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Joon believes that 50% of first-time brides in the United States are younger than their grooms. She performs a hypothesis test to determine if the percentageis the same or different from 50% . Joon samples 100 first-time brides and 53 reply that they are younger than their grooms. For the hypothesis test, she uses a 1% level ofsignificance.

Set up the Hypothesis Test:

The 1% level of significance means that α = 0.01 . This is a test of a single population proportion .

H o : p = 0.50 H a : p 0.50

The words "is the same or different from" tell you this is a two-tailed test.

Calculate the distribution needed:

Random variable: p ̂ = the percent of of first-time brides who are younger than their grooms.

Distribution for the test: The problem contains no mention of a mean. The information is given in terms of percentages. Use the distribution for p ̂ , the estimated proportion.

p ̂ ~ N ( p , p q n ) Therefore, p ̂ ~ N ( 0.5 , 0.5 0.5 100 ) where p = 0.50 , q = 1 - p = 0.50 , and n = 100 .

Calculate the p-value using the normal distribution for proportions:

p-value = P ( p ̂ 0.47 or p ̂ > 0.53 ) = 0.5485

where x = 53 , p ̂ = x n = 53 100 = 0.53 .

Interpretation of the p-value: If the null hypothesis is true, there is 0.5485 probability (54.85%) that the sample (estimated) proportion p ̂ is 0.53 or more OR 0.47 or less (see the graph below).

Normal distribution curve of the percent of first time brides who are younger than the groom with values of 0.47, 0.50, and 0.53 on the x-axis. Vertical upward lines extend from 0.47 and 0.53 to the curve. 1/2(p-values) are calculated for the areas on outsides of 0.47 and 0.53.

μ = p = 0.50 comes from H o , the null hypothesis.

p ̂ = 0.53 . Since the curve is symmetrical andthe test is two-tailed, the p ' for the left tail is equal to 0.50 - 0.03 = 0.47 where μ = p = 0.50 . (0.03 is the differencebetween 0.53 and 0.50.)

Compare α and the p-value:

Since α = 0.01 and p-value = 0.5485 . Therefore, α p-value .

Make a decision: Since α p-value , you cannot reject H o .

Conclusion: At the 1% level of significance, the sample data do not show sufficient evidence that the percentage of first-time brides that are younger than their grooms isdifferent from 50%.

The Type I and Type II errors are as follows:

The Type I error is to conclude that the proportion of first-time brides that are younger than their grooms is different from 50% when, in fact, the proportion is actually 50%.(Reject the null hypothesis when the null hypothesis is true).

The Type II error is there is not enough evidence to conclude that the proportion of first time brides that are younger than their grooms differs from 50% when, in fact, the proportion does differ from 50%. (Do not reject the null hypothesis when the null hypothesis is false.)

Cell Phone Market Research Company conducted a national survey in 2010 and found that 30% of households in the United States owned at least three cell phones. Michele, a statistics student, decided to replicate this study where she lives. She conducts a random survey of 150 households in her town and finds that 53 of the households own at least three cell phones. Is this strong evidence that the proportion of households with at least three cell phone in Michele's town is more than the national percentage? Test at a 5% significance level.

Set up the Hypothesis Test:

H o : p = 0.30 H a : p > 0.30

Determine the distribution needed:

The random variable is p ̂ = proportion of households that have at least three cell phones.

The distribution for the hypothesis test is p ̂ ~ N ( 0.30 , (0.30) (0.70) 150 )

The value that helps determine the p-value is p ̂ . Calculate p ̂ .

p ̂ = x n where x is the number of successes and n is the total number in the sample.

x = 53 , n = 150

p ̂ = 53 150

What is a success for this problem?

A success is having at least three cell phones in a household.

What is the level of significance?

The level of significance is the preset α . Since α is not given, assume that α = 0.05 .

Draw the graph for this problem. Draw the horizontal axis. Label and shade appropriately.

Calculate the p-value.

p-value = 0.077

Make a decision. _____________(Reject/Do not reject) H 0 because____________.

