What is the value of |-6|-|6| -(-6)

Se necesitan 10 micros si queremos que cada 3 micros transporten 90 pasajeros.

En principio, sabemos que 300 pasajeros pueden transportarse en 4 microbuses.

Entonces, el numero de pasajeros que va por cada micro será el cociente entre el numero de pasajeros y el numero de micros:

N = 300/4 = 75

Queremos responder:

¿Cuántos micros se deben aumentar para  que por cada 3 micros se transporten 90 pasajeros?

Definamos X como el numero de grupos de 3 micros que tendriamos en esta situación.

Entonces 300 sobre X, debe ser igual a 90 (el numero de pasajeros que va en cada grupo de 3 micros)

300/X = 90

300 = 90*X

300/90 = X = 3.33...

Notar que el número total de micros sera 3 veces X:

3*X = 3*3.33.... = 10

Se necesitan 10 micros.

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Answer:

i hope it will help you

Step-by-step explanation:

Working capital management is how companies are able to manage finances and continue operations.

Answer:

2016

Step-by-step explanation:

using USA dollars:

$42000 x .072 (7.2%) = 3024 total commission

3024 x 2/3 = 2016 brokers amount

Start with a volume of a cuboid,

[tex]V=abc=3\cdot2\cdot3=18\mathrm{cm^3}[/tex]

The side of the cube we need equals to the LCM of the cubiod's sides,

[tex]\mathrm{LCM}(a,b,c)=\mathrm{LCM}(3,2,3)=6[/tex]

Now compute the volume of such cube,

[tex]V=\mathrm{LCM}(a,b,c)^3=6^3=216\mathrm{cm^3}[/tex]

Divide the volumes to get how many cubiods are in such cube,

[tex]\dfrac{V_{\mathrm{cube}}}{V_{\mathrm{cubiod}}}=\dfrac{216}{18}=\boxed{12}[/tex]

Hope this helps :)

Answer:

Hi,

Answer: 12

Step-by-step explanation:

lcm(3,2,3)=6

Volume of a cuboid=3*2*3=18 (cm³)

Volume of the cube=6³=216 (cm³)

Number of cuboids=216/18=12.

From the test the person wants, and the sample data, we build the test hypothesis, find the test statistic,  and use this to reach a conclusion.

This is a two-sample test, thus, it is needed to understand the central limit theorem and subtraction of normal variables.

Doing this:

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

Central Limit Theorem

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

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 [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Subtraction between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

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

Proportion 1: Jet-ski users

86.5% out of 400, thus:

[tex]p_1 = 0.865[/tex]

[tex]s_1 = \sqrt{\frac{0.865*0.135}{400}} = 0.0171[/tex]

Proportion 2: boaters

92.8% out of 250, so:

[tex]p_2 = 0.928[/tex]

[tex]s_2 = \sqrt{\frac{0.928*0.072}{250}} = 0.0163[/tex]

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

Hypothesis:

Test the claim that the proportion of people who wear life vests while riding a jet ski is not the same as the proportion of people who wear life vests while riding in a boat.

At the null hypothesis, it is tested that the proportions are the same, that is, the subtraction is 0. So

[tex]H_0: p_1 - p_2 = 0 \rightarrow p_1 = p_2[/tex]

At the alternative hypothesis, it is tested that the proportions are different, that is, the subtraction is different of 0. So

[tex]H_1: p_1 - p_2 \neq 0 \rightarrow p_1 \neq p_2[/tex]

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

Test statistic:

The test statistic is:

[tex]z = \frac{X - \mu}{s}[/tex]

In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis, and s is the standard error.

0 is tested at the null hypothesis.

This means that [tex]\mu = 0[/tex]

From the samples:

[tex]X = p_1 - p_2 = 0.865 - 0.928 = -0.063[/tex]

[tex]s = \sqrt{s_1^2 + s_2^2} = \sqrt{0.0171^2 + 0.0163^2} = 0.0236[/tex]

The value of the test statistic is:

[tex]z = \frac{X - \mu}{s}[/tex]

[tex]z = \frac{-0.063 - 0}{0.0236}[/tex]

[tex]z = -2.67[/tex]

The value of the test statistic is z = -2.67.

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

p-value of the test and decision:

The p-value of the test is the probability that the proportion differs by at at least 0.063, which is P(|z| > 2.67), given by 2 multiplied by the p-value of z = -2.67.

Looking at the z-table, z = -2.67 has a p-value of 0.0038.

2*0.0038 = 0.0076.

The p-value of the test is 0.0076 < 0.05(standard significance level), which means that there is enough evidence to conclude that the proportion of people who wear life vests while riding a jet ski is not the same as the proportion of people who wear life vests while riding in a boat.

