Respuesta :
Answer:
The 90% confidence interval for the difference of the population means is approximately (-17.98, -2.02).
Step-by-step explanation:
Before building the confidence interval, we need to understand the central limit theorem and subtraction of normal variables.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]
Subtraction between normal variables:
When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.
Boys:
Mean of 75, sample of 45, standard deviation of 25.
This means that [tex]\mu_B = 75, s_B = \frac{25}{\sqrt{45}}[/tex]
Girls:
Mean of 85, sample of 30, standard deviation of 17.
This means that [tex]\mu_G = 85, s_G = \frac{17}{\sqrt{30}}[/tex]
Distribution of the difference of mean grades of boys and girls:
[tex]\mu = \mu_B - \mu_G = 75 - 85 = -10[/tex]
[tex]s = \sqrt{s_B^2+s_G^2} = \sqrt{(\frac{25}{\sqrt{45}})^2+(\frac{17}{\sqrt{30}})^2} = 4.85[/tex]
Confidence interval:
As stated, the critical value is [tex]z = 1.645[/tex]
The margin of error is of:
[tex]M = zs = 1.645*4.85 = 7.98[/tex]
Lower bound:
[tex]\mu - M = -10 - 7.98 = -17.98[/tex]
Upper bound:
[tex]\mu + M = -10 + 7.98 = -2.02[/tex]
The 90% confidence interval for the difference of the population means is approximately (-17.98, -2.02).
