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Leto [7]
3 years ago
8

there are 11 pieces of pie left over in the cafeteria. if 6 pieces are apple and 5 are cherry, what fraction of the remaining pi

eces are apple
Mathematics
1 answer:
Leto [7]3 years ago
8 0

Answer:

\frac{6}{11}

Step-by-step explanation:

we know that

To find what fraction of the remaining pieces are apple, divide the remaining  pieces of apple by the  total remaining pieces

we have that

the remaining  pieces of apple is equal to 6

the  total remaining pieces is 11

so

\frac{6}{11}

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What is the remainder when 3 is synthetically divided into the polynomial -2x^2 + 7x - 9?
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Answer:

for apex the answer is -6


Step-by-step explanation:


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(8 ^ 4 * 9 ^ 5)/(16 ^ 2 * 27 ^ 3)<br>help needed plzzzzzz helppppp ​
Roman55 [17]

Answer:

answer is 48

Step-by-step explanation:

simplified after exponents.

4,096 x 59,049/ 256 x 19,683

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241,864,704/5,038,848

= 48

6 0
3 years ago
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
This is probably very easy but I totally forgot (look at picture)
Darina [25.2K]
Coordinates for new triangle -

P’(-1,1)
Q’(-3,3)
R’(-3,1)
3 0
3 years ago
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Sally is interested in taking a job in a city in which she's not familiar with the cost of living. She is especially concerned a
Salsk061 [2.6K]

Answer:

a. Mean

Step-by-step explanation:

We have been given that the Sally is interested in taking a job in a city in which she's not familiar with the cost of living. She is especially concerned about the cost of housing and is interested in the average cost of a three bedroom home.

We know that in a normal distribution all central tendencies (mean, mode, median) are equal.

When a very large or very small valued data point is added to data set, mean is mostly affected by that outlier.

We know that mode of a data set is the point that appears at-most in the data set, so outliers doesn't affect mode.

Median of a data set is less affected by outliers.

The price of the three bedroom homes owned by millionaires will be greater than prices of houses owned by people in the neighborhood.

Therefore, mean will be most influenced by three bedroom homes owned by millionaires.

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3 years ago
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