plz answer this asap

Answer:

[tex] \bar x = 40, s =10[/tex]

And from these values we can estimate the sample variance like this:

[tex] s^2 = 10^2 =100[/tex]

And we can also estimate the coeffcient of variation given by:

[tex] \hat{CV} =\frac{s}{\bar x}[/tex]

And replacing we got:

[tex] \hat{CV} = \frac{10}{40}= 0.25[/tex]

And this coefficient is useful in order to see the variability in terms of the mean for this case since is lower than 1 we can conclude that this variation around the mean is low.

Step-by-step explanation:

For this case we have the following info given:

[tex] \bar x = 40, s =10[/tex]

And from these values we can estimate the sample variance like this:

[tex] s^2 = 10^2 =100[/tex]

And we can also estimate the coeffcient of variation given by:

[tex] \hat{CV} =\frac{s}{\bar x}[/tex]

And replacing we got:

[tex] \hat{CV} = \frac{10}{40}= 0.25[/tex]

And this coefficient is useful in order to see the variability in terms of the mean for this case since is lower than 1 we can conclude that this variation around the mean is low.

Answer:

  the sum of the prices divided by 7

Step-by-step explanation:

The mean is the sum of the elements of a set, divided by the number of elements in the set. This set has 7 members, so its mean is ...

  the sum of the prices divided by 7

Answer: No.

Step-by-step explanation:

I guess that here we have the statement:

If the sum of two numbers is odd----> can their quotient be an odd number?

first, for n an integer number, we have that:

an odd number can be written as 2n + 1

an even number can be written as 2n.

The sum of two numbers is only odd if one of them is odd and the other even.

Then we have a number that is 2n and other that is 2k + 1, for n and k integer numbers.

Now, let's see if the quotient can also be an odd number.

One way to think this is:

There is an odd number such that when we multiply it by another odd number, the result is an even number?

no, and i can prove it as:

let 2k + 1 be an odd number, and 2j + 1 other.

the product is:

(2k + 1)*(2j + 1) = 2*(2*k*j + k + j) + 1

and as k and j are integers, also does 2*k*j + k + j, so:

2*(2*k*j + k + j) + 1 is an odd number.

This says that the product of two odd numbers is always odd, then we never can have that the quotient between an even number and an odd number is odd.

Answer:

14

Step-by-step explanation:

Answer:

Which of these factors will affect the friction on a road

Step-by-step explanation:

Answer:

Step-by-step explanation:

Let X denote the life span of a car battery and it follows and exponential distribution with average of 6 years.

Thus , the parameter of the exponential distribution is calculated as,

μ = 6

[tex]\frac{1}{\lambda} =6[/tex]

[tex]\lambda = \frac{1}{6}[/tex]

a) The required probability is

[tex]P(X>4)=1-P(X\leq 4)\\\\=1-F(4)\\\\1-(1-e^{- \lambda x})\\\\=e^{-\frac{4}{6}[/tex]

= 0.513

Hence, the probability that a randomly selected car battery will last more than four years is 0.513

b) The variance of the battery span is calculated as

[tex]\sigma ^2=\frac{1}{(\frac{1}{\lambda})^2 }\\\\\sigma ^2=\frac{1}{(\frac{1}{6})^2 } \\\\=6^2=36[/tex]

The 95% percentile [tex]x_{a=0.05}[/tex] (α = 5%) of the battery span is calculated

[tex]x_{0.05}=-\frac{log(\alpha) }{\lambda} \\\\=-\frac{log(0.05)}{1/6} \\\\=-6log(0.05)\\\\=17.97 \ years[/tex]

c)  

Let [tex]X_r[/tex] denote the remaining life time of a car battery

i)the probability the battery will last an additional five years is calculated below

[tex]P(X_r>5)=e^{-5\lambda}\\\\=e^{-\frac{5}{6} }\\\\=0.4346[/tex]

ii) The average time that the battery is expected to last is calculated

[tex]E(X_r)=\frac{1}{\lambda} \\\\=6[/tex]

