Answer:
When we compare the significance level 
we see that 
so we can reject the null hypothesis at 10% of significance. So the the true mean is difference from 21 at this significance level.
Step-by-step explanation:
Data given and notation
represent the sample mean
represent the population standard deviation
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
z would represent the statistic (variable of interest)
represent the p value for the test (variable of interest)
State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the average age of the evening students is significantly different from 21, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
The statistic is given by:
(1)
Calculate the statistic
We can replace in formula (1) the info given like this:
P-value
Since is a two sided test the p value would be:
Conclusion
When we compare the significance level we see that so we can reject the null hypothesis at 10% of significance. So the the true mean is difference from 21 at this significance level.
<span>1. </span>When given a raw score, it must be converted
into a z-score (standard score). Raw scores cannot be placed on a normal
distribution curve because they do not have the same means and standard
deviations, but when it is converted into a z-score, the number of standard
deviations above or below the population mean can be measured. The z-scores on
the center are average, the scores on the left are lower than average and the
scores on the right are higher than average.
<span>2. </span>A z-score is a standard score which can be
placed on a normal distribution curve. A z-score indicates the distance of the
standard deviations from the mean (center of the curve).
The answer is (3x - 4) (x + 3)
Answer:
Parallel
Step-by-step explanation:
Answer:
(
n
−
5
)
(
2
n
+
9
)
Step-by-step explanation:
Factor by grouping
