The waiting time in line at an ice cream shop has a uniform distribution between 3 and 14 minutes. What is the 75th percentile of this distribution? (Recall: The 75th percentile divides the distribution into 2 parts so that 75% of area is to the left of 75th percentile) _______ minutes Answer: (Round answer to two decimal places.)

Answer:

Option B

Step-by-step explanation:

When A and B are independent events:

P(A and B) = P(A) * P(B)

OR

P(A|B) = P(A) * P(B)

Answer:

g(-5) = 2

g(0) = -2

g(1) = 2

Step-by-step explanation:

g(-5) satisfies x <-2, since -5 is less than -2.

g(0) satisfies -2≤x≤1 since 0 is greater than 2 but less than 1. When we plug in 0 into (x+1)^2 -2, we get -2.

g(1) satisfies -2≤x≤1 since it says that x is less than OR EQUAL TO 1. We then plug in 1 into (x+1)^2 -2 and get 2.

Answer:

As the P-value (0.0107) is bigger than the significance level (0.01), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that listening to music while solving math problems will make a particular brain area more active.

Step-by-step explanation:

This is a hypothesis test for the population mean.

The claim is that listening to music while solving math problems will make a particular brain area more active.

Then, the null and alternative hypothesis are:

[tex]H_0: \mu=35\\\\H_a:\mu> 35[/tex]

The significance level is 0.01.

The sample has a size n=1.

The sample mean is M=58.

The standard deviation of the population is known and has a value of σ=10.

We can calculate the standard error as:

[tex]\sigma_M=\dfrac{\sigma}{\sqrt{n}}=\dfrac{10}{\sqrt{1}}=10[/tex]

Then, we can calculate the z-statistic as:

[tex]z=\dfrac{M-\mu}{\sigma_M}=\dfrac{58-35}{10}=\dfrac{23}{10}=2.3[/tex]

This test is a right-tailed test, so the P-value for this test is calculated as:

[tex]\text{P-value}=P(z>2.3)=0.0107[/tex]

As the P-value (0.0107) is bigger than the significance level (0.01), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that listening to music while solving math problems will make a particular brain area more active.

Answer:

a) From the empirical rule we know that within 3 deviations from the mean we have 99.7% of the data

b) [tex] P(191.5<X<319.5)[/tex]

We can find the number of deviations from the mean for the limits using the z score formula given by:

[tex]z=\frac{x-\mu}{\sigma}[/tex]

And replacing we got:

[tex] z=\frac{191.5-255.4}{63.9}= -1[/tex]

[tex] z=\frac{319.3-255.4}{63.9}= 1[/tex]

So we have values within 1 deviation from the mean and using the empirical rule we know that we have 68% of the values for this case

Step-by-step explanation:

For this case we have the following properties for the random variable of interest "blood platelet counts"

[tex]\mu = 255.4[/tex] represent the mean

[tex]\sigma = 63.9[/tex] represent the population deviation

Part a

From the empirical rule we know that within 3 deviations from the mean we have 99.7% of the data

Part b

We want this probability:

[tex] P(191.5<X<319.5)[/tex]

We can find the number of deviations from the mean for the limits using the z score formula given by:

[tex]z=\frac{x-\mu}{\sigma}[/tex]

And replacing we got:

[tex] z=\frac{191.5-255.4}{63.9}= -1[/tex]

[tex] z=\frac{319.3-255.4}{63.9}= 1[/tex]

So we have values within 1 deviation from the mean and using the empirical rule we know that we have 68% of the values for this case

Answer:

Please the read the answer below

Step-by-step explanation:

In order to find the 95% confidence interval for the difference of the two populations, you use the following formula (which is available when the population size is greater than 30):

CI = [tex](p_1-p_2)\pm Z_{\alpha/2}(\sqrt{\frac{p_1(1-p_1)}{n_1}+\frac{p_2(1-p_2)}{n_2}})[/tex]     (1)

where:

p1: proportion of one population = 52/9853 = 0.0052

p2: proportion of the other population = 41/11541 = 0.0035

α: tail area = 1 - 0.95 = 0.05

Z_α/2: Z factor of normal distribution = Z_0.025 = 1.96

n1: sample of the first population = 52

n2: sample of the second population = 41

You replace the values of all parameters in the equation (1) :

[tex]CI =(0.0052-0.0035)\pm (1.96)(\sqrt{\frac{0.0052(1-0.0052)}{52}+\frac{0.0035(1-0.0035)}{41}})\\\\CI=0.0017\pm0.026[/tex]

By the result obtained in the solution, you can conclude that the sample is not enough, because the margin error is greater that the difference of proportion of each sample population.

