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Aleksandr-060686 [28]
3 years ago
15

Is 7.787887888… a rational number? PLEASE ANSWER ASAP!! WILL GIVE BRAINLIEST!!!!!

Mathematics
2 answers:
Olenka [21]3 years ago
8 0

Answer:

yes  7 787887888/1,000,000,000

Step-by-step explanation:

skelet666 [1.2K]3 years ago
7 0

Answer:

yes it is a rational number because the number has a repeating pattern  

Step-by-step explanation:

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At least 96.00​% of the data in any data set lie within how many standard deviations of the​ mean? Explain how you arrived at yo
zheka24 [161]

The answer assumes that the question is about the <em>normal distribution</em>.

Answer:

96% of the data in any data set <em>normally distributed</em> is 2.05 <em>standard deviations</em> <em>above</em> and <em>below</em> the mean.

Step-by-step explanation:

The key to solving this question is having into account that exists the <em>standard normal distribution</em> that permits obtaining any probability from any normally distributed data, doing the following transformation:

\\ z = \frac{x-\mu}{\sigma}

That is, in this case, we subtract a given value <em>x</em> from the <em>population mean</em> and then divide the result by the <em>population standard deviation</em>. This is a z-score, and this value is associated with the probability for a <em>standard normal distribution</em>, with a population mean = 0 and population standard deviation = 1.

Fortunately, for the <em>standard normal distribution</em>, there is associated a ubiquitous <em>standard normal table</em> for possible values of <em>z</em> and the corresponding probability. Then, knowing that the data are <em>normally distributed</em> and having both distribution <em>parameters</em>, namely, the <em>population mean</em> and <em>population standard deviation</em>, we can consult any standard normal table to find the probabilities for any data distributed following the normal distribution.

However, even without previously know the values of the normal parameters, the standard normal distribution can tell us how many standard deviations from the mean are 96.00% of the data for every normally distributed population.

<h3>Solving the question</h3>

Having all this information at hand, we know that <em>the z-score value tells us how many standard deviations</em> <em>from the mean</em> are the data normally distributed. As a result, we can determine how many standard deviations below and above the population mean represent the 96.00% of the cases for this normal distribution consulting a <em>cumulative standard normal table from the mean</em>.

If we divide 96.00/2 = 48, that is, 0.48, we need to find the z-score for this probability consulting a <em>cumulative standard normal table from the mean</em>. The values for a z-score for that probability is z=2.05, approximately. So, since the normal distribution is also symmetrical, those values are above and below the mean, that is, z =2.05 (above) and z=-2.05(below).

Thus, 96% of the data in any data set normally distributed is 2.05 <em>standard deviations</em> <em>above</em> and <em>below</em> the mean.  

 

5 0
4 years ago
Would it be B or C?
lesya [120]
The answer of this question is b
4 0
3 years ago
Read 2 more answers
Select the three images that represent a fraction that is equal to 6/8.
algol [13]

Answer:

1 2 5

Step-by-step explanation:

right I got it right on the test

4 0
3 years ago
Two integers, a and b have different signs. The absolute value of integer that got this description. Then decide if the product
Vika [28.1K]

Since a and b have opposite signs then both the product and quotient will be negative. The absolute value of a · b will be greater than the absolute value of \frac{a}{b}.

Without the absolute value sign, then since both the product and the quotient are negative, a · b < \frac{a}{b}

Answer: the product is less than the quotient

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3 years ago
Explain how counting number of girls in five children family can be treated as a binomial experiment. What assumptions are neces
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This is a binomial experiment and you'll use the binomial probability distribution because:

  1. There are two choices for each birth. Either you get a girl or you get a boy. So there are two outcomes to each trial. This is where the "bi" comes from in "binomial" (bi means 2).
  2. Each birth is independent of any other birth. The probability of getting a girl is the same for each trial. In this case, the probability is p = 1/2 = 0.5 = 50%
  3. There are fixed number of trials. In this case, there are 5 births so n = 5 is the number of trials.

Since all of those conditions above are met, this means we have a binomial experiment.

Some textbooks may split up item #2 into two parts, but I chose to place them together since they are similar ideas.

8 0
4 years ago
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