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Novay_Z [31]
3 years ago
12

How many solutions does y=5x+3 have

Mathematics
2 answers:
Mariulka [41]3 years ago
7 0

Answer:

\infty

Step-by-step explanation:

The domain/range of x or y is not restricted. Therefore, for x \in \mathrm{R}, the solutions for y are \mathrm{R} (all real numbers).

Therefore, there are an infinite number of solutions to this equation.

aleksandrvk [35]3 years ago
4 0

Answer:

infinite

Step-by-step explanation:

y and x can be any numbers because they're independants

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I would like to receive some help for this
natali 33 [55]

Answer: can't get enough info.

a = 11

Step-by-step explanation:

a + 15 = 3a - 7

-a             -a

15 = 2a - 7

+7         +7

22 = 2a

/2       /2

11 = a

6 0
2 years ago
Suppose a batch of metal shafts produced in a manufacturing company have a population standard deviation of 1.3 and a mean diame
lbvjy [14]

Answer:

54.86% probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

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 = 208, \sigma = 1.3, n = 60, s = \frac{1.3}{\sqrt{60}} = 0.1678

What is the probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

Lesser than 208 - 0.1 = 207.9 or greater than 208 + 0.1 = 208.1. Since the normal distribution is symmetric, these probabilities are equal, so we find one of them and multiply by 2.

Lesser than 207.9.

pvalue of Z when X = 207.9. So

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

By the Central Limit Theorem

Z = \frac{207.9 - 208}{0.1678}

Z = -0.6

Z = -0.6 has a pvalue of 0.2743

2*0.2743 = 0.5486

54.86% probability that the mean diameter of the sample shafts would differ from the population mean by more than 0.1 inches

6 0
3 years ago
Help me I need at least a B in 7th grade math
Leya [2.2K]

For part a, yes because each student is paying the same amount

For part c, each student is paying $15 to go

For part d, it's $1800

For part e, it would be 95 students

8 0
3 years ago
Any help is apprenticed!
nirvana33 [79]
This is the answer. Hope it helps

5 0
3 years ago
What is m∠AEB? <br> (See attachment)
aleksley [76]
Hey there,
Angle AEB + Angle CED = 180 degrees (vertically opposite angles)
(5x-10) degrees + (3x + 40) degrees = 180 degrees
5x -10 + 3x + 40 = 180 degrees
5x + 3x= 180 + 10 - 40
8x = 150
x = 150 / 8
   = 18.75 degrees 
Angle AEB = (18.75 x 5) - 10 
                  =83.75 degrees.

Hope this helps ^_^

~Top
3 0
3 years ago
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