Answer:

9 people

Step-by-step explanation:

37, 39, 41, 46, 61, 63, 69, 77, 80

9 people waited more than 36 minutes.

Answer:

Step-by-step explanation:

The question is incomplete. Here is the complete question.

Translate this sentence into an equation. The product of Holly's height and 3 is 39. Use the variable h to represent Holly's height.

Let holly's savings be h. If the  product of Holly's savings and 3 is 39, this can be represented mathematically as h*3 = 39

To get holly's savings "h', we will divide both sides of the equation by 3

h*3 = 39

h*3/ 3= 39/3

h = 13*3/ 3

h = 13 * 3/3

h = 13*1

h = 13

Holly's savings is 13 and the required equation is 3h =39

Answer:

The probability that all three have type B​+ blood is 0.001728

Step-by-step explanation:

For each person, there are only two possible outcomes. Either they have type B+ blood, or they do not. The probability of a person having type B+ blood is independent of any other person. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

In which [tex]C_{n,x}[/tex] is the number of different combinations of x objects from a set of n elements, given by the following formula.

[tex]C_{n,x} = \frac{n!}{x!(n-x)!}[/tex]

And p is the probability of X happening.

The probability that a person in the United States has type B​+ blood is 12​%.

This means that [tex]p = 0.12[/tex]

Three unrelated people in the United States are selected at random.

This means that [tex]n = 3[/tex]

Find the probability that all three have type B​+ blood.

This is P(X = 3).

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

[tex]P(X = 3) = C_{3,3}.(0.12)^{3}.(0.88)^{0} = 0.001728[/tex]

The probability that all three have type B​+ blood is 0.001728

Answer:

The calculated value t = 4.976 > 2.6264 at 0.01 level of significance

Null hypothesis is rejected

Alternative hypothesis is accepted

The  mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012

Step-by-step explanation:

Given Mean of the population μ = $53,900

Given sample size 'n' = 100

Mean of the sample size x⁻ = 55,144

Sample standard deviation 'S' = 5200

Null hypothesis:H₀: There is no difference between the means

Alternative Hypothesis :H₁: The  mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012

Test statistic

[tex]t = \frac{x^{-} -mean}{\frac{S}{\sqrt{n} } }[/tex]

[tex]t = \frac{55144-53900}{\frac{5200}{\sqrt{100} } }[/tex]

t = 4.976

Degrees of freedom

ν = n-1 = 100-1 =99

t₀.₀₁ = 2.6264

The calculated value t = 4.976 > 2.6264 at 0.01 level of significance

Null hypothesis is rejected

Alternative hypothesis is accepted

Final answer:-

The  mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012

Answer:

We conclude that the mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012.

Step-by-step explanation:

We are given that the Wall Street Journal reported that bachelor’s degree recipients with majors in business average starting salaries of $53,900 in 2012.

A sample of 100 business majors receiving a bachelor’s degree in 2013 showed a mean starting salary of $55,144 with a sample standard deviation of $5,200.

Let [tex]\mu[/tex] = mean starting salary for business majors in 2013.

So, Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] [tex]\leq[/tex] $53,900     {means that the mean starting salary for business majors in 2013 is smaller than or equal to the mean starting salary in 2012}

Alternate Hypothesis, [tex]H_A[/tex] : [tex]\mu[/tex] > $53,900     {means that the mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012}

The test statistics that would be used here One-sample t-test statistics because we don't know about population standard deviation;

                               T.S. =  [tex]\frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }[/tex]  ~ [tex]t_n_-_1[/tex]

where, [tex]\bar X[/tex] = sample mean starting salary = $55,144

            s = sample standard deviation = $5,200

            n = sample of business majors = 100

So, the test statistics  =  [tex]\frac{55,144-53,900}{\frac{5,200}{\sqrt{100} } }[/tex]  ~ [tex]t_9_9[/tex]

                                     =  2.392

The value of t-test statistic is 2.392.

