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siniylev [52]
3 years ago
11

Amy purchased a five-year $5,250 bond below par value for $4,675 with a coupon of 3.5%. What was her yield?

Mathematics
1 answer:
Aleksandr [31]3 years ago
5 0

Answer:

3.9%

Step-by-step explanation:

All I know is I got it wrong from the other answer, and it says 3.9% is the right answer.

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What is the period of the sine funtion y = sin (2x) ?
Margarita [4]

Answer: a

Step-by-step explanation:

2x=2\pi

x=\pi ==> Period: \pi ==> a

8 0
1 year ago
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Jason tossed a fair coin 3 times. what is the probability of getting a head and two tails in any order?
mixer [17]

Step-by-step explanation:

fair coin is two sided Head H and Tail T

thrown 3 times

number of sample space n(s)=2³=>8

sample space (s)={HHH,HHT,HTH,HTT,THH,TTH,THT,TTT}

no of a head and two tails= 3/8

4 0
1 year ago
A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The s
Fofino [41]

Answer:

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

In this question, we have that:

\mu = 270, \sigma = 90, n = 18, s = \frac{90}{\sqrt{18}} = 21.2

What is the probability that 18 randomly selected bulbs would have an average life of no more than 260 days?

This is the pvalue of Z when X = 260. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{260 - 270}{21.2}

Z = -0.47

Z = -0.47 has a pvalue of 0.3192.

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

5 0
3 years ago
Convert decimal to percent 091:​
azamat

Answer:

The correct answer is 0.91

7 0
2 years ago
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Which of the following cannot be used to express the number 8? eight more than zero +8 eight below zero positive eight
MrRa [10]

Eight below zero would express the value -8, negative eight,

but not 8.

7 0
3 years ago
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