A survey of 1000 students found that 274 chose professional baseball team A as their favorite team. In a similar survey involving 760 students, 240 of them chose team A as their favorite. Compute a 95% con- fidence interval for the difference between the propor- tions of students favoring team A in the two surveys. Is there a significant difference?

Respuesta :

Answer:

The 95% confidence interval would be given (-0.0851;0.00108).  

We are confident at 95% that the difference between the two proportions is between [tex]-0.0851 \leq p_A -p_{A'} \leq 0.00108[/tex]

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

The margin of error is the range of values below and above the sample statistic in a confidence interval.  

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

[tex]p_A[/tex] represent the real population proportion for brand A  

[tex]\hat p_A =\frac{274}{1000}=0.274[/tex] represent the estimated proportion for team A 1

[tex]n_A=1000[/tex] is the sample size

[tex]p_{A'}[/tex] represent the real population proportion for team A 2  

[tex]\hat p_{A'} =\frac{240}{760}=0.316[/tex] represent the estimated proportion for team A 2

[tex]n_{A'}=760[/tex] is the sample size required for team A 2

[tex]z[/tex] represent the critical value for the margin of error  

The population proportion have the following distribution  

[tex]p \sim N(p,\sqrt{\frac{p(1-p)}{n}})[/tex]  

The confidence interval for the difference of two proportions would be given by this formula  

[tex](\hat p_A -\hat p_{A'}) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_{A'} (1-\hat p_{A'})}{n_{A'}}}[/tex]  

For the 95% confidence interval the value of [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2=0.025[/tex], with that value we can find the quantile required for the interval in the normal standard distribution.  

[tex]z_{\alpha/2}=1.96[/tex]  

And replacing into the confidence interval formula we got:  

[tex](0.274-0.316) - 1.96 \sqrt{\frac{0.274(1-0.274)}{1000} +\frac{0.316(1-0.316)}{760}}=-0.0851[/tex]  

[tex](0.274-0.316) + 1.96 \sqrt{\frac{0.274(1-0.274)}{1000} +\frac{0.316(1-0.316)}{760}}=0.00108[/tex]  

And the 95% confidence interval would be given (-0.0851;0.00108).  

We are confident at 95% that the difference between the two proportions is between [tex]-0.0851 \leq p_A -p_{A'} \leq 0.00108[/tex]

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