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masha68 [24]
3 years ago
6

Give the types of quantities

Mathematics
1 answer:
Sergeeva-Olga [200]3 years ago
7 0
Magnitude (how much) and multitude (how many), the two principal types of quantities, are further divided as mathematical and physical.
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Olenka [21]

Answer:

a. y2×

b.y1×

c.y1×

d.y2×

e.1×

4 0
2 years ago
Plas answer this I need it today
liberstina [14]

Answer:

Step-by-step explanation:

17 : Both

9.5 : Rational

7/5 : Rational

3 1/2: Rational

29: Both

7 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
Please help me with this question!
gavmur [86]
First off, let's convert the percentages to decimal format, so our 77% turns to 77/100 or 0.77, and our 55% turns to 55/100 or 0.55 and so on

now, the sum of both salines, must add up to the 77% mixture, let's say is "y"
so, 11 + 4 = y, and whatever the concentration level is, must also sum up to the mixture's concentration of 77%

anyway   thus

\bf \begin{array}{lccclll}&#10;&amount&concentration&&#10;\begin{array}{llll}&#10;concentrated\\&#10;amount&#10;\end{array}\\&#10;&-----&-------&-------\\&#10;\textit{first sol'n}&11&x&11x\\&#10;\textit{second sol'n}&4&0.55&2.20\\&#10;------&-----&-------&-------\\&#10;mixture&y&0.77&0.77y&#10;\end{array}\\\\&#10;-------------------------------\\\\&#10;\begin{cases}&#10;11+4=y\implies 15=\boxed{y}\\&#10;11x+2.2=0.77y\\&#10;----------\\&#10;11x+2.2=0.77\cdot \boxed{15}&#10;\end{cases}

solve for "x"
6 0
4 years ago
if the 300 inspected light bulbs represent 20% of an hour's total production of light bulbs, how many light bulbs are produced i
KIM [24]
Hi there! 
So to get this we just need to multiply 300 by 5 because it is 1/5 of the hour work. 300 x 5 = 1500 light bulbs. Hope this helps!


6 0
3 years ago
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