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Business sign conservation. The Federal Highway Administration (FHWA) lately issued new guidelines for maintaining and replacing business signs. Civil masterminds at North Carolina State University studied the effectiveness of colorful sign conservation practices developed to cleave to the new guidelines and published the results in the Journal of Transportation Engineering (June 2013). One portion of the study concentrated on the proportion of business signs that fail the minimal FHWA retro-reflectivity conditions. Of signs maintained by the. North Carolina Department of Transportation (NCDOT), .512 were supposed failures. Of signs maintained by. County- possessed roads in North Carolina, 328 were supposed. Failures. Conduct a test of the thesis to determine whether the true proportions of business signs that fail the minimal FHWA retro-reflectivity conditions differ depending on whether the signs are maintained by the NCDOT or by the county. Test using α = .05

Short Answer

Expert verified

The null hypothesis is rejected at α = 0.05.

Step by step solution

01

Step-by-Step Solution Step 1: Check the true proportions of traffic signs

Check whether the true proportions of traffic signs that fail the minimum FHWA retro-reflectivity requirements differ depending on whether the signs are maintained by the NCDOT or by the county.

The test hypotheses are given below:

Null hypothesis:

H₁: P₁-P₁= 0

The true proportions of traffic signs that fall under the minimum FHWA retro-reflectivity requirements do not differ depending on whether the signs are maintained by the NCDOT or the county.

Alternative hypothesis:

Ha:P1P20

The true proportions of traffic signs that fall under the minimum FHWA retro-reflectivity requirements differ depending on whether the signs are maintained by the NCDOT or the county.

02

Use MINITAB

Use MINITAB to obtain the test statistic and p-value for the difference.

MINITAB procedure:

Step 1: Select stat > Basic Statistics > 2 proportions.

Step 2: Select Epitomized data

Step 3: In the First sample, enter Trials and Events as 512.

Step 4: In the Second sample, enter Trials and Events as 328.

Step 5: Check Perform thesis test in Hypothecated proportion, enter 0.

Step 6: Check Options and enter the Confidence position as 95.0.

Step 7: Select not equal in indispensable

Step 8: Click OK in all dialogue boxes.

03

Minitab Output

MINITAB output

Test and CI for Two Proportions

Difference = p (1) – p (2)

Estimate for difference: 0.184

95% CI for difference: (0.141497, 0.226503)

Test for difference = 0 (vs ≠ 0): z = 8.34 p-value = 0.00

Fisher`s exact test: p – value = 0.0000

From the MINITAB output, the value test statistic is 8.34, and the p-value is 0.0000

04

Rejection rule

If the p-value <a, then reject the null hypothesis.

Conclusion:

Here, the p-value is less than the level of significance.

That is, p-value (=0.000) <a=0.05)

Therefore, the null hypothesis is rejected at 2 = 0.05

Thus, it can be concluded that the true proportions of traffic signs that fall under the minimum FHWA retro-reflectivity requirements differ depending on whether the signs are maintained by the NCDOT or by the county.

05

Final answer

The null hypothesis is rejected at α = 0.05.

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Most popular questions from this chapter

It is desired to test H0: m = 75 against Ha: m 6 75 using a = .10. The population in question is uniformly distributed with standard deviation 15. A random sample of size 49 will be drawn from the population.

a. Describe the (approximate) sampling distribution of x under the assumption that H0 is true.

b. Describe the (approximate) sampling distribution of x under the assumption that the population mean is 70.

c. If m were really equal to 70, what is the probability that the hypothesis test would lead the investigator to commit a Type II error?

d. What is the power of this test for detecting the alternative Ha: m = 70?

Question: Independent random samples selected from two normal populations produced the sample means and standard deviations shown below.

Sample 1

Sample 2

n1= 17x¯1= 5.4s1= 3.4

role="math" localid="1660287338175" n2= 12x¯2=7.9s2=4.8

a. Conduct the testH0:(μ1-μ2)>10against Ha:(μ1-μ2)10. Interpret the results.

b. Estimateμ1-μ2 using a 95% confidence interval

Let t0 be a particular value of t. Use Table III in Appendix D to find t0 values such that the following statements are true.

a.=P(-t0<t<t0).95wheredf=10b.P(t-t0ortt0)wheredf=10c.P(tt0)=.05wheredf=10d.P(t-t0ortt0)=.10wheredf=20e.P(t-t0ortt0)=.01wheredf=5

Forensic analysis of JFK assassination bullets. Following theassassination of President John F. Kennedy (JFK) in 1963, the House Select Committee on Assassinations (HSCA) conducted an official government investigation. The HSCA concluded that although there was a probable conspiracy involving at least one shooter in addition to Lee Harvey Oswald, the additional shooter missed all limousine occupants. A recent analysis of assassination bullet fragments, reported in the Annals of Applied Statistics(Vol. 1, 2007), contradicted these findings, concluding that the evidence used by the HSCA to rule out a second assassin is fundamentally flawed. It is well documented that at least two different bullets were the source of bullet fragments found after the assassination. Let E= {bullet evidence used by the HSCA}, T= {two bullets used in the assassination}, and= {more than two bullets used in the assassination}. Given the evidence (E), which is more likely to have occurred— two bullets used (T) or more than two bullets used ?

a. The researchers demonstrated that the ratio,P(T\E)/P(Tc\E), is less than 1. Explain why this result supports the theory of more than two bullets used in the assassination of JFK.

b. To obtain the result, part a, the researchers first showed that P(T\E)P(Tc\E)=[PE\T.PT][PE\Tc.PTc]Demonstrate this equality using Bayes’s Rule.

Random samples of size n1=400 andn2=500 were drawn from populations 1 and 2, respectively. The samples yieldedx1=105 and x2=140. TestH0:p1-p20 againstHa:p1-p2<0at the 1% level of significance.

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