An event that cannot happen is a certain b possible c impossible
2 answers:
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Answer:
We conclude that the percentage of employed workers who have registered to vote exceeds the percentage of unemployed workers who have registered to vote.
Step-by-step explanation:
We are given that 513 employed persons and 604 unemployed persons are independently and randomly selected, and that 287 of the employed persons and 280 of the unemployed persons have registered to vote.
Let = <u><em>percentage of employed workers who have registered to vote.</em></u>
= <u><em>percentage of unemployed workers who have registered to vote.</em></u>
So, Null Hypothesis, :
{means that the percentage of employed workers who have registered to vote does not exceeds the percentage of unemployed workers who have registered to vote}
Alternate Hypothesis, :
{means that the percentage of employed workers who have registered to vote exceeds the percentage of unemployed workers who have registered to vote}
The test statistics that would be used here <u>Two-sample z test for proportions;</u>
T.S. = ~ N(0,1)
where, = sample proportion of employed workers who have registered to vote =
= 0.56
= sample proportion of unemployed workers who have registered to vote =
= 0.46
= sample of employed persons = 513
= sample of unemployed persons = 604
So, <u><em>the test statistics</em></u> =
= 3.349
The value of z test statistics is 3.349.
<u>Now, at 0.05 significance level the z table gives critical value of 1.645 for right-tailed test.</u>
Since our test statistic is more than the critical value of z as 3.349 > 1.645, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u>we reject our null hypothesis</u>.
Therefore, we conclude that the percentage of employed workers who have registered to vote exceeds the percentage of unemployed workers who have registered to vote.
Answer:
a) Figure attached
b)
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability with this difference:
An we know using the graph in part a that this area correspond to 0.95 or 95%
c)
And we can find this probability with this difference:
An we know using the graph in part a that this area correspond to 0.95 or 34+34+13.5+2.35%=83.85%
d)
And using the z score we got:
And that correspond to approximately 0.15%
Step-by-step explanation:
Part a
For this case we can see the figure attached.
Previous concepts
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".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Part b
Let X the random variable that represent the length of human pregnancy of a population, and for this case we know that:
Where and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability with this difference:
An we know using the graph in part a that this area correspond to 0.95 or 95%
Part c
And we can find this probability with this difference:
An we know using the graph in part a that this area correspond to 0.95 or 34+34+13.5+2.35%=83.85%
Part d
We want this probability:
And using the z score we got:
And that correspond to approximately 0.15%
