Please help asap I needs someone to find the addition property added

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Explanation:

We have an octagon because there are n = 8 sides. The diagram below shows one way to number the sides so you can count them efficiently (without missing any or double counting any).

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Plug n = 8 into the formula below

S = 180(n-2)

S = 180(8-2)

S = 180(6)

S = 1080

The 8 interior angles add up to 1080 degrees.

Answer:

decrease

Step-by-step explanation:

Answer:

Step-by-step explanation:

a). For function 'f',

Slope of a linear function passing through two points [tex](x_1,y_1)[/tex] and [tex](x_2,y_2)[/tex] is given by,

Slope = [tex]\frac{y_2-y_1}{x_2-x_1}[/tex]

For the function 'f' given in the table,

Slope of the linear function passing through two points (-1, -5) and (0, -1) given in the table,

Slope = [tex]\frac{-5+1}{-1-0}[/tex]

          = 4

Equation of the line passing through a point (0, -1) and slope = 4 will be,

y - y' = m(x - x')

y + 1 = 4(x - 0)

y = 4x - 1

f(x) = 4x - 1

For function 'g',

Equation of the function 'g' has been given as,

g(x) = 4x + 3

By comparing this equation with the slope-intercept equation of a line,

y = mx + b

Therefore, slope of the function 'g' is,

m = 4

Since slopes of both the functions are same, linear graphs of both the functions will be parallel.

b). Equation of the function 'f' is,

f(x) = 4x - 1

y-intercept of the function = -1

Equation of function 'g',

g(x) = 4x + 3

y-intercept = 3

Therefore, function 'g' will have the greater y-intercept.

Answer:

The probability that the proportion of airborne viruses in a sample of 662 viruses would be greater than 6%=0.00427

Step-by-step explanation:

We are given that

[tex]\mu_{\hat{p}}=p=4%=0.04[/tex]

n=662

We have to find the probability that the proportion of airborne viruses in a sample of 662 viruses would be greater than 6%.

q=1-p=1-0.04=0.96

[tex]\sigma_{\hat{p}}=\sqrt{p(1-p)/n}[/tex]

[tex]\sigma_{\hat{p}}=\sqrt{\frac{0.04(1-0.04)}{662}}[/tex]

[tex]\sigma_{\hat{p}}=0.0076[/tex]

Now,

[tex]P(\hat{p}>0.06)=1-P(\hat{p}<0.06)[/tex]

[tex]=1-P(\frac{\hat{p}-\mu_{\hat{p}}}{\sigma_{\hat{p}}}<\frac{0.06-0.04}{0.0076})[/tex]

[tex]=1-P(Z<2.63)[/tex]

[tex]=1-0.99573[/tex]

[tex]P(\hat{p}>0.06)=0.00427[/tex]

Hence, the probability that the proportion of airborne viruses in a sample of 662 viruses would be greater than 6%=0.00427

Answer:

By using a pair of compasses and a ruler you can draw all angles

Answer:

10 hours

Step-by-step explanation:

ok so we know he is getting payed $20 + $7 every hour so what i would do is keep the multiply the 7 till you get 70 so thats 7x10=70 and 70+20=90 so he worked for 10 hours last week :)  i hope this helps, i tried my best to explain it

Answer:

f(6)=-42

f(0)=0

f(-1)=7

Step-by-step explanation:

since f(x) =-7x

it implies that f(6),f(0) and f(-1) are all equal to f(x)

which is equal to -7x .

so wherever you find x you out it in the

function

The angle C of the triangle ABC is ( π - 3a ).

The angle is defined as the span between two intersecting lines or surfaces at or close to the point where they meet.

The angle will be calculated as follows:-

We know that the sum of the angles of the triangle is 180 degrees or π in radians.

∠A + ∠B + ∠C = π

a + 2a + ∠C = π

∠C = π - a - 2a

∠C = π - 3a

Therefore angle C of the triangle ABC is ( π - 3a ).

