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Yanka [14]
2 years ago
7

I NEED HELP WITH THIS ASAP PLEASEEE!!!!

Mathematics
1 answer:
Bingel [31]2 years ago
7 0

Answer:

1. Marcia

2. (I do not understand what this question is asking)

3. Marcia's estimation is closer

4. 690 people per year

Step-by-step explanation:

1. Marcia's estimation has a greater number of people because he estimated 600 people per year, while Adam estimated 2% of 12,500 (250 people per year).

2. (I do not understand what this question is asking)

3. marcias guess was 600 (600x50+12,500 = 42,500. 42,500 - 35,400 = 7,100) while Adam's guess was 250 per year (250x50+12,500 = 10,400). Therefore, Marcia's guess was closer to 35,400.

4. If Marcia adjusted her answer so that the population in Burbville was ACTUALLY going to be 34,500, she would need to adjust her estimation to 690 people per year.

Hope this helps! So sorry I couldn't understand question 2!

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soldi70 [24.7K]
Length =
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(9 \times 2) + (12 \times 2) = 42 \: ft.
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"Immediately after a ban on using hand-held cell phones while driving was implemented, compliance with the law was measured. A r
sergiy2304 [10]

Answer:

(a) Null Hypothesis, H_0 : p_1-p_2=0  or  p_1= p_2  

    Alternate Hypothesis, H_A : p_1-p_2\neq 0  or  p_1\neq p_2

(b) We conclude that there is a statistical difference in these two proportions measured initially and then one year later.

Step-by-step explanation:

We are given that a random sample of 1,250 drivers found that 98.9% were in compliance. A year after the implementation, compliance was again measured to see if compliance was the same (or not) as previously measured.

A different random sample of 1,100 drivers found 96.9% compliance."

<em />

<em>Let </em>p_1<em> = proportion of drivers that were in compliance initially</em>

p_2<em> = proportion of drivers that were in compliance one year later</em>

(a) <u>Null Hypothesis</u>, H_0 : p_1-p_2=0  or  p_1= p_2      {means that there is not any statistical difference in these two proportions measured initially and then one year later}

<u>Alternate Hypothesis</u>, H_A : p_1-p_2\neq 0  or  p_1\neq p_2     {means that there is a statistical difference in these two proportions measured initially and then one year later}

The test statistics that will be used here is <u>Two-sample z proportion statistics</u>;

                     T.S.  = \frac{(\hat p_1-\hat p_2)-(p_1-p_2)}{\sqrt{ \frac{\hat p_1(1-\hat p_1)}{n_1} + \frac{\hat p_2(1-\hat p_2)}{n_2}} }  ~ N(0,1)

where, \hat p_1 = sample proportion of drivers in compliance initially = 98.9%

\hat p_2 = sample proportion of drivers in compliance one year later = 96.9%

n_1 = sample of drivers initially = 1,250

n_2 = sample of drivers one year later = 1,100

(b) So, <u><em>the test statistics</em></u>  =  \frac{(0.989-0.969)-(0)}{\sqrt{ \frac{0.989(1-0.989)}{1,250} + \frac{0.969(1-0.969)}{1,100}} }  

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<u>Now, P-value of the test statistics is given by;</u>

         P-value = P(Z > 3.33) = 1 - P(Z \leq 3.33)

                                            = 1 - 0.99957 = <u>0.00043</u>

Since in the question we are not given with the level of significance so we assume it to be 5%. Now at 5% significance level, the z table gives critical values between -1.96 and 1.96 for two-tailed test.

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

Therefore, we conclude that there is a statistical difference in these two proportions measured initially and then one year later.

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Step-by-step explanation:

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