Kai had a gross weekly paycheck of $616 last week. Kai worked 6 hours for 4 of the days and 8 hours on 1 day. What is Kai's hourly rate of pay? a. $16.21 b. $19.25 c. $20.53 d. $25.67 Please select the best answer from the choices provided

Answers

Answer 1

Answer:

The correct answer is B. $ 19.25

Explanation:

To calculate the hourly rate of pay, first, let's calculate the total number of hours Kai worked, and then divide the total earned into the number of hours.

6 hours x 4 days = 24 hours

8 hours x 1 day = 8 hours

24 hours + 8 hours = 32 hours

This shows Kai worked a total of 32 hours. Now to find the hourly rate of pay, follow this procedure:

$616 (total earned) ÷ 32 hours = $19.25 each hour

This means Kai earns $19.25 for each hour of work and therefore the hourly rate of pay is $19.25.

Answer 2

Answer:

Kai earns $19.25 for each hour of work that is the hourly rate of pay is $19.25. Hence option b is true.

Given that;

Kai had a gross weekly paycheck of $616 last week.

And, Kai worked 6 hours for 4 of the days and 8 hours on 1 day.

Now the total working hour would be,

The working hours in 4 days,

4 × 6 = 24 hours

The working hours in 1 day,

1 × 8 = 8 hours.

Hence, the total working hours in a week is,

24 + 8 = 32 hours

Since Kai had a gross weekly paycheck of $616 last week.

Hence, Kai's hourly rate of pay is,

$616 ÷ 32 = $19.25

Therefore, option b is true.

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Every morning Jack flips a fair coin ten times. He does this for anentire year. LetXbe the number of days when all the flips come out the same way(all heads or all tails).(a) Give the exact expression for the probabilityP(X >1).(b) Is it appropriate to approximateXby a Poisson distribution

Answers

Answer:

See the attached picture for detailed answer.

Step-by-step explanation:

See the attached picture for detailed answer.

Final answer:

The probability question from part (a) requires calculating the chance of getting all heads or all tails on multiple days in a year, which involves complex probability distributions. For part (b), using a Poisson distribution could be appropriate due to the rarity of the event and the high number of trials involved.

Explanation:

The question pertains to the field of probability theory and involves calculating the probability of specific outcomes when flipping a fair coin. For part (a), Jack flips a coin ten times each morning for a year, counting the days (X) when all flips are identical (all heads or all tails). The exact expression for P(X > 1), the probability of more than one such day, requires several steps. First, we find the probability of a single day having all heads or all tails, then use that to calculate the probability for multiple days within the year. For part (b), whether it is appropriate to approximate X by a Poisson distribution depends on the rarity of the event in question and the number of trials. A Poisson distribution is typically used for rare events over many trials, which may apply here.

For part (a), the probability on any given day is the sum of the probabilities of all heads or all tails: 2*(0.5^10). Over a year (365 days), we need to calculate the probability distribution for this outcome occurring on multiple days. To find P(X > 1), we would need to use the binomial distribution and subtract the probability of the event not occurring at all (P(X=0)) and occurring exactly once (P(X=1)) from 1. However, this calculation can become quite complex due to the large number of trials.

For part (b), given the low probability of the event (all heads or all tails) and the high number of trials (365), a Poisson distribution may be an appropriate approximation. The mean (λ) for the Poisson distribution would be the expected number of times the event occurs in a year. Since the probability of all heads or all tails is low, it can be considered a rare event, and the Poisson distribution is often used for modeling such scenarios.

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"The municipal transportation authority determined that 58% of all drivers were speeding along a busy street. In an attempt to reduce this percentage, the city put up electronic speed monitors so that drivers would be warned if they were driving over the speed limit. A follow-up study is now planned to see if the speed monitors were effective. The null and alternative hypotheses of the test are H0 : π = 0.58 versus Ha : π < 0.58. It is planned to use a sample of 150 drivers taken at random times of the week and the test will be conducted at the 5% significance level. (a) What is the most number of drivers in the sample that can be speeding and still have them conclude that the alternative hypothesis is true? (b) Suppose the true value of π is 0.52. What is the power of the test? (c) How could the researchers modify the test in order to increase its power without increasing the probability of a Type I Error?"

