Answer:
(1.06)0 = 1 and positive powers of 1.06 are larger than 1, thus the minimum value N(t) attains, if t≥0, is 400.
From the point of view of the context, a CD account grows in value over time so with a deposit of $400 the value will never drop to $399.
Answer:
$36
Step-by-step explanation:
20x.80=16
20+16=36
Hence, the original price is $36
Answer:(a) margin error = 2.4%
(b) The margin error gives the measure in percentage of how the population parameter determined differ from the real population statistics or value.
(c) in 90% of the samples of teens in the country, the percent who go online several times a day will be within 50.6% and 55.4%. of the estimated 100%
Step-by-step explanation:
Using the proportion formulae
Margin error = z √p(1-p)/n
n= 1170, p = 53% = 0.53, 1-p = 0.47
and the z value at 90% C.I = 1.645
M error= 1.645 √0.53×0.47/1170
Margin error = 0.024 = 0.024 ×100
Margin error = 2.4%
53 - 2.4 = 50.6% and 53 + 2.4 = 55.4%
In other words 90% of the time: the number of teens who go online several time a day will be between 50.6 and 55.4%.
Answer:
x=22° hope it helps:)
Step-by-step explanation:
Please mark it the brainliest if you won't mind:)
(:
Answer:
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:
Step-by-step explanation:
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".
Solution to the problem
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
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: