Answer:
= 2.48 × 10¹²
(scientific notation)
= 2.48e12
(scientific e notation)
= 2.48 × 10¹²
(engineering notation)
(trillion; prefix tera- (T))
= 2480000000000
<span>(real number)</span>
Can barely see the questions ! Retake a picture if you can.
Answer:
Therefore, the probability that at least half of them need to wait more than 10 minutes is <em>0.0031</em>.
Step-by-step explanation:
The formula for the probability of an exponential distribution is:
P(x < b) = 1 - e^(b/3)
Using the complement rule, we can determine the probability of a customer having to wait more than 10 minutes, by:
p = P(x > 10)
= 1 - P(x < 10)
= 1 - (1 - e^(-10/10) )
= e⁻¹
= 0.3679
The z-score is the difference in sample size and the population mean, divided by the standard deviation:
z = (p' - p) / √[p(1 - p) / n]
= (0.5 - 0.3679) / √[0.3679(1 - 0.3679) / 100)]
= 2.7393
Therefore, using the probability table, you find that the corresponding probability is:
P(p' ≥ 0.5) = P(z > 2.7393)
<em>P(p' ≥ 0.5) = 0.0031</em>
<em></em>
Therefore, the probability that at least half of them need to wait more than 10 minutes is <em>0.0031</em>.
Answer:
D 40,000nm
Step-by-step explanation: 1nm/10^-9m * 10^-6/1um = 10^3 nm/um
Therefore in 40 microns there are:
40um * 10^3 nm/um = 40 * 10^3 nm = 40,000 nm
Answer:
We accept H₀ , we do not have enought evidence for rejecting H₀
Step-by-step explanation:
Normal Distribution
sample size n = 60
standard deviation σ = 15
1.Hypothesis Test : Is a one tailed-test on the right
H₀ null hypothesis μ₀ = 50
Hₐ alternative hypothesis μ₀ > 50
2.-We will do the test for a significance level α = 0,01 tht means for a 99% interval of confidence
then z(c) = 2.32
3.- We compute z(s)
z(s) = [ ( μ - μ₀ ) /( σ/√n ) ⇒ z(s) = ( 2 * √60 ) / 15
z(s) = 15.49/15 ⇒ z(s) = 1.033
4.- We compare values of z(c) and z(s)
z(s) < z(c) 1.033 < 2.32
z(s) is in the acceptance region so we accept H₀ , we do not have enough evidence for rejecting H₀