Answer:
116.113cm2 is the purple reigon area
Step-by-step explanation:
using pi r squared
1st circle area: 16.619
2nd circle area: 132.7322
1st - 2nd = 116.113 cm2
Add the complex numbers: (4 + 8i) + (–2 – i)
Answer:
2 + 7i
Step-by-step explanation:
(4 + 8i) + (-2 - i)
open the brackets
4 + 8i - 2 - i
add or subtract like terms
2 + 7i
Answer:
2+7i
Step-by-step explanation:
Open the brackets.
4+8i-2-i
You will get…
2+7i
B: 751.29
C: 1954.13
D: 1536.19
Solution:
use formula P[((1+(r/n)^(nt))-1)/(r/n)]
Solution 50[((1+(0.48/12)^(2 x 12))-1)/(0.48/12)]
= C $1954.13
It is given that you have invested $50 a month in an annuity that earns 48% APR compounded monthly. We can conclude that after 2 years you will have $1954.13 in your account.
To solve this we are going to use the formula for the future value of an ordinary annuity:
where
FV is the future value
P is the periodic payment
r is the interest rate in decimal form
n is the number of times the interest is compounded per year
t is the number of years
It is given that you have invested $50 a month in an annuity that earns 48% APR compounded monthly. we need to find how much money you have in this account after 2 years.
Since the interest is compounded monthly, it is compounded 12 times per year; therefore,
r = 48% = 0.48
n = 12
Let's put the values in our formula:
Thus, We can conclude that after 2 years you will have $1954.13 in your account.
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Answer:
The answer is - budget constraint
Step-by-step explanation:
The slope of the budget constraint is determined by the relative price of the two goods, which is calculated by taking the price of one good and dividing it by the price of the other good.
A budget constraint happens when a consumer demonstrates limited consumption patterns by a certain income.
Answer:
The probability that the O-ring came from Galshus and Sons given that it is defective is 0.359.
Step-by-step explanation:
Probability of getting O-ring from Little Rock Plastics = 0.29
Probability of getting O-ring from Galshus and Sons = 0.71
Probability of getting Defective Rings from Little Rock Plastics = 0.04
Probability of getting Defective Rings from Galshus and Sons = 0.10
Denoting Little Rock Plastics as LRP, Galshus and Sons as GS and Defective as D, we can write:
P(LRP) = 0.29
P(GS) = 0.71
P(D ∩ LRP) = 0.04
P(D ∩ GS) = 0.10
We are given that an O-ring is found to be defective and we need to find the probability that it came from Galshus and Sons so we will use the conditional probability formula for calculating the probability that the O-ring came from Galshus and Sons given that it is defective.
P(GS|D) = P(D ∩ GS)/P(D)
We need to compute P(D) first. So,
P(D) = P(D|GS) + P(D|LRP)
= P(D∩GS)/P(GS) + P(D∩LRP)/P(LRP)
= 0.10/ 0.71 + 0.04/0.29
= 0.1408 + 0.1379
P(D) = 0.2787
P(GS|D) = P(D ∩ GS)/P(D)
= 0.10/0.2787
= 0.3587
P(GS|D) = 0.359
Using Bayes' theorem, the probability that a defective O-ring came from Galshus and Sons is approximately 0.802 or 80.2%
To find the answer to your question, we need to use Bayes' theorem. This theorem refers to the probability of an event, based on prior knowledge of conditions that might be related to the event. First, let us identify the following:
Probability of choosing an O-ring from Little Rock Plastics (L), P(L) = 0.29
Probability of choosing an O-ring from Galshus and Sons (G), P(G) = 1 - P(L) = 0.71
Probability that an O-ring from Little Rock is defective, P(D|L) = 0.04
Probability that an O-ring from Galshus and Sons is defective, P(D|G) = 0.10
By Bayes' theorem, the probability that a defective O-ring came from Galshus and Sons is given by: P(G|D) = [P(G) * P(D|G)] / [P(L) * P(D|L) + P(G) * P(D|G)]
Upon substitution, P(G|D) = [0.71 * 0.10] / [0.29 * 0.04 + 0.71 * 0.10]. This equates to approximately 0.802, or 80.2%, meaning there is a 80.2% chance that the defective O-ring came from Galshus and Sons.
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Step 2: The null hypothesis and alternative hypothesis?
Step 5: whats the p-value is:
Answer:
Parameter = 0.5
Null hypothesis : H0 : P0 = 0.5
Alternative hypothesis ; H0 : P0 > 0.5
Pvalue = 0.99966
Step-by-step explanation:
The parameter defines a statistical value or calculation which is derived from the population.
The parameter in this scenario is the population proportion, P0 which is 0.5
The scenario above describes a scenario to test the difference in population.
The null hypothesis, that bride and groom are of the same age ;
H0 : P0 = 0.5
The alternative hypothesis ; the bride is younger Than the groom in more than half of the population.
H1 : p0 > 0.5
To obtain the Pvalue :
Test statistic : (phat - P0) ÷ √(p0(1 -p0) / n)
Phat = x/n
x = 67 ; sample size, n = 100
Phat = x / n = 67/100 = 0.67
P0 = 1 - 0.5 = 0.5
Tstatistic = (0.67-0.50) ÷ √(0.5(0.5) / 100)
Tstatiatic = 0.17 ÷ 0.05
Tstatistic = 3.4
P-value : p(Z < 3.4) = 0.99966 (Z probability calculator).