Q: How much did Jay have to pay excluding his share of the insurance premium?
A: $1800+$200 = $2000
Q: How much did Jay's company pay for his insurance premium?
A: $700. If Jay's $350 is 1/3 of the premium , then Jay's company pays 2*$350=$700 as rest of his premium.
Q: Jay paid 10% and the plan paid 90% beyond the deductible. How much did Jay's insurance company pay total?
A: Jay's insurance company paid $16200. Given that Jay paid $1800 beyond his deductible of $200 (and that is 10% of the actual cost) means that his plan (insurance company) paid 90%=9*$1800=$16200.
Q: How much did Jay have to pay total, including his share of the premium?
A: Jay paid $2350. He paid $200 deductible + $1800 beyond deductible + $350 premium
Answer: sometimes
Step-by-step explanation:
Answer:it is c
Step-by-step explanation:
fjhrhgvfj
PV × (1 + r/n)∧nt = FV
$70.00 × (1 + .16/4)∧4X25 = FV
$70.00 × (1 + .04)∧100 = FV
$70.00 × 50.50 = FV
$3535 =FV
The final amount is $3535
Answer:
![P(X=1)](https://tex.z-dn.net/?f=%20P%28X%3D1%29)
And using the probability mass function we got:
![P(X=1) = (5C1) (0.25)^1 (1-0.25)^{5-1}= 0.396](https://tex.z-dn.net/?f=%20P%28X%3D1%29%20%3D%20%285C1%29%20%280.25%29%5E1%20%281-0.25%29%5E%7B5-1%7D%3D%200.396)
Step-by-step explanation:
Previous concepts
The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".
Solution to the problem
For this cae that one buggy whip would be defective is ![p = \frac{5}{20}=0.25](https://tex.z-dn.net/?f=%20p%20%3D%20%5Cfrac%7B5%7D%7B20%7D%3D0.25)
Let X the random variable of interest, on this case we now that:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
And we want to find this probability:
![P(X=1)](https://tex.z-dn.net/?f=%20P%28X%3D1%29)
And using the probability mass function we got:
![P(X=1) = (5C1) (0.25)^1 (1-0.25)^{5-1}= 0.396](https://tex.z-dn.net/?f=%20P%28X%3D1%29%20%3D%20%285C1%29%20%280.25%29%5E1%20%281-0.25%29%5E%7B5-1%7D%3D%200.396)