5x^2-10x=0 written in factored form​

If the length of the tile is x and the breadth of the tile is y then the area of each tile is equal to xy units.

Given that we can assume the length of tile be x and breadth of tile be y. We are required to find the area of the each tile and draw a figure showing the tile whose length is x and the breadth is y.

Tile is in the shape of the rectangle because the length and breadth are different and we know that the area of the rectangle is equal to product of the length and breadth of that rectangle.

If the length of tile is x and the breadth of tile is y then the area of the tile is equal to x*y which is xy units. Figure is attached with the solution.

Hence if the length of the tile is x and the breadth of the tile is y then the area of each tile is equal to xy units.

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Butt Koko, this is the solution:

Original price = 19.99

Sale price = 15.99

Discount = 19.99 - 15.99 = 4.00

We can use Direct Rule of Three to calculate the percent of discount, this way:

Price Percent

19.99 100

4.00 x

___________________

4 * 100 = 19.99 * x

400 = 19.99x

x = 400/19.99

x = 20.01

The approximate percent discount on the frisbee is 20%

Answer:

mean = 86

mean w/o 2 lowest = 92

median = 91

median w/o 2 lowest = 93

mode = 98

mode w/o 2 lowest = 98

Step-by-step explanation:

Answer:

I have no clue

Step-by-step explanation:

The maximum profit will be $87,000.

To find the quantity of things that will augment the benefit, we want to find the vertex of the parabola addressed by the given capability.

The vertex of a parabola in the form of\(y = ax^2 + bx + c\) is located at the point \((-b/2a, c - b^2/4a)\).

So for the function \(P(x) = -3x^2 + 12x + 75,\) the coefficient of \(x^2\) is -3, the coefficient of x is 12, and the constant term is 75.

Therefore, the number of items that will maximize the profit is:

x = -b/2a = -12 / 2(-3) = 2

The second derivative test is something we can use to make sure that this is a maximum. The vertex is a maximum when the second derivative of P(x) is -6, which is negative.

Since x is in thousands, the maximum profit occurs when 2,000 items are produced, and the maximum profit is:

\(P(2) = -3(2)^2 + 12(2) + 75 = 87\)

Hence, the business will boost its benefit by making 2,000 things, and the most extreme benefit will be $87,000.

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hope it helps you

thank you

Answer:

8 GB

Step-by-step explanation:

Cost = sum of fees 1, 2, and 3

C = 56 + .95g +  .08t

so

68 = 56 + .95g + .08(55)

68 = 56 + .95g + .08(55)

68 = 56 + .95g + 4.4

68 - 56 - 4.4 = .95g

7.6 = .95 g

7.6/.95 = g

8 = g

Answer:

Step-by-step explanation:

The root which is 2 is the fractional portion of your exponent

\(\sqrt{x^{7} y^{12} }\)

=\((x^{7} y^{12} )^{\frac{1}{2} }\)              >You can distribute 1/2 to each term by multiplying

\(=x^{\frac{7}{2} } y^{6\)

Answer:

x = -4/7

Step-by-step explanation:

-5/2x + 1 = x + 3

-7/2x = 2

(-2/7)-7/2x = 2(-2/7)

x = -4/7

Answer:

17+3x

that is the answer

Answer:

17 + 3x

Step-by-step explanation:

9 + 8 + 3x

=17 + 3x

because the 3 contain a valuable x that why it is add to the 17

Answer:

Congruent Angles

Step-by-step explanation:

Answer: C : Congruent Angles

Step-by-step explanation:

I just took the test

Answer:

7. y=46,x=44

Step-by-step explanation:

srq=y(alternate angles)

38+y=84(sum of the two opposite interior angles equals to exterior)

therefore y=46

x+y=90(sum of the two adjacent angles of a right angled triangle)

x+46=90

x=44

therefore y=46 and x=44

A positive \(\frac{3\pi }{2}\) radians angle’s terminal side falls on the negative y-axis.

The starting side of the angle is the primary ray, whereas the end position of the ray following rotation is the terminal side of that angle.

A positive 270 degree angle’s terminal side falls on the negative y-axis as shown in the figure.

Hence, a positive \(\frac{3\pi }{2}\) radians angle’s terminal side falls on the negative y-axis.

Thus, option (B) is correct.

Consider the following figure for this.

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Answer: B

Step-by-step explanation:

Answer: AB= 4 times 5 i think

Step-by-step explanation:

Since T(0) ≠ 0, we can conclude that the transformation T is not linear.

The correct answer is: T(0) ≠ 0

To determine if the transformation T is linear, we need to check if it satisfies two properties: T(0) = 0 and T(cu + dv) = cT(u) + dT(v) for all vectors u, v in the domain of T and all scalars c, d.

Let's evaluate T(0) to check if it satisfies the first property:

T(0, 0) = (3(0), -2(0), 0+5, 4(0)) = (0, 0, 5, 0)

Now, let's analyze what is true about T(0):

T(0) = (0, 0, 5, 0)

From this result, we can see that T(0) is not equal to the zero vector (0, 0, 0, 0). According to the first property, for a transformation to be linear, T(0) must be equal to the zero vector.