A similar question is found at https://brainly.com/question/24250158

9514 1404 393

Answer:

  (9√3 -3π/2) ft^3 ≈ 10.88 ft^3

Step-by-step explanation:

The area of the hexagon is given by the formula ...

  A = (3/2)√3·s^2 . . . . for side length s

The area of the hexagonal face of this solid is ...

  A = (3/2)√3·(2 ft)^2 = 6√3 ft^2

__

The area of the circular hole in the hexagonal face is ...

  A = πr^2

The radius is half the diameter, so is r = (2 ft)/2 = 1 ft.

  A = π(1 ft)^2 = π ft^2

Then the area of the "solid" part of the face of the figure is ...

  A = (6√3 -π) ft^2

__

The volume is ...

  V = Bh . . . . . where B is the area of the base of the prism, and h is its height

  V = ((6√3 -π) ft^2)(3/2 ft) = (9√3 -3π/2) ft^3 ≈ 10.88 ft^3

Step-by-step explanation:

her it Go i think it is helpful for u

Answer:

b is your answer hope it is helpful

Answer:

b is the correct answer

Step-by-step explanation:

the answer is b

Answer:

4^15

Step-by-step explanation:

We know a^b^c = a^(b*c)

4^3^5

4^(3*5)

4^15

Answer:

I don't know because I don't understand what you mean

9514 1404 393

Answer:

Step-by-step explanation:

Part A: All of the coefficients have a common factor of 3. All of the variable products have a common factor of y, so the greatest common factor of all terms is 3y. The expression can be written as ...

  (3y)(2x^2 -1x -8xy +4y)

__

Part B: The remaining factor can be factored pairwise:

  3y(x(2x -1) -4y(2x -1)) = 3y(x -4y)(2x -1)

Step-by-step explanation:

the box is

9 in × 3.5 in × 4.5 in = 141.75 in³

each block is

0.5 in × 0.5 in × 0.5 in = 0.125 in³ (1/8 in³)

so, we can fit

141.75 / 0.125 = 1134

blocks into the box.

and they fit neatly, as the dimensions of the box and the cubes allow a tight packing without any empty left over space in the box.

Answer:

pordondede donde eres?

Step-by-step explanation:

........................

9514 1404 393

Answer:

  e = 225

Step-by-step explanation:

To eliminate the coefficient of e, multiply both sides of the equation by its reciprocal. The reciprocal of -1/75 is -75.

  (-75)(-3) = (-75)(-e/75)

  225 = e

Answer:

C. 395.1

Step-by-step explanation:

Substitute the value for x:

[tex]V=0.95(8)^{2.9}\\V=395.1[/tex]

Answer:

x < -4

Step-by-step explanation:

-3x > 12

-----   ----

-3      -3

12 ÷ -3 = -4

Which means:

x < -4

(The sign changes because the equation is divided by a negative number)

Hope this helped.

Answer:

x <-4

Step-by-step explanation:

-3x > 12

Divide each side by -3. remembering to flip the inequality

-3x/-3 > 12/-3

x <-4

Answer:

-6

Step-by-step explanation:

(-12)+(-8)= -20

-20+14= -6

Answer:

The shopping time (in minutes) of the nine shoppers are:

15, 16, 18, 20, 22, 25, 27, 28, 29 (just to make it easier to read, I rearranged  everything from least to greatest.)

We can see, that 3 shoppers shopped for 15-20 minutes.

And, 3 shoppers shopped for 21-26 minutes.

And finally, 3 shoppers shopped for 27-32 minutes.

So the answer for all 3 of the boxes is 3.

Let me know if this helps.

Answer:

12 free throw attempts

Step-by-step explanation:

First, find what percent of free throw attempts he misses:

6/10

= 0.6

So, he misses 60% of the time. Multiply 20 by 0.6 to find how many you would expect Lamar to miss out of 20 attempts:

20(0.6)

= 12

So, you would expect Lamar to miss 12 free throw attempts

Answer:

a) To show that we can use the 1 proportion z-interval, we know that 250 ( size sample) is big enough to approximate the binomial distribution ( tolerance-intolerance) to a normal distribution.

b) See step by step explanation

CI 90 %  =  (  0,296 ; 0,392)

c) We can support that with 90 % of confidence we will find the random variable between this interval ( 0,296 ; 0,392)

d) the CI 95 % will be wider

Step-by-step explanation:

Sample Information:

