Factor x3 ‒ 11x2 ‒ 7x + 77 by grouping. What is the resulting expression?a

(x2 ‒ 7)(x ‒ 11)


b

(x2 ‒ 7)(x + 11)


c

(x2 ‒ 11)(x + 7)


d

(x2 ‒ 11)(x ‒ 7)

Answers

Answer 1
Answer:

Answer:

A. (x^(2)-7)\cdot (x-11)

Step-by-step explanation:

The third order polynomial is factored herein:

x^(2)\cdot (x-11) - 7\cdot (x-11)

(x^(2)-7)\cdot (x-11)

Which represents answer A.


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Answers

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Step-by-step explanation:

Answer:

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1st. 1/5

2nd. 5

Step-by-step explanation:

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Answers

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Hope this helps :D

Before a computer is assembled, its motherboard goes through a special inspection. Assume only 85% of motherboards pass this inspection.(a) What is the probability that at least 13 of the next 15 motherboards pass inspection?
(b) On the average, how many motherboards should be inspected until a motherboard that passes inspection is found?

Answers

a. The probability that at least 13 of the next 15 motherboards pass inspection is 0.604.

b. On average, 1.1765 motherboards should be inspected until a motherboard that passes inspection is found.

a.

The formula for the probability of getting exactly k successes in n trials with a success probability of p is:

P(X = k) = (^nC_k) * p^k * (1 - p)^((n - k))

Where "n choose k" represents the binomial coefficient, which is calculated as n! / (k! * (n - k)!), where "!" denotes factorial.

In this case:

n = 15 (number of trials)

k = 13, 14, 15 (number of successes)

p = 0.85 (probability of success)

First, let's calculate the probability that exactly 13, 14, and 15 motherboards pass inspection.

For k = 13:

P(X = 13) = (^(15) C_ {13}) * 0.85^(13) * (1 - 0.85)^((15 - 13))

= 0.28564

For k = 14:

P(X = 14) = (^(15) C_(14)) * 0.85^(14) * (1 - 0.85)^((15 - 14))

= 0.23123

For k = 15:

P(X = 15) = (^(15) C_(15)) * 0.85^(15) * (1 - 0.85)^((15 - 15))

= 0.08735

Now, sum these probabilities to get the final answer:

P(at least 13) = P(X = 13) + P(X = 14) + P(X = 15)

= 0.28564 + 0.23123 + 0.08735

= 0.60422

= 0.604

(b)

The average number of trials needed until a motherboard that passes inspection is found can be calculated using the concept of the expected value of a geometric distribution:

Expected value (E) = 1 / p

Where p is the probability of success.

In this case, p = 0.85.

E = 1 / 0.85

= 1.1765

Thus, on average, 1.1765 motherboards should be inspected until a motherboard that passes inspection is found.

Learn more about the probability here:

brainly.com/question/11234923

#SPJ12

Final answer:

To find the probability that at least 13 of the next 15 motherboards pass the inspection, use the binomial formula for each scenario (13, 14, and 15 passing) and sum the results. To find on average how many motherboards need to be inspected for one to pass inspection, just take the reciprocal of the probability of success (1/0.85).

Explanation:

This question falls under the domain of probability and statistics. Let's tackle each part separately:

(a) When we talk about at least 13 out of 15 motherboards passing, we have to consider the situations where exactly 13, 14, or all 15 pass. For each case, you would use the binomial formula P(X=k) = C(n, k) * (p^k) * ((1-p)^(n-k)). In this formula, n is the number of trials (which is 15), k is the number of successes we are interested in, p is the probability of a success (which is 0.85), C(n, k) is a combination that represents the different ways k successes can happen in n trials. Calculate this for k = 13, 14, and 15 and sum the results to get the probability for at least 13 to pass.

(b) To find on average how many motherboards should be inspected until one passes is straightforward - it is simply the reciprocal of the probability of success which is 1/0.85.

Learn more about Probability here:

brainly.com/question/22962752

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How do you do this question?

Answers

Answer:

z = -ln│5eᵗ + C│

Step-by-step explanation:

dz/dt + 5eᵗ⁺ᶻ = 0

dz/dt = -5eᵗ⁺ᶻ

dz/dt = -5eᵗeᶻ

-e⁻ᶻ dz = 5eᵗ dt

e⁻ᶻ = 5eᵗ + C

-z = ln│5eᵗ + C│

z = -ln│5eᵗ + C│

Which is greater 4/7 ×1/4 or 4/7×1/6​

Answers

4/7x1/4 is the correct answer

Answer:4/7*1/4

trust me >:)