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Lera25 [3.4K]
3 years ago
14

Find the consecutive positive odd integers whose product is 99​

Mathematics
1 answer:
dezoksy [38]3 years ago
4 0

Answer:

9 and 11

Step-by-step explanation:

So let's say that the first integer is x.

That means that the second integer is x+2, since it us the next odd number.

This problem can be easily solved with our mind the answer is 9 and 11, but I'll show you the steps to slove this.

We make an equation using these two numbers:

(x)*(x+2)=99\\

Now all we gotta do is solve for x:

x^2 +2x = 99\\x^2+2x-99=0

Now we use either splitting the middle term or quadratic formula:

x^2+11x-9x+99=0\\x(x+11)-9(x+11)=0\\(x+11)(x-9)=0

Now we split each terma and solve for x:

(x-9)=0\\x=9\\(x+11)=0\\x=-11

Now the question states <em>positive </em>so we can rule out x = -11.

Now we have the first integer x = 9,

the second integer is x+2 = 9+2 =11

So the two consecutive positive odd integers are 9 and 11

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andrey2020 [161]

Answer:

0.0174 = 1.74% probability that the sample mean would be greater than 101.63 WPM

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 normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}};

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\mu = 97, \sigma = 19, n = 75, s = \frac{19}{\sqrt{75}} = 2.1939

What is the probability that the sample mean would be greater than 101.63 WPM?

This is 1 subtracted by the pvalue of Z when X = 101.63. So

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

By the Central Limit Theorem

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

Z = \frac{101.63 - 97}{2.1939}

Z = 2.11

Z = 2.11 has a pvalue of 0.9826.

1 - 0.9826 = 0.0174

0.0174 = 1.74% probability that the sample mean would be greater than 101.63 WPM

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http://eldata2.neu.topica.vn/TXTOKT02/Giao%20trinh/03_NEU_TXTOKT02_Bai2_v1.0014109205.pdf

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