Assuming that α = 0.05, α < p-value . The Decision is do not reject H 0 because there is not sufficient evidence to conclude that the proportion of households that have at least three cell phones is not 30%.

The next example is a poem written by a statistics student named Nicole Hart. The solution to the problem follows the poem. Notice that the hypothesis test is for a singlepopulation proportion. This means that the null and alternate hypotheses use the parameter p . The distribution for the test is normal. The estimated proportion p ̂ is the proportion of fleas killed to the total fleas found on Fido. This is sample information.The problem gives a preconceived α = 0.01 , for comparison, and a 95% confidence interval computation. The poem is clever and humorous, so please enjoy it!

Hypothesis testing problems consist of multiple steps. To help you do the problems, solution sheets are provided for your use. Look in the Table of Contents Appendix for the topic "Solution Sheets." If you like, use copies of the appropriate solution sheet for homework problems.

My dog has so many fleas, They do not come off with ease.As for shampoo, I have tried many types Even one called Bubble Hype,Which only killed 25% of the fleas, Unfortunately I was not pleased.I've used all kinds of soap, Until I had give up hopeUntil one day I saw An ad that put me in awe.A shampoo used for dogs Called GOOD ENOUGH to Clean a HogGuaranteed to kill more fleas. I gave Fido a bathAnd after doing the math His number of fleasStarted dropping by 3's! Before his shampooI counted 42. At the end of his bath,I redid the math And the new shampoo had killed 17 fleas.So now I was pleased. Now it is time for you to have some funWith the level of significance being .01, You must help me figure outUse the new shampoo or go without?

Set up the Hypothesis Test:

H o : p = 0.25 H a : p > 0.25

Determine the distribution needed:

In words, CLEARLY state what your random variable X or p ̂ represents.

p ̂ = The proportion of fleas that are killed by the new shampoo

State the distribution to use for the test.

Normal: N ( 0.25 , ( 0.25 ) ( 1 - 0.25 ) 42 )

Test Statistic: z = 2.3163

Calculate the p-value using the normal distribution for proportions:

p-value = 0.0103

In 1 – 2 complete sentences, explain what the p-value means for this problem.

If the null hypothesis is true (the proportion is 0.25), then there is a 0.0103 probability that the sample (estimated) proportion is 0.4048 ( 17 42 ) or more.

Use the previous information to sketch a picture of this situation. CLEARLY, label and scale the horizontal axis and shade the region(s) corresponding to the p-value.

Normal distribution graph of the proportion of fleas killed by the new shampoo with values of 0.25 and 0.4048 on the x-axis. A vertical upward line extends from 0.4048 to the curve and the area to the left of this is shaded in. The test statistic of the sample proportion is listed.

Compare α and the p-value:

Indicate the correct decision (“reject” or “do not reject” the null hypothesis), the reason for it, and write an appropriate conclusion, using COMPLETE SENTENCES.

alpha decision reason for decision
0.01 Do not reject H o α p-value

Conclusion: At the 1% level of significance, the sample data do not show sufficient evidence that the percentage of fleas that are killed by the new shampoo is more than 25%.

Construct a 95% Confidence Interval for the true mean or proportion. Include a sketch of the graph of the situation. Label the point estimate and the lower and upper bounds of the Confidence Interval.

Normal distribution graph of the proportion of fleas killed by the new shampoo with values of 0.26, 17/42, and 0.55 on the x-axis. A vertical upward line extends from 0.26 and 0.55. The area between these two points is equal to 0.95.

Confidence Interval: ( 0.26 , 0.55 ) We are 95% confident that the true population proportion p of fleas that are killed by the new shampoo is between 26% and 55%.

This test result is not very definitive since the p-value is very close to alpha. In reality, one would probably do more tests by giving the dog another bath after the fleas have had a chance to return.
Practice Key Terms 2

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Source:  OpenStax, Collaborative statistics using spreadsheets. OpenStax CNX. Jan 05, 2016 Download for free at http://legacy.cnx.org/content/col11521/1.23
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