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Nastasia [14]
3 years ago
6

A football team gains 11 yards on a pass, loses 8 yards in a sack,

Mathematics
1 answer:
OLEGan [10]3 years ago
5 0

Answer:

Step-by-step explanation:

loose (8+5) yards so they lost 13 yards

and obviously they gained 11 yards according to the information given.

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If C{1,2} and D={4,5,6}, find C×D by tabulation method. i need for exam​
Katarina [22]

Answer:

Step-by-step explanation:

C * D = {(x,y): x is an element of C and y is an element of D.}

C * D = { (1,4), (1,5), (1,6), (2,4), (2,5), (2,6) }

4 0
3 years ago
Factor completely 49x2 − 81. <br> a. (7x 9)2 <br> b. (7x − 9)2 <br> c. (7x 9)(7x − 9) <br> d. 7x − 9
vredina [299]
Use the property
(a -b)(a+ b) = a^2 - b^2

49x^2 - 81 = (7x + 9)((7x - 9)
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4 years ago
Read 2 more answers
Suppose that a basketball player can score on a particular shot with probability .3. Use the central limit theorem to find the a
Rom4ik [11]

Answer:

(a) The probability that the number of successes is at most 5 is 0.1379.

(b) The probability that the number of successes is at most 5 is 0.1379.

(c) The probability that the number of successes is at most 5 is 0.1379.

(d) The probability that the number of successes is at most 11 is 0.9357.

→ All the exact probabilities are more than the approximated probability.

Step-by-step explanation:

Let <em>S</em> = a basketball player scores a shot.

The probability that a basketball player scores a shot is, P (S) = <em>p</em> = 0.30.

The number of sample selected is, <em>n</em> = 25.

The random variable S\sim Bin(25,0.30)

According to the central limit theorem if the sample taken from an unknown population is large then the sampling distribution of the sample proportion (\hat p) follows a normal distribution.

The mean of the the sampling distribution of the sample proportion is: E(\hat p)=p=0.30

The standard deviation of the the sampling distribution of the sample proportion is:

SD(\hat p)=\sqrt{\frac{ p(1- p)}{n} }=\sqrt{\frac{ 0.30(1-0.30)}{25} }=0.092

(a)

Compute the probability that the number of successes is at most 5 as follows:

The probability of 5 successes is: p=\frac{5}{25} =0.20

P(\hat p\leq 0.20)=P(\frac{\hat p-E(\hat p)}{SD(\hat p)}\leq  \frac{0.20-0.30}{0.092} )\\=P(Z\leq -1.087)\\=1-P(Z

**Use the standard normal table for probability.

Thus, the probability that the number of successes is at most 5 is 0.1379.

The exact probability that the number of successes is at most 5 is:

P(S\leq 5)={25\choose 5}(0.30)^{5}91-0.30)^{25-5}=0.1935

The exact probability is more than the approximated probability.

(b)

Compute the probability that the number of successes is at most 7 as follows:

The probability of 5 successes is: p=\frac{7}{25} =0.28

P(\hat p\leq 0.28)=P(\frac{\hat p-E(\hat p)}{SD(\hat p)}\leq  \frac{0.28-0.30}{0.092} )\\=P(Z\leq -0.2174)\\=1-P(Z

**Use the standard normal table for probability.

Thus, the probability that the number of successes is at most 7 is 0.4129.

The exact probability that the number of successes is at most 7 is:

P(S\leq 57)={25\choose 7}(0.30)^{7}91-0.30)^{25-7}=0.5118

The exact probability is more than the approximated probability.

(c)

Compute the probability that the number of successes is at most 9 as follows:

The probability of 5 successes is: p=\frac{9}{25} =0.36

P(\hat p\leq 0.36)=P(\frac{\hat p-E(\hat p)}{SD(\hat p)}\leq  \frac{0.36-0.30}{0.092} )\\=P(Z\leq 0.6522)\\=0.7422

**Use the standard normal table for probability.

Thus, the probability that the number of successes is at most 9 is 0.7422.

The exact probability that the number of successes is at most 9 is:

P(S\leq 9)={25\choose 9}(0.30)^{9}91-0.30)^{25-9}=0.8106

The exact probability is more than the approximated probability.

(d)

Compute the probability that the number of successes is at most 11 as follows:

The probability of 5 successes is: p=\frac{11}{25} =0.44

P(\hat p\leq 0.44)=P(\frac{\hat p-E(\hat p)}{SD(\hat p)}\leq  \frac{0.44-0.30}{0.092} )\\=P(Z\leq 1.522)\\=0.9357

**Use the standard normal table for probability.

Thus, the probability that the number of successes is at most 11 is 0.9357.

The exact probability that the number of successes is at most 11 is:

P(S\leq 11)={25\choose 11}(0.30)^{11}91-0.30)^{25-11}=0.9558

The exact probability is more than the approximated probability.

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The answer is: -4/a^2 b^2
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