To know more about an angle follow

https://brainly.com/question/25770607

#SPJ2

Answer:

0.9624 = 96.24% probability that the sample proportion will differ from the population proportion by less than 3%

Step-by-step explanation:

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

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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 p-value, we get the probability that the value of the measure is greater than X.

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]

Suppose a large shipment of televisions contained 9% defectives

This means that [tex]p = 0.09[/tex]

Sample of size 393

This means that [tex]n = 393[/tex]

Mean and standard deviation:

[tex]\mu = p = 0.09[/tex]

[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.09*0.91}{393}} = 0.0144[/tex]

What is the probability that the sample proportion will differ from the population proportion by less than 3%?

Proportion between 0.09 - 0.03 = 0.06 and 0.09 + 0.03 = 0.12, which is the p-value of Z when X = 0.12 subtracted by the p-value of Z when X = 0.06.

X = 0.12

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

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

[tex]Z = \frac{0.12 - 0.09}{0.0144}[/tex]

[tex]Z = 2.08[/tex]

[tex]Z = 2.08[/tex] has a p-value of 0.9812

X = 0.06

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

[tex]Z = \frac{0.06 - 0.09}{0.0144}[/tex]

[tex]Z = -2.08[/tex]

[tex]Z = -2.08[/tex] has a p-value of 0.0188

0.9812 - 0.0188 = 0.9624

0.9624 = 96.24% probability that the sample proportion will differ from the population proportion by less than 3%

Answer:

y = -2(x + 3)² + 2

y = 2{ -(x + 3)²+ 1}

y = 2{ -(x² + 6x + 9) + 1}

y = 2{ -x² - 6x - 9 + 1}

y = 2{ -x² - 6x - 8 }

y = -2 { x² + 6x + 8}

OR

y = -2{(x + 4)(x + 2)}

Answer:

3396.65

Step-by-step explanation:

Let's start by cacluating the amount the bank is loaning us

800000*.8=640000

Let's now calculate the effective rate: .049/12= .004083333333

let x= payment

[tex]640000=x\frac{1-(1+.004083333333)^{-30*12}}{.004083333333}\\x=3396.651012[/tex]

Answer:

x=-6, y=0

Step-by-step explanation:

it's impossible to fully solve an equation where 2 variables are unknown. So we have to make it equal to 1 set. to do this, we have to think logically.

if y=x+6, then that means wherever it says y, we can put x+6. because x+6=x+6, right? so we plug x+6 into the second equation and get.

x+6=0.5x+3

to solve for x we subtract 6 from one side and 0.5 from the other and get

0.5x=-3

then we multiply both sides by 2 to make be a whole number

x=-6

now we just plug this into either equation. because the first one is easier, we can just set it up as

y=(-6)+6

which means y=0

Answer:

pretty sure it could

Step-by-step explanation:

Answer:

What it's asking is for 2 angles at different angles of attack, are parallel

Step-by-step explanation:

for example, // these two slashes are parallel because they wont ever touch, it wants you to find if the angles are parallel or not.

Answer:

[-3, -1]

Step-by-step explanation:

The minimum y value is -3.

The maximum y value is -1.

-3 and -1 are included, so we use square brackets.

Answer: [-3, -1]

Lauren will get 2/25 because the coin only lands on heads or tail

Answer:

option one is the correct answer

Answer:

1/625

Step-by-step explanation:

Answer:

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

Step-by-step explanation:

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

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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 p-value, we get the probability that the value of the measure is greater than X.

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.

Mean diameter of 144 millimeters, and a variance of 49.

This means that [tex]\mu = 144, \sigma = \sqrt{49} = 7[/tex]

Sample of 46:

This means that [tex]n = 46, s = \frac{7}{\sqrt{46}}[/tex]

Wat is the probability that the sample mean would differ from the population mean by more than 2 millimeters?

