Mathematics, 20.12.2019 19:31 vallhernandez13

In making plans for an executive traveler’s club, an airline would like to estimate the proportion of its current customers who would qualify for membership. a random sample of 500 customers yielded 40 who would qualify.

(a) test the hypothesis h0 : p = 0.05 vs ha : p < 0.05 by constructing reject region at α = 0.1 state what action the airline should take.
(b) compute the p-value using r.

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Answer from: saifallahassefa

a) $\hat p = 0.05 -1.28 \sqrt{\frac{0.05 (1-0.05)}{500}}=0.0375$

So the rejection zone would be given by $\hat p$ In our case since the estimated proportion is 0.08 we are not on the rejection zone so we FAIL to reject the null hypothesis.

b) prop.test(40, 500, p = 0.05,alternative = c("less"),conf.level = 0.95, correct = FALSE)

With the following output

1-sample proportions test without

continuity correction

data: 40 out of 500, null probability 0.05

X-squared = 9.4737, df = 1, p-value = 0.999

alternative hypothesis: true p is less than 0.05

95 percent confidence interval:

0.000000 0.102291

sample estimates:

0.08

Step-by-step explanation:

Data given and notation

n=500 represent the random sample taken

X=40 represent the customers who would qualify for membership

$\hat p=\frac{40}{500}=0.08$ estimated proportion of adults that said that it is morally wrong to not report all income on tax returns

p_o=0.05 is the value that we want to test

$\alpha$ represent the significance level

z would represent the statistic (variable of interest)

$p_v{/tex} represent the p value (variable of interest) Concepts and formulas to use We need to conduct a hypothesis in order to test the claim that the true proportion is less than 0.05.: Null hypothesis:[tex]p\geq 0.05$

Alternative hypothesis: p < 0.05

When we conduct a proportion test we need to use the z statisitc, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value p_o .

Part a

The population proportion have the following distribution

$p \sim N(p,\sqrt{\frac{p(1-p)}{n}})$

And we know that the z score is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$

And we are interested to find the value of $hat p[\tex] in order to reject the null hypothesis. So we need to find a z value that accumulates 0.1 of the area on the left and this value is [tex]z_{0.1}=-1.28$

$-1.28=\frac{\hat p -0.05}{\sqrt{\frac{0.05 (1-0.05)}{500}}}$

And if we solve for $hat p[\tex] we got:[tex]\hat p = 0.05 -1.28 \sqrt{\frac{0.05 (1-0.05)}{500}}=0.0375$

So the rejection zone would be given by $\hat p$ In our case since the estimated proportion is 0.08 we are not on the rejection zone so we FAIL to reject the null hypothesis.

Part b

prop.test(40, 500, p = 0.05,alternative = c("less"),conf.level = 0.95, correct = FALSE)

With the following output

1-sample proportions test without

continuity correction

data: 40 out of 500, null probability 0.05

X-squared = 9.4737, df = 1, p-value = 0.999

alternative hypothesis: true p is less than 0.05

95 percent confidence interval:

0.000000 0.102291

sample estimates:

0.08

Answer from: Quest

can you put the picture up?

step-by-step explanation:

Answer from: Quest

answer: bea's uncle is 25 years old.

step-by-step explanation:

given the equation $3x- 15= 60$ , we can say that the variable "x" represents the age of bea's uncle. then to find his age, we need to solve for "x":

we must add 15 to both sides of the equation:

$3x- 15+(15)= 60+(15)\\3x=75$

now we need to divide both sides of the equation by 3:

$\frac{3x}{3}=\frac{75}{3}\\\\x=25$

therefore, we can conclude that bea's uncle is 25 years old.

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