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Sauron [17]
4 years ago
8

PLEASE HELP!!!

Mathematics
1 answer:
igomit [66]4 years ago
3 0

Answer:

Step-by-step explanation:

-2(p + 4) = 3 - 3p + 1p.....combine like terms

-2(p + 4) = 3 - 2p...distribute the -2 through the parenthesis

-2p - 8 = 3 - 2p

-2p + 2p = 3 + 8

0 = 11 <==== no solution

if it is a false statement, it has no solutions

if it ends like : 6 = 6 or -2 = -2, then there is infinite solutions

if it ends like : x = 8 or x = -5, then there is 1 solution

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Given ΔMNO, find the measure of ∠NMO.
Ulleksa [173]

Answer:

m<NMO = 76 deg

Step-by-step explanation:

If a triangle has two congruent sides, then the angles opposite those two congruent sides are congruent.

Since sides NO and NM are congruent, then angles NMO and NOM are congruent.

Angles NOP and NOM are supplementary, so their measures add up to 180 deg.

m<NOM + m<NOP = 180

m<NOM + 104 = 180

m<NOM = 76

m<NMO = m<NOM = 76

m<NMO = 76 deg

6 0
4 years ago
Read 2 more answers
Suppose cattle in a large herd have a mean weight of 1217lbs1217 lbs and a variance of 10,40410,404. What is the probability tha
AlexFokin [52]

Answer:

0.2460 = 24.60% probability that the mean weight of the sample of cows would differ from the population mean by more than 11 lbs if 116 cows are sampled at random from the herd.

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(which is the square root of the variance) \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 = 1217, \sigma = \sqrt{10414} = 102, n = 116, s = \frac{102}{\sqrt{116}} = 9.475

What is the probability that the mean weight of the sample of cows would differ from the population mean by more than 11 lbs if 116 cows are sampled at random from the herd?

This is 2 multiplied by the pvalue of Z when X = 1217 - 11 = 1206. So

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

By the Central Limit Theorem

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

Z = \frac{1206 - 1217}{9.475}

Z = -1.16

Z = -1.16 has a pvalue of 0.1230

2*0.1230 = 0.2460

0.2460 = 24.60% probability that the mean weight of the sample of cows would differ from the population mean by more than 11 lbs if 116 cows are sampled at random from the herd.

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3 years ago
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Answer:

-1.58

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Got it right on edge:)

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Ostrovityanka [42]

Answer:

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• Then using distributive property, factorise out the value h so that the reverse is true.

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• for the variable "lw", divide it by h in order to add it to the bracket of (w + l). Make sure the reverse is true:

{ \rm{S = h(w + l) + h( \frac{lw}{h} )}} \\

• finally, completely factorise out the value h

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Romashka-Z-Leto [24]

Answer:

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