Now, at 0.01 significance level the t table gives a critical value of 2.369 at 99 degree of freedom for right-tailed test.

Since our test statistic is more than the critical value of t as 2.392 > 2.369, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which we reject our null hypothesis.

Therefore, we conclude that the mean starting salary for business majors in 2013 is greater than the mean starting salary in 2012.

Answer:

a. P(x=0)=0.2967

b. P(x=1)=0.4444

c. P(x=2)=0.2219

d. P(x=3)=0.0369

Step-by-step explanation:

The variable X: "number of meals that exceed $50" can be modeled as a binomial random variable, with n=3 (the total number of meals) and p=0.333 (the probability that the chosen restaurant charges mor thena $50).

The probabilty p can be calculated dividing the amount of restaurants that are expected to charge more than $50 (5 restaurants)  by the total amount of restaurants from where we can pick (15 restaurants):

[tex]p=\dfrac{5}{15}=0.333[/tex]

Then, we can model the probability that k meals cost more than $50 as:

[tex]P(x=k) = \dbinom{n}{k} p^{k}(1-p)^{n-k}\\\\\\P(x=k) = \dbinom{3}{k} 0.333^{k} 0.667^{3-k}\\\\\\[/tex]

a. We have to calculate P(x=0)

[tex]P(x=0) = \dbinom{3}{0} p^{0}(1-p)^{3}=1*1*0.2967=0.2967\\\\\\[/tex]

b. We have to calculate P(x=1)

[tex]P(x=1) = \dbinom{3}{1} p^{1}(1-p)^{2}=3*0.333*0.4449=0.4444\\\\\\[/tex]

c. We have to calcualte P(x=2)

[tex]P(x=2) = \dbinom{3}{2} p^{2}(1-p)^{1}=3*0.1109*0.667=0.2219\\\\\\[/tex]

d. We have to calculate P(x=3)

[tex]P(x=3) = \dbinom{3}{3} p^{3}(1-p)^{0}=1*0.0369*1=0.0369\\\\\\[/tex]

Answer:

2/7

Step-by-step explanation:

Seven employees can be arranged in 7! ways. n(S) = 7!

Two adjacent desks for married couple can be selected in 6 ways viz.,(1, 2), (2, 3), (3,4), (4, 5), (5,6),(6,7).

This couple can be arranged in the two desks in 2! ways. Other five persons can be arranged in 5! ways.

So, number of ways in which married couple occupy adjacent desks

= 6×2! x 5! =2×6!

so, the probability that the married couple will have adjacent desks

[tex]\frac{n(A)}{n(s)} =\frac{2\times6!}{7!} \\=\frac{2}{7}[/tex]

Answer:

The null and alternative hypothesis are:

[tex]H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2> 0[/tex]

where μ1 is the population mean sales with compensation plan, and μ2 is the populatiojn mean sales without compensation plan.

A Type I error is made when a true null hypothesis is rejected. In this case, it would be concluded that the compensation plan increases sales, when in fact it does not (at least, not significantly).

The consequences of this error would be that the compensation plan would have evidence to be implemented in the company when in fact it will not bring the results it is expected to have.

Step-by-step explanation:

This hypothesis test will test the claim that the compensation plan increases the average sales per salesperson. This claim will be stated in the alternative hypothesis, and will state that, with the compensation plan, the sales are significantly higher than without the compensation plan.

The null hypothesis, that Steve wants to falsify, will state that the sales will not differ with or withour compensation plan.

We can write this hypothesis as:

[tex]H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2> 0[/tex]

where μ1 is the population mean sales with compensation plan, and μ2 is the populatiojn mean sales without compensation plan.

A Type I error is made when a true null hypothesis is rejected. In this case, it would be concluded that the compensation plan increases sales, when in fact it does not (at least, not significantly).

The consequences of this error would be that the compensation plan would have evidence to be implemented in the company when in fact it will not bring the results it is expected to have. The sales would be expected to increase due to this implementation, and they will not increase, at least, not for the compensation plan.

