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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 and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
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:
Group 2: Sample of 35, mean of 1439, standard deviation of 298.
This means that:
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
At the alternate hypothesis, we test that there is difference, that is, the subtraction is different of 0. So
The test statistic is:
In which X is the sample mean, is the value tested at the null hypothesis and s is the standard error.
0 is tested at the null hypothesis:
This means that
From the two samples:
Test statistic:
The test statistic is z = -2.11.
the assumption being that "x" is a plain variable whilst "y" is a function, that matters because the chain rule would be needed for a function, not so for a plain variable.
now, we know that y(5) = -23, which is another way of saying that when x = 5, y = -23, but we already knew that, we can get that by simply plugging it into the equation hmmm y'(5), well