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2 years ago

13

Ms. Jacobson is taking her son and five friends to a trampoline gym. The cost to enter the gym is $9 for each person. Ms. Jacobs

on paid for everyone including herself to enter the gym. How much did she pay for everyone including herself to enter the gym?

1 answer:

Sonja [21]2 years ago

8 0

Answer:

She paid $27

Step-by-step explanation:

9x3

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<h3>Answer: Choice B) 468 cm^2</h3>

============================================================

Explanation:

As the diagram shows, we have a triangular face with a base of b = 18 and height of h = 13. The area of this triangular face is:

A = 0.5*b*h

A = 0.5*18*13

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This is the amount of paint you'll need to cover the outer surface of the pyramid, or you can think of it as the amount of wrapping paper needed. This assumes there are no gaps or overlaps.

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2 years ago

CCN and ActMedia provided a television channel targeted to individuals waiting in supermarket checkout lines. The channel showed

tatyana61 [14]

Answer:

(a) Null Hypothesis, $H_0$ : $\mu$ = 8 minutes

Alternate Hypothesis, $H_A$ : $\mu$ $\neq$ 8 minutes

(b) The P-value of the test statistics is 0.0436.

(c) We conclude that the actual mean waiting time equals the standard at 0.05 significance level.

(d) 95% confidence interval for the population mean is [7.93 minutes , 9.07 minutes].

Step-by-step explanation:

We are given that the length of the program was based on the assumption that the population mean time a shopper stands in a supermarket checkout line is 8 minutes.

A sample of 120 shoppers showed a sample mean waiting time of 8.5 minutes. Assume a population standard deviation of 3.2 minutes.

<u><em>Let </em></u> $\mu$ <u><em> = actual mean waiting time.</em></u>

(a) So, Null Hypothesis, $H_0$ : $\mu$ = 8 minutes {means that the actual mean waiting time does not differs from the standard}

Alternate Hypothesis, $H_A$ : $\mu$ $\neq$ 8 minutes {means that the actual mean waiting time differs from the standard}

The test statistics that would be used here <u>One-sample z test statistics</u> as we know about the population standard deviation;

T.S. = $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ ~ N(0,1)

where, $\bar X$ = sample mean waiting time = 8.5 minutes

$\sigma$ = population standard deviation = 3.2 minutes

n = sample of shoppers = 120

So, <u><em>test statistics</em></u> = $\frac{8.5-8}{\frac{3.2}{\sqrt{120} } }$

= 1.71

The value of t test statistics is 1.71.

(b) Now, the P-value of the test statistics is given by;

P-value = P(Z > 1.71) = 1 - P(Z $\leq$ 1.71)

= 1 - 0.9564 = 0.0436

(c) Now, at 0.05 significance level the z table gives critical values of -1.96 and 1.96 for two-tailed test.

<em>Since our test statistics lies within the range of critical values of z, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which </em><u><em>we fail to reject our null hypothesis</em></u><em>.</em>

Therefore, we conclude that the actual mean waiting time equals the standard.

(d) Now, the pivotal quantity for 95% confidence interval for the population mean is given by;

P.Q. = $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ ~ N(0,1)

where, $\bar X$ = sample mean waiting time = 8.5 minutes

$\sigma$ = population standard deviation = 3.2 minutes

n = sample of shoppers = 120

$\mu$ = population mean

<em>Here for constructing 95% confidence interval we have used One-sample z test statistics as we know about population standard deviation.</em>

<u>So, 95% confidence interval for the population proportion, </u> $\mu$ <u> is ;</u>

P(-1.96 < N(0,1) < 1.96) = 0.95 {As the critical value of z at 2.5% level

of significance are -1.96 & 1.96}

P(-1.96 < $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ < 1.96) = 0.95

P( $-1.96 \times {\frac{\sigma}{\sqrt{n} } }$ < ${\bar X-\mu}$ < $1.96 \times {\frac{\sigma}{\sqrt{n} } }$ ) = 0.95

P( $\bar X-1.96 \times{\frac{\sigma}{\sqrt{n} } }$ < $\mu$ < $\bar X+1.96 \times{\frac{\sigma}{\sqrt{n} } }$ ) = 0.95

<u>95% confidence interval for</u> $\mu$ = [ $\bar X-1.96 \times{\frac{\sigma}{\sqrt{n} } }$ , $\bar X+1.96 \times{\frac{\sigma}{\sqrt{n} } }$ ]

= [ $8.5-1.96 \times{\frac{3.2}{\sqrt{120} } }$ , $8.5+1.96 \times{\frac{3.2}{\sqrt{120} } }$ ]

= [7.93 minutes , 9.07 minutes]

Therefore, 95% confidence interval for the population mean is [7.93 minutes , 9.07 minutes].

Yes, it support our above conclusion.

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3 years ago