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konstantin123 [22]
3 years ago
14

Happy New Year!!

Mathematics
1 answer:
Kazeer [188]3 years ago
4 0

145÷7.25 = 20

Step-by-step explanation:

This is a simple division of numbers with decimals.

Here we have dividend ( the number to be divided) (or numerator) = 145

and divisor (the number which divides dividend) (or denominator)= 7.25

Now, in case of decimals in denominator, we add number of zeroes in numerator equal to number of digits after decimal point in denominator, and thus the decimal point gets removed. So, this gives us 14500÷725, which by simple calculation is equal to 20.

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An economist uses the price of a gallon of milk as a measure of inflation. She finds that the average price is $3.82 per gallon
salantis [7]

Answer:

(a) The standard error of the mean in this experiment is $0.052.

(b) The probability that the sample mean is between $3.78 and $3.86 is 0.5587.

(c) The probability that the difference between the sample mean and the population mean is less than $0.01 is 0.5754.

(d) The likelihood that the sample mean is greater than $3.92 is 0.9726.

Step-by-step explanation:

According to the Central Limit Theorem if we have an unknown population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 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:

n=40\\\mu=\$3.82\\\sigma=\$0.33

As <em>n</em> = 40 > 30, the distribution of sample mean is \bar X\sim N(3.82,\ 0.052^{2}).

(a)

The standard error is the standard deviation of the sampling distribution of sample mean.

Compute the standard deviation of the sampling distribution of sample mean as follows:

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

    =\frac{0.33}{\sqrt{40}}\\\\=0.052178\\\\\approx 0.052

Thus, the standard error of the mean in this experiment is $0.052.

(b)

Compute the probability that the sample mean is between $3.78 and $3.86 as follows:

P(3.78

                               =P(-0.77

Thus, the probability that the sample mean is between $3.78 and $3.86 is 0.5587.

(c)

If the difference between the sample mean and the population mean is less than $0.01 then:

\bar X-\mu_{\bar x}

Compute the value of P(\bar X as follows:

P(\bar X

                    =P(Z

Thus, the probability that the difference between the sample mean and the population mean is less than $0.01 is 0.5754.

(d)

Compute the probability that the sample mean is greater than $3.92 as follows:

P(\bar X>3.92)=P(\frac{\bar X-\mu_{\bar x}}{\sigma_{\bar x}}>\frac{3.92-3.82}{0.052})

                    =P(Z

Thus, the likelihood that the sample mean is greater than $3.92 is 0.9726.

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Answer:

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Step-by-step explanation:

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hope this helps

i would appreciate it if u can heart and like my answer and maybe even give it 5 stars or brainliest pls i beg u thx !!! : )

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