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Rom4ik [11]
3 years ago
14

115.2 divided by 9.6

Mathematics
2 answers:
Monica [59]3 years ago
6 0

Answer:

12

Step-by-step explanation:

Len [333]3 years ago
5 0
12

Mark brainliest please
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The population in 1993 was 11,211 people. The annual increase of the population is 4.18%. What is the population of Cypress in 2
RoseWind [281]

Answer:

  Based on this information the population in 2019 is <u>23,395</u>. This is because 4.18% of 11,211 is 468.62, times 26(amount of years) is 12,184. After that you would just add the original population(11,211).

Step-by-step explanation:

3 0
3 years ago
An investment analyst has tracked a certain bluechip stock for the past six months and found that on any given day, it either go
anastassius [24]

Answer:

0.2109 or 21.09%

Step-by-step explanation:

In order to maintain the same price after two days, the stock must go up (U) on two days and go down (D) on two days, the sample space for this event is:

S={UUDD, UDUD, UDDU, DDUU, DUDU, DUUD}

There are 6 equally likely possible outcomes. The probability that the price of the stock will be the same as it is today is:

P =6* (0.25*0.25*0.75*0.75)\\P=0.2109=21.09\%

The probability is 0.2109 or 21.09%.

7 0
3 years ago
What is the maximum number of snowmen they can make?
Anastasy [175]
To answer this question, you do 5 2/3 divided by 1/2. First, change 5 2/3 to 17/3. Then, use the reciprocal method by doing 17/3 times 2/1, which gives you 34/3. That’s 11.3 repeating, so they can make 11 whole snowmen.
3 0
3 years ago
±√121 what is the answer
HACTEHA [7]

Answer:

±11 is the answer........

6 0
3 years ago
Read 2 more answers
The mean life of a television set is 119 months with a standard deviation of 14 months. If a sample of 74 televisions is randoml
irina [24]

Answer:

50.34% probability that the sample mean would differ from the true mean by less than 1.1 months

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, the sample means with size n of at least 30 can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 119, \sigma = 14, n = 74, s = \frac{14}{\sqrt{74}} = 1.63

If a sample of 74 televisions is randomly selected, what is the probability that the sample mean would differ from the true mean by less than 1.1 months

This is the pvalue of Z when X = 119 + 1.1 = 120.1 subtracted by the pvalue of Z when X = 119 - 1.1 = 117.9. So

X = 120.1

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{120.1 - 119}{1.63}

Z = 0.68

Z = 0.68 has a pvalue of 0.7517

X = 117.9

Z = \frac{X - \mu}{s}

Z = \frac{117.9 - 119}{1.63}

Z = -0.68

Z = -0.68 has a pvalue of 0.2483

0.7517 - 0.2483 = 0.5034

50.34% probability that the sample mean would differ from the true mean by less than 1.1 months

8 0
3 years ago
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