Z = 1.555 should be used
If we seek an 88% confidence interval, that means we only want a 12% chance that our interval does not contain the true value.
Assuming a two-sided test, that means we want a 6% chance attributed to each tail of the Z-distribution.
the zα/2 value of z0.06.
This z value at α/2=0.06 is the coordinate of the Z-curve that has 6% of the distribution's area to its right, and thus 94% of the area to its left. We find this z-value by reverse-lookup in a z-table.
<h3>What is Z-distribution?</h3>
The standard normal distribution, also called the z-distribution, is a special normal distribution where the mean is 0 and the standard deviation is 1.
Any normal distribution can be standardized by converting its values into z-scores. Z-scores tell you how many standard deviations from the mean each value lies.
<h3>Why is z-score used?</h3>
The standard score (more commonly referred to as a z-score) is a very useful statistic because it
(a) allows us to calculate the probability of a score occurring within our normal distribution and
(b) enables us to compare two scores that are from different normal distributions.
To learn more about Z-distribution from the given link
brainly.com/question/17039068
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Answer:
- a) x+y
- b) 2x+y
- c) -x
- d) x+y+1
- e) y-x
- f) x/2
Step-by-step explanation:
The applicable rules of logarithms are ...
log(ab) = log(a) +log(b)
log(a^b) = b·log(a)
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Answer:
Step-by-step explanation:
Confidence interval for the difference in the two proportions is written as
Difference in sample proportions ± margin of error
Sample proportion, p= x/n
Where x = number of success
n = number of samples
For city 1,
x = 22
n1 = 155
p1 = 22/155 = 0.14
For city 2,
x = 12
n2 = 135
p2 = 12/135 = 0.09
Margin of error = z√[p1(1 - p1)/n1 + p2(1 - p2)/n2]
To determine the z score, we subtract the confidence level from 100% to get α
α = 1 - 0.95 = 0.05
α/2 = 0.05/2 = 0.025
This is the area in each tail. Since we want the area in the middle, it becomes
1 - 0.025 = 0.975
The z score corresponding to the area on the z table is 1.96. Thus, confidence level of 95% is 1.96
Margin of error = 1.96 × √[0.14(1 - 0.14)/155 + 0.09(1 - 0.09)/135]
= 1.96 × √0.00138344086
= 0.073
Confidence interval = 0.12 - 0.09 ± 0.073
= 0.03 ± 0.073
C. Since the confidence interval does not include zero, there is evidence that the vacancy rates are different between the two cities.
because of the communities property
Answer: B
Step-by-step explanation:
hope this helps