Answer:

For this case we know that the confidence level is 89.48% or 0.8948 and the significance would be: [tex] \alpha=1-0.8948 = 0.1052[/tex] and the value of [tex]\alpha/2 =0.0526[/tex]

Now we need to find a quantile in the normal standard distribution who accumulate 0.0526 of the area on each tail of the normal standard distribution and we got:

[tex] z_{\alpha/2}= \pm 1.62015[/tex]

And we can use the following excel code for example:

"=NORM.INV(0.0526,0,1)"

Step-by-step explanation:

For this case we know that the confidence level is 89.48% or 0.8948 and the significance would be: [tex] \alpha=1-0.8948 = 0.1052[/tex] and the value of [tex]\alpha/2 =0.0526[/tex]

Now we need to find a quantile in the normal standard distribution who accumulate 0.0526 of the area on each tail of the normal standard distribution and we got:

[tex] z_{\alpha/2}= \pm 1.62015[/tex]

And we can use the following excel code for example:

"=NORM.INV(0.0526,0,1)"

The image of the ramp with dimensions is missing, so i have attached it.

Answer:

680 in² of wood is needed.

Step-by-step explanation:

The way to find how much wood would be needed by devon would be to find the total surface area of the ramp.

From the attached image,

Let's find the area of the 2 triangles first;

A1 = 2(½bh) = bh = 15 x 8 = 120 in²

Area of the slant rectangular portion;

A2 = 17 x 14 = 238 in²

Area of the base;

A3 = 15 × 14 = 210 in²

Area of vertical rectangle;

A4 = 8 × 14 = 112 in²

Total Surface Area = A1 + A2 + A3 + A4 = 120 + 238 + 210 + 112 = 680 in²

Answer:

d. 10th  e. 26th

Step-by-step explanation:

22-12=10

12+14=26

Answer:

C.

Step-by-step explanation:

1/2r = 2π/Cb

The answer is B..........

Answer:

B. 1

Step-by-step explanation:

If it was more than one it wouldn't be a triangle.

Answer:

a = 13

b = 0

Step-by-step explanation:

Conjugate of -3 + 2i is -3 - 2i

(-3 + 2i) (-3 - 2i)

We need to expand:

9 + 6i + -6i + -4i^2

-4i^2 =(-4)(-1) = 4

9 + 4 = 13

a = 13

b = 0

Step-by-step explanation:

45.50

Converting decimal

45.50 x 100 = 4550

Before Andrei adds the marbles to the glass tank, the glass tank was empty. This means that the volume of the empty tank is when n = 0 and the volume is 32 liters.

Given that:

[tex]W = 32 - 0.05n[/tex]

A linear function is represented as:

[tex]y = b + mx[/tex]

Where

[tex]b \to[/tex] y intercept

Literally, the y intercept is the initial value of the function.

In this function, the y intercept means the initial volume of the glass tank before filling it with marbles.

Compare [tex]y = b + mx[/tex] and [tex]W = 32 - 0.05n[/tex]

[tex]b = 32[/tex]

This means that the volume of the glass tank is 32 liters.

Read more about linear functions at:

https://brainly.com/question/21107621

Answer:

0.05

Step-by-step explanation:

Answer:

Among mildly obese people, 95% of the people have between 251 and 495 minutes of activity per day.

Among lean people, 95% of the people have between 317 and 733 minutes of activity per day.

Step-by-step explanation:

The Empirical Rule states that, for a normally distributed random variable:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviation of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

Within what limits do the active minutes for 95% of the people in each group fall

By the Empirical Rule, within 2 standard deviations of the mean.

Mildly obese:

Mean = 373, standard deviation = 61.

373 - 2*61 = 251 minutes

373 + 2*61 = 495 minutes

Among mildly obese people, 95% of the people have between 251 and 495 minutes of activity per day.

