A researcher claims that the mean annual cost of raising a child (age 2 and under) by husband-wife families in the U.S. is $13,960. In a random sample of husband-wife families in the U.S. the mean annual cost of raising a child (age 2 and under) is $13,725. The sample consists of 500 children and the population standard deviation is $2,345. At the Ξ± = 0.10, is there enough evidence to reject the claim? Use the p-value approach.

Respuesta :

Answer:

[tex]z=\frac{13725-13960}{\frac{2345}{\sqrt{500}}}=-2.24[/tex] Β  Β 

[tex]p_v =2*P(z<-2.24)=0.0251[/tex] Β 

If we compare the p value and the significance level given [tex]\alpha=0.1[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is different from 13960 at 10% of signficance.

Step-by-step explanation:

Data given and notation Β 

[tex]\bar X=13275[/tex] represent the sample mean

[tex]\sigma=2345[/tex] represent the sample standard deviation

[tex]n=500[/tex] sample size Β 

[tex]\mu_o =68[/tex] represent the value that we want to test

[tex]\alpha=0.1[/tex] represent the significance level for the hypothesis test. Β 

t would represent the statistic (variable of interest) Β 

[tex]p_v[/tex] represent the p value for the test (variable of interest) Β 

State the null and alternative hypotheses. Β 

We need to conduct a hypothesis in order to check if the true mean is 13960, the system of hypothesis would be: Β 

Null hypothesis:[tex]\mu = 13690[/tex] Β 

Alternative hypothesis:[tex]\mu \neq 13690[/tex] Β 

If we analyze the size for the sample is > 30 and we know the population deviation so is better apply a z test to compare the actual mean to the reference value, and the statistic is given by: Β 

[tex]z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}[/tex] Β (1) Β 

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value". Β 

Calculate the statistic

We can replace in formula (1) the info given like this: Β 

[tex]z=\frac{13725-13960}{\frac{2345}{\sqrt{500}}}=-2.24[/tex] Β  Β 

P-value

Since is a two sided test the p value would be: Β 

[tex]p_v =2*P(z<-2.24)=0.0251[/tex] Β 

Conclusion Β 

If we compare the p value and the significance level given [tex]\alpha=0.1[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is different from 13960 at 10% of signficance.

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