Above 144 + 2 = 146 or below 144 - 2 = 142. Since the normal distribution is symmetric, these probabilities are equal, which means that we find one of them and multiply by two.

Probability the sample mean is below 142:

p-value of Z when X = 142, so:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

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

[tex]Z = \frac{142 - 144}{\frac{7}{\sqrt{46}}}[/tex]

[tex]Z = -1.94[/tex]

[tex]Z = -1.94[/tex] has a p-value of 0.0262

2*0.0262 = 0.0524

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

Answer:

Step 1

Because the number in front of the bracket is 1 and it is also affected by the negative sign(-),5 is supposed to be negative not positive because (negative by positive is negative)

And since the first step has an error in it,the remaining steps would also be wrong.

Answer:

9 4/24 or 9 1/6

Answer:

(-7, -1) =(x1,y1)

(8, 5)=(x2,y2)

now

[tex]slope (m) = \frac{y2 - y1}{x2 - x1} [/tex]

[tex]or = \frac{5 - ( - 1)}{8 - ( - 7)} [/tex]

[tex]or = \frac{5 + 1} {8 + 7} [/tex]

[tex]or = \frac{6}{15} [/tex]

[tex]or = \frac{2}{5} [/tex]

Step-by-step explanation:

hope it is helpful to you ☺️

Answer:

11/6

Step-by-step explanation:

Answer:

Option A

Step-by-step explanation:

Histogram shows the range of data on the x-axis while the frequency of occurrence is on the y-axis.

We have the following ranges from the Histogram ;

0 to 11

11 to 22

22 to 33

33 to 44

44 to 55

55 to 66

66 to 77

77 to 88

88 to 99

99 to 110

From the given set of data, the frequency according to the range is as follows;

0 to 11; 4

11 to 22; 8

22 to 33; 7

33 to 44; 6

44 to 55; 4

55 to 66; 2

66 to 77; 2

77 to 88; 1

88 to 99; 0

99 to 110; 1

The only Histogram that corresponds to these frequency is option A

Answer:

4.286

Step-by-step explanation:

you really need help with this ? you cannot just use your calculator ? that would have been faster than putting that question in here ...

remember, similar to the number positions in front of the decimal point, it is equally important to add the same positions after the decimal point.

we have 10th, 100th, 1000th, 10000th, 100000th, ... no end possible.

so we have

2.826 miles

and need to add 1.46 miles

2.826

1.46

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4.286

and the line of thinking goes from right to left

nothing plus 6 is 6

6 plus 2 is 8

4 plus 8 is 12, so we write 2 and carry over the 1

1 plus 2 plus 1 carry over is 4

if it helps, you can always add zeroes at the end of any digits after the decimal point, as you can also add zeroes in front to the digits before the decimal point to make both numbers have the same length and their decimal points are perfectly aligned.

our addition could have also looked like

2.826

1.460

with the same result

overall, if this is truly helping you, an example of using both leading and tailing zeroes could be

4278.9472081

0021.6380000

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4300.5852081

9514 1404 393

Answer:

  (t, u, w) = (1, -2, -2)

Step-by-step explanation:

A graphing calculator makes short work of this, giving the solution as ...

  (t, u, w) = (1, -2, -2)

__

There are many ways to solve this "by hand." Here's one of them.

Add the first and third equations. Their sum is ...

  -3t +4w = -11 . . . . . [eq4]

Add this to twice the second equation. That sum is ...

  (-3t +4w) +2(-4t -2w) = (-11) +2(0)

  -11t = -11

  t = 1

Substituting this into the second equation gives ...

  -4(1) -2w = 0

  w +2 = 0 . . . . divide by -2

  w = -2 . . . . add -2

Substituting for t in the third equation lets us find u.

  2(1) -2u = 6

  -1 +u = -3 . . . . . divide by -2

  u = -2 . . . . add 1

The solution is (t, u, w) = (1, -2, -2).

Answer:

0.7994 = 79.94% probability that the proportion of persons with myopia will differ from the population proportion by less than 3%.