Lean people:

Mean = 525, standard deviation = 104

525 - 2*104 = 317 minutes

525 + 2*104 = 733 minutes

Among lean people, 95% of the people have between 317 and 733 minutes of activity per day.

Answer:

Step-by-step explanation:

a) The %tax comes from the "Rate" column on the line "up to $9525". It is 10%.

__

b) Simply compute the difference shown:

  $38,700 -$9,525 = $29,175

__

c) 22% of $9,300 is ...

  0.22 × $9,300 = $2,046

__

d) The total from the three previous calculations is ...

  $952.50 +3,501.00 +2,046.00 = $6,499.50

Answer:

10%

$29,175

$2,046

$6,499.50

got it right on ttm.  

Step-by-step explanation:

just believe me it works

Answer:  The answer is C 90

Step-by-step explanation: Rotations is ¼ and the Radians is π/2

Answer:

Step-by-step explanation:Srry it's bit rough...

Answer:

x^3-6x^2-4x-8

Step-by-step explanation:

First you would multiply (x-2) by itself (x-2) to get

x^2-2x-2x+4

then you would combine like terms

x^2-4x+4

Then you would multiply that by x-2

(x^2-4x+4)(x-2)

x^3-2x^2-4x^2-8x+4x-8

then you combine like terms

x^3-6x^2-4x-8

Answer:

a) Level of significance α=0.05

Two-tailed test, with null and alternative hypothesis:

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

b) Student's t distribution. We assume equal variances for both populations, independent sampled values and populations normally distributed.

Test statistic t=-2.4

c) P-value = 0.018

d) Rejection of the null hypothesis.

The data is statistically significant.

e) There is evidence to conclude there is significant difference in average off-schedule times between the bus lines. The difference we see in the samples seems not due to pure chance.

Step-by-step explanation:

This is a hypothesis test for the difference between populations means.

The claim is that there is a significant difference in average off-schedule times for this bus lines.

Then, the null and alternative hypothesis are:

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

The significance level is 0.05.

The sample 1 (bus line A), of size n1=51 has a mean of 53 and a standard deviation of 17.

The sample 2 (bus line B), of size n2=60 has a mean of 60 and a standard deviation of 13.

The difference between sample means is Md=-7.

[tex]M_d=M_1-M_2=53-60=-7[/tex]

The estimated standard error of the difference between means is computed using the formula:

[tex]s_{M_d}=\sqrt{\dfrac{\sigma_1^2}{n_1}+\dfrac{\sigma_2^2}{n_2}}=\sqrt{\dfrac{17^2}{51}+\dfrac{13^2}{60}}\\\\\\s_{M_d}=\sqrt{5.667+2.817}=\sqrt{8.483}=2.913[/tex]

Then, we can calculate the t-statistic as:

[tex]t=\dfrac{M_d-(\mu_1-\mu_2)}{s_{M_d}}=\dfrac{-7-0}{2.913}=\dfrac{-7}{2.913}=-2.4[/tex]

The degrees of freedom for this test are:

[tex]df=n_1+n_2-1=51+60-2=109[/tex]

This test is a two-tailed test, with 109 degrees of freedom and t=-2.4, so the P-value for this test is calculated as (using a t-table):

[tex]\text{P-value}=2\cdot P(t<-2.4)=0.018[/tex]

As the P-value (0.018) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is enough evidence to support the claim that there is a significant difference in average off-schedule times for this bus lines.

Answer:

She can answer, after performing the hypothesis test, that there is not enough evidence to support the claim that the city firefighters salary is significantly lower than the national average.

Step-by-step explanation:

She can statistically test the claim of the firefighters to see if it has statistical evidence.

This is a hypothesis test for the population mean.

The claim is that the city firefighters salary is significantly lower than the national average.

Then, the null and alternative hypothesis are:

[tex]H_0: \mu=38202\\\\H_a:\mu< 38202[/tex]

The significance level is 0.1.  Is less conservative than 0.05, for example, so if there is little evidence, the null hypothesis with be rejected.