Answer:

At first it increases by 25%, then you have 1.25x the original temp. A drop of 40% gives you .6 x 1.25, or 75% of the original temperature

Step-by-step explanation:

found that on the web for yuh. I really hope it helped.

Answer:

decreased by 25%

Step-by-step explanation:

Answer:

  15

Step-by-step explanation:

The general form of an exponential equation is ...

  f(x) = (initial value)(growth factor)^x

That is, the "growth factor" is the base of the exponent. In your equation ...

  f(x) = (1/5)(15^x)

the growth factor is 15.

Answer:

D

Step-by-step explanation:

because you put the one and the five and BOOM the inter carol makes the wheel go round and round.

Answer:

Step-by-step explanation:

Plotting a point A and tracing a point B at 4 units from A results in a circle.

▪The locus of a point at equal distance from a fixed point is a circle.

▪Point A is (5,5) and length of AB is 4 units

This implies that the radius of circle is 4 units.

▪The point B can be swirled around A keeping the distance AB constant.

▪The resulting figure is a circle.

▪This circle is plotted and attached below.

I hope this helped. I am sorry if you get it wrong

Answer:

This is the right answer for Edementum and Plato users

Like and Rate!

Answer:

CICI

Step-by-step explanation: NO cici

Christian, Iris and Morgan each get an equal share of 1/2 of the pizza and the model 1/6 represent the fraction of the ​pizza each person gets.

The division in mathematics is one kind of operation. In this process, we split the expressions or numbers into the same number of parts.

Given:

Christian, Iris and Morgan each get an equal share of 1/2 of the pizza.

To find the fraction of the ​pizza each person gets:

Divide the amount of pizza by the number of people.

There are 3 people and 1/2 pizza.

The fraction of the pizza each person gets

= The amount of pizza / number of people

The fraction of the pizza each person gets

= (1/2) / 3

Simplifying into multiplication,

The fraction of the pizza each person gets = 1/2 x 1/3

The fraction of the pizza each person gets

= 1/(2x3)

= 1/6

Therefore, the model that represents the requirement is 1/6.

To learn more about the division;

https://brainly.com/question/13263114

#SPJ5

EASY!

Answer: 17/16 or 1 1/16

Step-by-step explanation:

BRO IT'S ELEMANTARY FRACTIONS!!!!

Answer:

C. 44

Step-by-step explanation:

[tex] \frac{1}{2} m - \frac{3}{4} n = 16 \\ \\ \frac{1}{2} m - \frac{3}{4} \times 8 = 16..( plug \: n = 8) \\ \\ \frac{1}{2} m - 3 \times 2 = 16 \\ \\ \frac{1}{2} m - 6 = 16 \\ \\ \frac{1}{2} m = 16 + 6 \\ \\ \frac{1}{2} m = 22 \\ \\ m = 22 \times 2 \\ \\ m = 44[/tex]

The value of m in the given equation is equal to 3.

Given the following data:

To find the value of m in the given equation:

In this exercise, you're required to determine the value of m in the given equation. Thus, we would translate the word problem into an algebraic equation.

[tex]\frac{1}{2m} -\frac{3}{4n} =16[/tex]

Substituting the value of n in the equation, we have;

[tex]\frac{1}{2m} -\frac{3}{4(8)} =16\\\\\frac{1}{2m} -\frac{3}{32} =16\\\\16m-32=16\\\\16m=16+32\\\\16m=48\\\\m=\frac{48}{16}[/tex]

m = 3.

Read more on word problems here: brainly.com/question/13170908

Answer:

Step-by-step explanation:

Area of rectangular menu

Length × breadth

3×2=6sq feet

Answer:

6 ft^2

Step-by-step explanation:

area of rectangle = length * width

area = 3 ft * 2 ft

area = 6 ft^2

Answer: 90 minutes

Step-by-step explanation:

Area of the side = 15 x 18 = 270 sq. ft.

3 sq. ft take a minute to paint

270 sq. ft. will take 270 / 3

= 90 minutes

Answer:

There are 10 teams.

Step-by-step explanation:

Given that the question wants at least 48 swimmers so any numbers above 47 are counted.

In this diagram, there are 10 teams consisting 48 swimmers and above, 48, 52, 53, 63, 76, 79, 82, 84, 85 and 86.

Answer:

10 teams have 48 or more swimmers.