Step-by-step explanation:

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

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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 p-value, we get the probability that the value of the measure is greater than X.

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]

Suppose 42% of the population has myopia.

This means that [tex]p = 0.42[/tex]

Random sample of size 442 is selected

This means that [tex]n = 442[/tex]

Mean and standard deviation:

[tex]\mu = p = 0.42[/tex]

[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.42*0.58}{442}} = 0.0235[/tex]

What is the probability that the proportion of persons with myopia will differ from the population proportion by less than 3%?

Proportion between 0.42 + 0.03 = 0.45 and 0.42 - 0.03 = 0.39, which is the p-value of Z when X = 0.45 subtracted by the p-value of Z when X = 0.39.

X = 0.45

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

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

[tex]Z = \frac{0.45 - 0.42}{0.0235}[/tex]

[tex]Z = 1.28[/tex]

[tex]Z = 1.28[/tex] has a p-value of 0.8997

X = 0.39

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

[tex]Z = \frac{0.39 - 0.42}{0.0235}[/tex]

[tex]Z = -1.28[/tex]

[tex]Z = -1.28[/tex] has a p-value of 0.1003

0.8997 - 0.1003 = 0.7994

0.7994 = 79.94% probability that the proportion of persons with myopia will differ from the population proportion by less than 3%.

Answer:

Look into the picture

Step-by-step explanation:

Let me know if there's something wrong to my answer

Answer:

0.8743 = 87.43% probability that more than one accident occurs per year

Step-by-step explanation:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

In which

x is the number of sucesses

e = 2.71828 is the Euler number

[tex]\mu[/tex] is the mean in the given interval.

Buchtal, a manufacturer of ceramic tiles, reports on average 3.1 job-related accidents per year.

This means that [tex]\mu = 3.1[/tex]

What is the probability that more than one accident occurs per year?

This is:

[tex]P(X > 1) = 1 - P(X \leq 1)[/tex]

In which

[tex]P(X \leq 1) = P(X = 0) + P(X = 1)[/tex]

Then

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

[tex]P(X = 0) = \frac{e^{-3.6}*(3.6)^{0}}{(0)!} = 0.0273[/tex]

[tex]P(X = 1) = \frac{e^{-3.6}*(3.6)^{1}}{(1)!} = 0.0984[/tex]

[tex]P(X \leq 1) = P(X = 0) + P(X = 1) = 0.0273 + 0.0984 = 0.1257[/tex]

[tex]P(X > 1) = 1 - P(X \leq 1) = 1 - 0.1257 = 0.8743[/tex]

0.8743 = 87.43% probability that more than one accident occurs per year

the median of restaurant b's cleanliness ratings is 2.

the median of restaurant b's food quality ratings is 4.

the median of restaurant b's service ratings is 3.

:))

Answer:

the degree is the value of the biggest exponent = 5 (fifth degree)

Step-by-step explanation:

Answer:

5

Step-by-step explanation:

Since the highest power of x is 5, the degree of the polynomial x

3

−9x+3x

5

is 5.

Answer:

Types of variables:

Continuous variable include: income

Discrete variable include: number of dependents

Scale of measurement:

Nominal data include: Social security number

There is no ordinal data included

There is no interval data included

Ratio data include: Annual income,

Number of dependents.

Explanation:

Continuous variables are variables that are obtained by just counting, example: counting the number of times someone eats in a day.

Discrete variables are simply variables that are measured and are usually more precise than continuous variables, example: time, weight, length etc.

Nominal data are data types that are in the form of labels or names and do not have any particular order, example :social security number basically identifies a person and is not ranked or ordered in any way.

Ordinal data are data types that also in the form of names but with ranking and order.

Interval data are data types that rank and order data but with continuous measurement that may take on negative values, example measure of temperature.

Ratio data is same as interval data but does not take negative values, example we can not say that someone is -6 years old.