Given:
Sample Mean <span>= 30<span>
Sample size </span><span><span><span>= 1000</span></span><span>
</span></span></span>Population Standard deviation or <span><span><span>σ<span>=2</span></span><span>
</span></span>Confidence interval </span><span>= 95%</span>
to compute for the confidence interval
Population Mean or <span>μ<span><span>= sample mean ± (</span>z×<span>SE</span>)</span></span>
<span><span>where:</span></span>
<span><span>SE</span>→</span> Standard Error
<span><span>SE</span>=<span>σ<span>√n</span>= 30</span></span>√1000=0.9486
Critical Value of z for 95% confidence interval <span>=1.96</span>
<span>μ<span>=30±<span>(1.96×0.9486)</span></span><span>
</span></span><span>μ<span>=30±1.8594</span></span>
Upper Limit
<span>μ <span>= 30 + 1.8594 = 31.8594</span></span>
Lower Limit
<span>μ <span>= 30 − 1.8594 = <span>28.1406</span></span></span>
<span><span><span>
</span></span></span>
<span><span><span>answer: 28.1406<u<31.8594</span></span></span>
Answer:
a

b

Step-by-step explanation:
From the question we are told that
The sample size is n = 103
The sample mean of sag is 
The sample mean of swells is 
The standard deviation of sag is 
The standard deviation of swells is 
The number of swell for a randomly selected transformer is k = 100
The number of sag for a randomly selected transformer is c = 400
Generally the z-score for the number of swells is mathematically represented as

=> 
=> 
Generally the z-score for the number of sags is mathematically represented as



Answer: B. Y=2/3x
Step-by-step explanation:
Answer:
Idk if its multiple choice but you can do 1 of 2 ways theres using distance formula =√(5-3)sq+(1-4)sq
=√4+9
=√13 <--
or
3.6 units
Given: The two points that are P(5,1) and Q(3,4).
To find: The distance between these two points.
Solution: It is given that there are two points that are P(5,1) and Q(3,4).
The distance between these two points can be found out as using the distance formula that is: 3.6
Thus, the distance between the given two points is 3.6 units.
So you choose 13 or 3.6 Hope this helps :)