = -5

rewrite the equation in exponential form:

10^-5 = x

10^-5 = 1/10000

1/10000 = 0.00001


That is the correct answer.

8 0
3 years ago
A sample of 5 strings of thread is randomly selected and the following thicknesses are measured in millimeters. Give a point est
xxTIMURxx [149]

Answer:

Point estimate for the population variance = 3.92 * 10^{-3} .

Step-by-step explanation:

We are given that a sample of 5 strings of thread is randomly selected and the following thicknesses are measured in millimeters ;

       X                       X - Xbar                                         (X-Xbar)^{2}

      1.13            1.13 - 1.188 = -0.058                                 3.364 * 10^{-3}

      1.15            1.15 - 1.188 = -0.038                                 1.444 * 10^{-3}    

      1.15            1.15 - 1.188 = -0.038                                 1.444 * 10^{-3}

      1.24           1.24 - 1.188 = 0.052                                 2.704 * 10^{-3}

      1.27           1.27 - 1.188 = 0.082                               <u>  6.724 * </u>10^{-3}<u>    </u>

                                                                    \sum (X-Xbar)^{2} <u>= 0.01568   </u>

Firstly, Mean of above data, Xbar = \frac{\sum X}{n} = \frac{1.15+1.24+1.15+1.27+1.13}{5} = 1.188

Point estimate of Population Variance = Sample variance

                                                               = \frac{\sum (X-Xbar)^{2}}{n-1} = \frac{0.01568}{4} = 3.92 * 10^{-3} .

Therefore, point estimate for the population variance = 3.92 * 10^{-3} .

       

5 0
3 years ago
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