Step-by-step explanation:
Hey there!
0.3 = 3/8 (equal to eachother)
Reason: (<u>3</u><u>/</u><u>8</u><u> </u><u>=</u><u> </u><u>0.375</u><u>)</u>
<u>So</u><u>,</u><u> </u><u>0</u><u>.</u><u>3</u><u> </u><u>is</u><u> </u><u>equal</u><u> </u><u>to</u><u> </u><u>eachother</u><u>. </u>
<u>0</u><u>.</u><u>3</u><u>=</u><u>0</u><u>.</u><u>3</u>
<em><u>Hope it helps</u></em><em><u>.</u></em><em><u>.</u></em><em><u>.</u></em>
Answer:
15 units
Step-by-step explanation:

d = 14.866
d = 15
Answer:
a=1/2
Step-by-step explanation:
first we need to isolate a squared. so we add 1/4 to both sides
then you take the square root of a square to get 1/2
to check, 1/2 * 1/2 = 1/4
1/4-1/4 = 0
Answer: (a). 99 percent of the sample proportions results in a 99% confidence interval that includes the population proportion.
(b). 1 percent of the sample proportions results in a 99% confidence interval that does not include the population proportion.
Step-by-step explanation:
(a). 99 percent of the sample proportions results in a 99% confidence interval that includes the population proportion.
Explanation: If multiple samples were drawn from the same population and a 99% CI calculated for each sample, we would expect the population proportion to be found within 99% of these confidence intervals.
(b). 1 percent of the sample proportions results in a 99% confidence interval that does not include the population proportion.
Explanation: The 99% of the confidence intervals includes the population proportion value, it means, the remaining (100% – 99%) 1% of the intervals does not includes the population proportion.
If multiple samples were drawn from the same population and a 99% CI calculated for each sample, we would expect the population proportion to be found within 99% of these confidence intervals and 1 percent of the sample proportions results in a 99% confidence interval that does not include the population proportion.
Answer:
P = 0.006
Step-by-step explanation:
Given
n = 25 Lamps
each with mean lifetime of 50 hours and standard deviation (SD) of 4 hours
Find probability that the lamp will be burning at end of 1300 hours period.
As we are not given that exact lamp, it means we have to find the probability where any of the lamp burning at the end of 1300 hours, So we have
Suppose i represents lamps
P (∑i from 1 to 25 (
> 1300)) = 1300
= P(
>
) where
represents mean time of a single lamp
= P (Z>
) Z is the standard normal distribution which can be found by using the formula
Z = Mean Time (
) - Life time of each Lamp (50 hours)/ (SD/
)
Z = (52-50)/(4/
) = 2.5
Now, P(Z>2.5) = 0.006 using the standard normal distribution table
Probability that a lamp will be burning at the end of 1300 hours period is 0.006