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horrorfan [7]
2 years ago
10

Need help not sure about my answers

Mathematics
1 answer:
shusha [124]2 years ago
3 0

Answer:

  x = 0, x = 1

Step-by-step explanation:

Both graphs correctly plot f(x).

Only the bottom graph correctly plots g(x).

The points of intersection of f(x) and g(x) are (0, -4) and (1, -2). The x-value of these points are x = 0 and x = 1. These are the values of x for which f(x) = g(x).

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Which one is not equal
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Answer:

A

Step-by-step explanation:

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Multiply the numbers and simplifty the answer 3x1 3/4
melamori03 [73]
2.25 is the answer you take 3 times 3/4 and you get 2.25
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3 years ago
Linear Equations <br> 15 - b = 3a + 3 <br> Please help me with this ASAP
Studentka2010 [4]

Answer:

Step-by-step explanation:

15 - x = 3x + 3

15 - x = 3•x + 3

4x = 12

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8 0
2 years ago
Read 2 more answers
Find the greatest common factor of 26 and 14.
Molodets [167]

Answer:

2

Step-by-step explanation:

A factor is a number that can evenly divide into another number.

Let’s list all the factors of both numbers.

26: 1, 2, 13, 26

14: 1,2, 7, 14

Now find the GCF, or greatest common factor. The biggest number that is a factor of both 26 and 14 is 2.

Therefore, the GCF of 26 and 14 is 2.

6 0
3 years ago
Thompson and Thompson is a steel bolts manufacturing company. Their current steel bolts have a mean diameter of 144 millimeters,
valentinak56 [21]

Answer:

The probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.

Step-by-step explanation:

According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and appropriately huge random samples (n > 30) are selected from the population with replacement, then the distribution of the sample  means will be approximately normally distributed.

Then, the mean of the distribution of sample mean is given by,

\mu_{\bar x}=\mu

And the standard deviation of the distribution of sample mean  is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

The information provided is:

<em>μ</em> = 144 mm

<em>σ</em> = 7 mm

<em>n</em> = 50.

Since <em>n</em> = 50 > 30, the Central limit theorem can be applied to approximate the sampling distribution of sample mean.

\bar X\sim N(\mu_{\bar x}=144, \sigma_{\bar x}^{2}=0.98)

Compute the probability that the sample mean would differ from the population mean by more than 2.6 mm as follows:

P(\bar X-\mu_{\bar x}>2.6)=P(\frac{\bar X-\mu_{\bar x}}{\sigma_{\bar x}} >\frac{2.6}{\sqrt{0.98}})

                           =P(Z>2.63)\\=1-P(Z

*Use a <em>z</em>-table for the probability.

Thus, the probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.

8 0
2 years ago
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