Answers

Answer:

a) X=77 drivers

b) Power of the test = 0.404

c) Increasing the sample size.

Step-by-step explanation:

This is a hypothesis test of proportions. As the claim is that the speed monitors were effective in reducing the speeding, this is a left-tail test.

For a left-tail test at a 5% significance level, we have a critical value of z that is zc=-1.645. This value is the limit of the rejection region. That means that if the test statistic z is smaller than zc=-1.645, the null hypothesis is rejected.

The proportion that would have a test statistic equal to this critical value can be expressed as:

$p_c=\pi+z_c\cdot\sigma_p$

The standard error of the proportion is:

$\sigma_p=\sqrt{(\pi(1-\pi))/(n)}=\sqrt{(0.58*0.42)/(150)}\n\n\n \sigma_p=√(0.001624)=0.04$

Then, the proportion is:

$p_c=\pi+z_c\cdot\sigma_p=0.58-1.645*0.04=0.58-0.0658=0.5142$

This proportion, with a sample size of n=150, correspond to

$x=n\cdot p=150\cdot0.5142=77.13\approx 77$

The power of the test is the probability of correctly rejecting the null hypothesis.

The true proportion is 0.52, but we don't know at the time of the test, so the critical value to make a decision about rejecting the null hypothesis is still zc=-1.645 corresponding to a critical proportion of 0.51.

Then, we can say that the probability of rejecting the null hypothesis is still the probability of getting a sample of size n=150 with a proportion of 0.51 or smaller, but within a population with a proportion of 0.52.

The standard error has to be re-calculated for the new true proportion:

$\sigma_p=\sqrt{(\pi(1-\pi))/(n)}=\sqrt{(0.52*0.48)/(150)}\n\n\n \sigma_p=√(0.001664)=0.041$

Then, we calculate the z-value for this proportion with the true proportion:

$z=(p-\pi')/(\sigma_p)=(0.51-0.52)/(0.041)=(-0.01)/(0.041)=-0.244$

The probability of getting a sample of size n=150 with a proportion of 0.51 or lower is:

$P(p<0.51)=P(z<-0.244)=0.404$

Then, the power of the test is β=0.404.

The only variable left to change in the test in order to increase the power of the test is the sample size, as the significance level can not be changed (it is related to the probability of a Type I error).

It the sample size is increased, the standard error of the proprotion decreases. As the standard error tends to zero, the critical proportion tend to 0.58, as we can see in its equation:

$\lim_(\sigma_p \to 0) p_c=\pi+ \lim_(\sigma_p \to 0)(z_c\cdot\sigma_p)=\pi=0.58$

Then, if the critical proportion increases, the z-score increases, and also the probability of rejecting the null hypothesis.

Consider this composite figure that is made of two half spheres a cylinder. A composite figure is comprised of one cylinder and two half spheres. The cylinder has a height of 9 millimeters and radius of 5 millimeters. The volumes of each figure that make the composite figure have been determined. Sphere V = 500 3 π mm3 Cylinder V = 225π mm3 What is the volume of the composite figure?

Answers

Answer:

the answer is c

1,175/3mm3

Step-by-step explanation:

I got it right

Answer:

Actually:

V = 500/3

How to do this? what is the answer??

Answers

Answer:

I think that is the C

Step-by-step explanation:

Answer:

Option B is the correct answer.

Step-by-step explanation:

here, arc RT =162°

as in question given that the value of arc RT is 162° the value of angle RST is 1/2 of 162°.

so, its value must be 81°only.

hopeit helps..

Which headline is MOST likely to be included on a national news show?“Local school raises $5,000 for cancer research”

“Iran declares war on the United States”

“School in China raises $5,000 for cancer research”

“Company closes in Alaska, lays off 2 people”

WHO EVER ANSWERS FIRST I WILL GIVE BRAINLIEST PLSE HELP ME

Answers

Answer:

I personally think B but I do not know for sure.

Step-by-step explanation:

Write a verbal expression for each algebraic expression.2
1.) 9a

2.) c + 2d

3
3.) 7x - 1

Answers

1. nine(a)
2. c + two(d)
3. seven(x) - 1

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