Can someone help me solve this equation?

What is 2/3 - 8/12 please help me understand this :)

ANEK [815]

You times the denominator from 2/3 by 4 so it can be equivalent to 8/12
2/3 x 4 = 8/12-8/12=0

3 0

4 years ago

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What do both of these functions have in common? f(x)=5e^x+5 g(x)=0.5(x-5)^2-5

kondor19780726 [428]

Answer:

They have the same vertical shift. -Apex

Step-by-step explanation:

3 0

3 years ago

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In a survey, the planning value for the population proportion is . How large a sample should be taken to provide a confidence in

tatuchka [14]

Answer:

n=350

Step-by-step explanation:

Notation and definitions

$n$ random sample taken (variable of interest)

$\hat p=0.35$ estimated proportion (value assumed)

$p$ true population proportion

Confidence =0.95 or 95% (value assumed)

Me=0.05 (value assumed)

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The population proportion have the following distribution

$p \sim N(p,\sqrt{\frac{\hat p(1-\hat p)}{n}})$

In order to find the critical value we need to take in count that we are finding the interval for a proportion, so on this case we need to use the z distribution. Since our interval is at 95% of confidence, our significance level would be given by $\alpha=1-0.95=0.05$ and $\alpha/2 =0.025$ . And the critical value would be given by:

$z_{\alpha/2}=-1.96, z_{1-\alpha/2}=1.96$

The margin of error for the proportion interval is given by this formula:

$ME=z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}$ (a)

And on this case we have that $ME =\pm 0.05$ and we are interested in order to find the value of n, if we solve n from equation (a) we got:

$n=\frac{\hat p (1-\hat p)}{(\frac{ME}{z})^2}$ (b)

And replacing into equation (b) the values from part a we got:

$n=\frac{0.35(1-0.35)}{(\frac{0.05}{1.96})^2}=349.586$

And rounded up we have that n=350

4 0

3 years ago

Mrs.Stone is three times older than her younger daughter, Joyce, but only two times older than her older daughter, Alex. How old

olchik [2.2K]

Answer:

54 years

Step-by-step explanation:

Joyce age = x

Alex age = y

3x = 2y - - - (1)

y - 9 = 2(x - 9)

y - 9 = 2x - 18

-9 + 18 = 2x - y

9 = 2x - y

y = 2x - 9 - - (2)

3x = 2y

3x = 2(2x - 9)

3x = 4x - 18

18 = 4x - 3x

18 = x

Hence,

Mrs stone is 3 * 18 = 54 years

5 0

3 years ago

The amount people pay for cable service varies quite a bit but the mean monthly fee is $142 and the standard deviation is $29. t

zhuklara [117]

Answer:

a) By the Central Limit Theorem, the mean is $142 and the standard deviation is $0.7488.

b) By the Central Limit Theorem, approximately normal.

c) 0.0901 = 9.01% probability that the average cable service paid by the sample of cable service customers will exceed $143

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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.

The mean monthly fee is $142 and the standard deviation is $29.

This means that $\mu = 142, \sigma = 29$

Part a: what are the mean an standard deviation of the sample distribution of x hat show your work and justify your reasoning.

Sample of 1500(larger than 30).

By the Central Limit Theorem

The mean is $142

The standard deviation is $s = \frac{29}{\sqrt{1500}} = 0.7488$

Part b: what is the shape of the sampling distribution of x hat justify your answer.

By the Central Limit Theorem, approximately normal.

Part C: what is the probability that the average cable service paid by the sample of cable service customers will exceed $143?

This is 1 subtracted by the pvalue of Z when X = 143. So

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

By the Central Limit Theorem

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

$Z = \frac{143 - 142}{0.7488}$

$Z = 1.34$

$Z = 1.34$ has a pvalue of 0.9099

1 - 0.9099 = 0.0901

0.0901 = 9.01% probability that the average cable service paid by the sample of cable service customers will exceed $143

4 0

3 years ago