Answer:
Step-by-step explanation:
a. P(Z > 1.12) = 1-N(1.12) = 1-0.8686431=0.1313569
b. <em>P(Z S-2.35)</em> => P(Z <= 2.35) = 0.009386706
(please check interpretation of question b)
c. <em>POSZ s 1.34)</em> => P(0 <= Z <= 1.34) = 0.9098773 - 0.5 = 0.4098773
(please check interpretation of question c)
d. P(-0.8 sz s 2.44) => P(-0.8 <= 2.44) = 0.9926564 - 0.2118554 = 0.780801
(please check interpretation of question d)
Answer:
Partial-fraction decomposition is the process of starting with the simplified answer and taking it back apart, of "decomposing" the final expression into its initial polynomial fractions.
For example, Partial fraction decomposition is used to integrate rational functions and in engineering for finding inverse Laplace transforms.
Step-by-step explanation:
First take your whole number which is 6, then your decimals so it would be 6 1/3 but with a fraction sign 6 would go outside, 1 would go on top of 3.
3, because one cube means like from a certain view the 2-d model IS one block high so 1x16, 2x8, and 4x4.
Answer:
Since they use random sampling then we can conclude that the two estimators would be unbiased of the real parameter.
So then the best answer would be:
c. The sample proportion, ^p, in either proposal is equally likely to be close to the true population proportion, p, since the sampling is random.
Step-by-step explanation:
For this case we have a first sample size and from this sample we have people who anwswer yes and the estimated proportion of yes is given by:
And let a second sample size and from this sample we have people who anwswer yes and the estimated proportion of yes is given by:
For this case we know that the true proportion is
Since they use random sampling then we can conclude that the two estimators would be unbiased of the real parameter.
So then the best answer would be:
c. The sample proportion, ^p, in either proposal is equally likely to be close to the true population proportion, p, since the sampling is random.