The sample has a size n=27.

The sample mean is M=38073.

As the standard deviation of the population is not known, we estimate it with the sample standard deviation, that has a value of s=575.

The estimated standard error of the mean is computed using the formula:

[tex]s_M=\dfrac{s}{\sqrt{n}}=\dfrac{575}{\sqrt{27}}=110.659[/tex]

Then, we can calculate the t-statistic as:

[tex]t=\dfrac{M-\mu}{s/\sqrt{n}}=\dfrac{38073-38202}{110.659}=\dfrac{-129}{110.659}=-1.17[/tex]

The degrees of freedom for this sample size are:

df=n-1=27-1=26

This test is a left-tailed test, with 26 degrees of freedom and t=-1.17, so the P-value for this test is calculated as (using a t-table):

[tex]\text{P-value}=P(t<-1.17)=0.127[/tex]

As the P-value (0.127) is bigger than the significance level (0.1), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the city firefighters salary is significantly lower than the national average.

Answer:

4

Step-by-step explanation:

Set the height of the missing bar to 4 as there are 4 quantities between 21-25.

Answer:

The expected value of the random variable with the given probability distribution = 12 .52

Step-by-step explanation:

Given data

 x    :   0         1            5       10     1000

p(x)  :  0.33  0.32   0.24     0.10    0.01

The expected value of the given random variable of given probability distribution

E(X)  =  ∑ x p ( X = x)

E(X)  =  0 × 0.33 + 1 × 0.32 + 5 × 0.24 + 10× 0.10 + 1000×0.01

E (X)  =  12.52

Answer:

Step-by-step explanation:

0.00039 hm

Answer:

0.00039 hm is ur answer....

3.9 cm to 0.00039 hm...

Mark me as Brainlist...

Answer:

Answere is X= 8

Step-by-step explanation:

Use sine law

Sin(angle) = Opposite/ Hypotenuse

Sin (30) = 4 /X

X = 4 / sin (30)

X = 8

Answer:

96

Step-by-step explanation:

60% * 160 = 0.6 * 160 = 96.

Answer:

None

Step-by-step explanation:

There is no Forest Green iPhone XR's only the 11 Pros have that color.

Answer:

7/9

Step-by-step explanation:

7/15 ÷ 3/5

Copy dot flip

7/15 * 5/3

7/3 * 5/15

7/3 * 1/3

7/9

Answer:

I think it is 288.6 ft. Lol hope this helps

Step-by-step explanation:

Answer:

Set the height up to 4

Step-by-step explanation:

Since there are 4 numbers between 1-5, set the height up to 4

Answer:

4 temperature recordings.

Step-by-step explanation:

2, 2, 4, 5

There are 4 recordings in the range of 1-5°C.

Answer:

The answer is D.

Step-by-step explanation:

You have to apply Indices Law,

[tex] { ({a}^{m}) }^{n} \: ⇒ \: {a}^{mn} [/tex]

So for this question :

[tex] { ({6}^{7}) }^{3} [/tex]

[tex] = {6}^{7 \times 3} [/tex]

[tex] = {6}^{21} [/tex]

Answer:

The null hypothesis is that all the different teaching methods have the same average test scores.

H0: μ1 = μ2 = μ3 = μ4 = μ5

The alternative hypothesis is that at least one of the teaching methods have a different mean.

Ha: at least one mean is different. (μ1 ≠ μi)

Step-by-step explanation:

The null hypothesis (H0) tries to show that no significant variation exists between variables or that a single variable is no different than its mean. While an alternative Hypothesis (Ha) attempt to prove that a new theory is true rather than the old one. That a variable is significantly different from the mean.

For the case above, let μ represent the average test scores for the teaching methods:

The null hypothesis is that all the different teaching methods have the same average test scores.

H0: μ1 = μ2 = μ3 = μ4 = μ5

The alternative hypothesis is that at least one of the teaching methods have a different mean.

Ha: at least one mean is different. (μ1 ≠ μi)