Respuesta :
Answer:
The test statistic is z = -2.11.
Step-by-step explanation:
Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.
Central Limit Theorem
The Central Limit Theorem establishes 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.
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.
Group 1: Sample of 35, mean of 1276, standard deviation of 347.
This means that:
[tex]\mu_1 = 1276, s_1 = \frac{347}{\sqrt{35}} = 58.6537[/tex]
Group 2: Sample of 35, mean of 1439, standard deviation of 298.
This means that:
[tex]\mu_2 = 1439, s_2 = \frac{298}{\sqrt{35}} = 50.3712[/tex]
Test if there is a difference in productivity level.
At the null hypothesis, we test that there is no difference, that is, the subtraction is 0. So
[tex]H_0: \mu_1 - \mu_2 = 0[/tex]
At the alternate hypothesis, we test that there is difference, that is, the subtraction is different of 0. So
[tex]H_1: \mu_1 - \mu_2 \neq 0[/tex]
The test statistic is:
[tex]z = \frac{X - \mu}{s}[/tex]
In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis and s is the standard error.
0 is tested at the null hypothesis:
This means that [tex]\mu = 0[/tex]
From the two samples:
[tex]X = \mu_1 - \mu_2 = 1276 - 1439 = -163[/tex]
[tex]s = \sqrt{s_1^2+s_2^2} = \sqrt{58.6537^2+50.3712^2} = 77.3144[/tex]
Test statistic:
[tex]z = \frac{X - \mu}{s}[/tex]
[tex]z = \frac{-163 - 0}{77.3144}[/tex]
[tex]z = -2.11[/tex]
The test statistic is z = -2.11.
