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3 years ago

The quotient of 13 ÷ 24 is a decimal number. Which digit in the quotient is overlined?

Mathematics

2 answers:

Vlad1618 [11]3 years ago

7 0

The answer to 13 / 24 is 0.5416666666... The 6 is repeating, and therefore the overlined number is 6.

alexgriva [62]3 years ago

4 0

Answer:

i like yo cut g, are there options or not?

Step-by-step explanation:

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poizon [28]

No the solution should only be X=1

5 0

3 years ago

A parabola intersects the xxx-axis at x=3x=3x, equals, 3 and x=9x=9x, equals, 9.

vekshin1

Answer:

$x^2-12x+27 =0$

Step-by-step explanation:

Given a Parabola that intersects the x-axis at x=3 and x=9.

I presume you want to determine the equation of the parabola.

You can use this form:

Given roots of a parabola, the equation of the parabola is derived using the formula:

$x^2-($Sum of Roots)x+Product of Roots =0\\Since roots are 3 and 9, the equation becomes:\\x^2-(3+9)x+(3X9) =0\\x^2-12x+27 =0$

The equation of the parabola is:

$x^2-12x+27 =0$

8 0

3 years ago

What is (9+8)/(88+77)

barxatty [35]

Answer:

Exact form: 17/165

Decimal form: 0.103

Step-by-step explanation:

hope this helps :)

3 0

3 years ago

Read 2 more answers

Please answer them. 25 points.

diamong [38]

Step-by-step explanation:

Initial value is the y-intercept:

b = 1200

Rate of change is the difference in the charge amount per year:

m = (1350 - 1200) / (8 - 5) = 150 / 3 = 50

The equation would be:

y = 50x + 1200

8 0

2 years ago

Read 2 more answers

A random sample of n = 64 observations is drawn from a population with a mean equal to 20 and standard deviation equal to 16. (G

dezoksy [38]

Answer:

a) The mean of a sampling distribution of $\\ \overline{x}$ is $\\ \mu_{\overline{x}} = \mu = 20$ . The standard deviation is $\\ \frac{\sigma}{\sqrt{n}} = \frac{16}{\sqrt{64}}=2$ .

b) The standard normal z-score corresponding to a value of $\\ \overline{x} = 16$ is $\\ Z = -2$ .

c) The standard normal z-score corresponding to a value of $\\ \overline{x} = 23$ is $\\ Z = 1.5$ .

d) The probability $\\ P(\overline{x}$ .

e) The probability $\\ P(\overline{x}>23) = 1 - P(Z$ .

f) $\\ P(16 < \overline{x} < 23) = P(-2 < Z < 1.5) = P(Z$ .

Step-by-step explanation:

We are dealing here with the concept of a sampling distribution, that is, the distribution of the sample means $\\ \overline{x}$ .

We know that for this kind of distribution we need, at least, that the sample size must be $\\ n \geq 30$ observations, to establish that:

$\\ \overline{x} \sim N(\mu, \frac{\sigma}{\sqrt{n}})$

In words, the distribution of the sample means follows, approximately, a normal distribution with mean, $\mu$ , and standard deviation (called standard error), $\\ \frac{\sigma}{\sqrt{n}}$ .

The number of observations is n = 64.

We need also to remember that the random variable Z follows a standard normal distribution with $\\ \mu = 0$ and $\\ \sigma = 1$ .

$\\ Z \sim N(0, 1)$

The variable Z is

$\\ Z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}$ [1]

With all this information, we can solve the questions.

Part a

The mean of a sampling distribution of $\\ \overline{x}$ is the population mean $\\ \mu = 20$ or $\\ \mu_{\overline{x}} = \mu = 20$ .

The standard deviation is the population standard deviation $\\ \sigma = 16$ divided by the root square of n, that is, the number of observations of the sample. Thus, $\\ \frac{\sigma}{\sqrt{n}} = \frac{16}{\sqrt{64}}=2$ .

Part b

We are dealing here with a random sample. The z-score for the sampling distribution of $\\ \overline{x}$ is given by [1]. Then

$\\ Z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}$

$\\ Z = \frac{16 - 20}{\frac{16}{\sqrt{64}}}$

$\\ Z = \frac{-4}{\frac{16}{8}}$

$\\ Z = \frac{-4}{2}$

$\\ Z = -2$

Then, the standard normal z-score corresponding to a value of $\\ \overline{x} = 16$ is $\\ Z = -2$ .

Part c

We can follow the same procedure as before. Then

$\\ Z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}$

$\\ Z = \frac{23 - 20}{\frac{16}{\sqrt{64}}}$

$\\ Z = \frac{3}{\frac{16}{8}}$

$\\ Z = \frac{3}{2}$

$\\ Z = 1.5$

As a result, the standard normal z-score corresponding to a value of $\\ \overline{x} = 23$ is $\\ Z = 1.5$ .

Part d

Since we know from [1] that the random variable follows a standard normal distribution, we can consult the cumulative standard normal table for the corresponding $\\ \overline{x}$ already calculated. This table is available in Statistics textbooks and on the Internet. We can also use statistical packages and even spreadsheets or calculators to find this probability.

The corresponding value is Z = -2, that is, it is two standard units below the mean (because of the negative value). Then, consulting the mentioned table, the corresponding cumulative probability for Z = -2 is $\\ P(Z$ .