Sample size n  =  250

number of people with milk intolerance  x = 86

p₁  =  86 / 250    p₁ = 0.344    and   q₁ =  1  - p₁   q₁ = 0,656

To calculate 90 % of Confidence Interval   α = 10%  α/2 = 5 %  

α/2 = 0,05     z(c) from z-table is:  z(c) =  1.6

Then:

CI 90 %  =  (  p₁  ±  z(c) * SE )

SE =  √ (p₁*q₁)/n   =  √ 0,225664/250

SE = 0,03

CI 90 %  =  (  0,344  ±  1,6* 0,03 )

CI 90 %  =  (  0,344 - 0,048 ;  0,344 + 0,048)

b) CI 90 %  =  (  0,296 ; 0,392)

a) To show that we can use the 1 proportion z-interval, we know that 250 ( size sample) is big enough to approximate the binomial distribution ( tolerance-intolerance) to a normal distribution.

c) We can support that with 90 % of confidence we will find the random variable between  this interval (  0,296 ; 0,392) .

d) CI 95 %      then significance level α = 5 %   α/2 = 2.5 %  

α/2  =  0,025      z(c) = 1.96   from z-table

SE = 0,03

And  as 1.96 > 1.6    the CI 95 % will be wider

CI 95% =  ( 0,344 ±  1.96*0,03 )

CI 95% =  (  0,344 ± 0,0588 )

CI 95% =  ( 0,2852 ; 0,4028 )

To test the effectiveness of the weight loss program, a PAIRED SAMPLE test distribution is used.

The weight loss data collated for the program for both the beginning and end of the program period was obtained with one subject or person having two separate readings, these shows that the samples are NOT INDEPENDENT.

When performing a test which involves DEPENDENT or MATCHED samples, whereby means of two measurements taken from the SAME subject are involved, a PAIRED SAMPLE TEST DISTRIBUTION IS ADOPTED.

Therefore, the effectiveness of the weight loss programme will be accurately evaluated using a PAIRED SAMPLE TEST.

Learn more : https://brainly.com/question/17143411

Answer: 3246/6= 541

if u wanna know if a # is divisible by 6 or not, see if the # is divisible by 2 or 3. if it works for both, then it is divisible by 6

no bc it is not no no no no no no no

Answer:

The alternative hypothesis being tested in this example is that the tire life is of more than 60,000 miles, that is:

[tex]H_1: \mu > 60,000[/tex]

Step-by-step explanation:

A tire manufacturer has a 60,000 mile warranty for tread life. The company wants to make sure the average tire lasts longer than 60,000 miles.

At the null hypothesis, we test if the tire life is of at most 60,000 miles, that is:

[tex]H_0: \mu \leq 60,000[/tex]

At the alternative hypothesis, we test if the tire life is of more than 60,000 miles, that is:

[tex]H_1: \mu > 60,000[/tex]

Let the missing number be x.

=> x + 44587 = 65000

=> x = 65000 - 44587

= 20413

Ans.= The missing number will be 20413.

Hope this answer helps you..

..

..

Select it as the BRAINLIEST..

Answer:

False

Step-by-step explanation:

A composite figure would be any irregular shapes and can be made up of multiple shapes

Answer:

correct u did it

Step-by-step explanation:

told me

To conduct a hypothesis test to determine if there is a significant difference between the number of games won by the American League and the National League in the World Series, we can follow these steps:

Step 1: State the null and alternative hypotheses:

Null hypothesis (H0): There is no significant difference between the mean number of games won by the American League and the National League.

Alternative hypothesis (Ha): There is a significant difference between the mean number of games won by the American League and the National League.

Step 2: Determine the significance level:

In this case, the significance level is given as 10%, which means α = 0.10.

Step 3: Conduct the hypothesis test:

To conduct the hypothesis test, we can use a two-sample t-test because we have two independent samples and we do not have information about the population parameters.

Step 4: Calculate the test statistic and p-value:

Using the provided sample means, standard deviations, and sample sizes, we can calculate the test statistic and p-value using statistical software or a calculator.

Step 5: Compare the p-value to the significance level:

If the p-value is less than the significance level (α), we reject the null hypothesis and conclude that there is a significant difference between the mean number of games won by the American League and the National League. If the p-value is greater than the significance level, we fail to reject the null hypothesis.

Since the calculation of the test statistic and p-value requires specific values from the samples, such as the sample sizes, it is not possible to perform the exact calculation without those values. Additionally, the information provided in the question does not specify whether the data follows a normal distribution or other assumptions required for the t-test.

To conduct the hypothesis test accurately, it is recommended to use statistical software or consult a statistician who can perform the calculations using the provided sample means, standard deviations, and sample sizes.

To know more about  hypotenuse , here

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