Step-by-step explanation:

If we look at stem 4 there is one team with 48 members.

So counting from there we  have:

1 + 2 + 1 + 2 + 4

= 10 teams.

Answer:

Look below

Step-by-step explanation:

Answer:

D. e - 35

Step-by-step explanation:

We have that:

George earned e extra points.

Kate earned k extra points.

Kate earned 35 fewer extra credit points than George.

This means that k is e subtracted by 35, that is:

k = e - 35

So the correct answer is:

D. e - 35

Answer: D

Step-by-step explanation:

Since we are not given the height of the trapezoid, we can split this into a triangle and a rectangle. We find the area of each and then add them together. In order to do so, we must use Pythagorean Theorem to find the missing length so that we can find the area.

a²+b²=c²

a²+4²=8²

a²+16=64

a²=48

a=√48

a=4√3

Now that we know the missing length of the triangle, we can find the area of the triangle and the rectangle.

Triangle

A=1/2bh

A=1/2(4)(4√3)

A=8√3

-----------------------------------------------------------------------------------------

Rectangle

A=lw

A=7(4√3)

A=28√3

With our areas, we can add them together.

4√3+28√3=36√3 cm²

Answer:  b) they ARE similar because BRAD:KELY is 1:2

Step-by-step explanation:

In order for the shapes to be similar they must have congruent angles and proportional sides.

With the options a through d given, we can assume that their sides are proportional.  Since BRAD is smaller than KELY, BRAD would have the smaller number in the ratio.

Answer:

They are similar because Brad and Kelly are 1:2

Step-by-step explanation:

Answer:

4,500 x 5 = 22,500

4,500 divided by 5 = 900

4,500 plus 5 = 4,505

4,500 minus 5 = 4,495

Step-by-step explanation:

it is either one of those that u have to choose from good luck

Answer:

[tex]\dfrac{15}{19}[/tex]

Step-by-step explanation:

The soccer player so far has made 15 penalty kicks in 19 attempts.

Therefore:

Total Number of trials =19

Number of Successes =15

Therefore, the relative frequency probability that she will make her next penalty​ kick is:

[tex]=\dfrac{\text{Number of Successes}}{\text{Total Number of Trials}} \\=\dfrac{15}{19}[/tex]

Answer:

8p + 2s <= 150

Step-by-step explanation:

Let p = number of a pizza.

Let s = price of a bottle of soda.

The inequality is

8p + 2s <= 150

Answer:

is m= 10.5 espero que te ayude

Given Information:

Population proportion = p =  0.55

Sample size 1 = n₁ = 30

Sample size 2 = n₂ = 100

Sample size 3 = n₃ = 1000

Required Information:

Standard error = σ = ?

Answer:

[tex]$ \sigma_1 = 0.091 $[/tex]

[tex]$ \sigma_2 = 0.050 $[/tex]

[tex]$ \sigma_3 = 0.016 $[/tex]

Step-by-step explanation:

The standard error for sample proportions from a population is given by

[tex]$ \sigma = \sqrt{\frac{p(1-p)}{n} } $[/tex]  

Where p is the population proportion and n is the sample size.

For sample size n₁ = 30

[tex]$ \sigma_1 = \sqrt{\frac{p(1-p)}{n_1} } $[/tex]

[tex]$ \sigma_1 = \sqrt{\frac{0.55(1-0.55)}{30} } $[/tex]

[tex]$ \sigma_1 = 0.091 $[/tex]

For sample size n₂ = 100

[tex]$ \sigma_2 = \sqrt{\frac{p(1-p)}{n_2} } $[/tex]

[tex]$ \sigma_2 = \sqrt{\frac{0.55(1-0.55)}{100} } $[/tex]

[tex]$ \sigma_2 = 0.050 $[/tex]

For sample size n₃ = 1000

[tex]$ \sigma_3 = \sqrt{\frac{p(1-p)}{n_3} } $[/tex]

[tex]$ \sigma_3 = \sqrt{\frac{0.55(1-0.55)}{1000} } $[/tex]

[tex]$ \sigma_3 = 0.016 $[/tex]

As you can notice, the standard error decreases as the sample size increases.

Therefore, the greater the sample size lesser will be the standard error.