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yt= output. y∗= potential output.ϵv= random shock with a normal distribution with zero mean and constant variance σv2.ϵd= random shock with a normal distribution with zero mean and constant variance σd2.ϵp= random shock with a normal distribution with zero mean and constant variance σp2.

The model can be described as a three-equation New Keynesian model with partial indexation. The model consists of an aggregate supply equation, an interest rate reaction function, and a Phillips curve equation.

Aggregate Supply Equation: The aggregate supply equation indicates that the economy's potential output grows at a constant rate γ and that the actual output grows at the same rate plus a stochastic component that follows a normal distribution with zero mean and constant variance σv2. Yt = Yt-1+γ+(ϵv)i Interest Rate Reaction Function: The interest rate reaction function states that the central bank sets the policy interest rate according to a linear combination of expected inflation, the deviation of the output gap from potential, and the long-run real interest rate.

It is assumed that the long-run real interest rate equals the steady-state real interest rate r∗ and that it does not depend on macroeconomic variables. i = πe+β(Etπt+1−π∗)+βvvt+1+ϵd Phillips Curve Equation: The Phillips curve equation states that inflation depends on expected inflation, the output gap, and a random shock.

It is assumed that the expected inflation equals actual inflation and that the deviation of output from potential is a function of the current output gap and the previous output gap. πt = πt−1+κ(yt−y∗)+ϵpwhereγ= the rate at which potential output grows.t= time in periods. i= the nominal interest rate.

πe= expected inflation. r*= long-run real interest rate.β= a coefficient representing the responsiveness of consumption, investment, and other economic variables to changes in interest rates. Etπt+1= expected inflation in the next period. vt= output gap.ω= coefficient representing the responsiveness of prices to changes in output. e= a measure of output-gap persistence.κ= coefficient measuring the responsiveness of inflation to the output gap.

yt= output. y∗= potential output.ϵv= random shock with a normal distribution with zero mean and constant variance σv2.ϵd= random shock with a normal distribution with zero mean and constant variance σd2.ϵp= random shock with a normal distribution with zero mean and constant variance σp2.

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The hare can afford to nap for approximately 3686.33 seconds if he does not want to lose the race.

We can use the time it takes the hare to run 100 m to determine how long he can afford to nap.

First, let's find the time it takes the hare to run the 100 m:

t = d / v

Where t is the time, d is the distance, and v is the velocity (speed) of the hare.

t = 100 m / 15 m/s

t = 6.67 s

Next, let's find the time it takes the tortoise to run 1 km (1000 m):

t = d / v

Where t is the time, d is the distance, and v is the velocity (speed) of the tortoise.

t = 1000 m / 0.27 m/s

t = 3700 s

So, the time it takes the tortoise to run the race is 3700 s. The time it takes the hare to run the first 900 m is 7 s. Therefore, the time the hare has left to nap is:

3700 s - 7 s = 3693 s

And the time it takes the hare to run the last 100 m is 6.67 s. Therefore, the hare can afford to nap for:

3693 s - 6.67 s = 3686.33 s

So, the hare can afford to nap for approximately 3686.33 seconds if he does not want to lose the race.

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75 is the biggest number with which 525 and 3000 can be divided, making it the greatest common factor.

Finding all common factors between two integers and choosing the biggest one yields the highest common factor (HCF). It is the most powerful divisor for any pair of integers that can divide the inputted numbers evenly or fully. The largest of all the common factors between two or more integers is known as the Highest Common Factor (HCF). A number that divides two or more integers precisely is referred to as a common factor. Factors are numerical combinations that we may multiply to produce another number. These are the "common factors" when we determine the factors of two or more integers and discover some of those factors are the same (or "common").

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Answer:

rocks. rocks everywhere means no where for trees so no foods.

Step-by-step explanation:

3)  since we don't have the information about the interest paid (I), we cannot determine the rate of interest at this time.

(1) To find the total amount Adrian paid in 36 months, we can multiply the monthly installment by the number of installments:

Total payment A = Monthly installment * Number of installments

              = $375 * 36

              = $13,500

Therefore, Adrian paid a total of $13,500 over the course of 36 months.

(2) In the simple interest formula I = Prt, the letters used represent the following variables:

I: Interest (the amount of interest paid)

P: Principal (the initial amount, or in this case, the car worth)

r: Rate of interest (expressed as a decimal)

t: Time (in years)

(3) To find the rate of interest in percentage, we need more information. The simple interest formula can be rearranged to solve for the rate of interest:

r = (I / Pt) * 100

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Answer:

18+15+8= 41

Step-by-step explanation:

some words to ask

a) Any value outside of Q1 - 1.5(IQR) and Q3 + 1.5(IQR) can be considered a potential outlier.

b) This will give us a visual representation of the distribution of income among the full-time students.

c) It is important to analyze outliers carefully to ensure that they are not artificially skewing the results of our analysis.

(a) To check for outliers in the data set, we can use the box-and-whisker plot or the z-score method. However, since we do not have the exact data, we cannot use these methods. One way to identify potential outliers is to calculate the quartiles (Q1, Q2, and Q3) and the interquartile range (IQR).

(b) To draw a histogram of the data, we can use the frequency distribution table given in the question. The x-axis should represent the income ranges (e.g. $0-$100, $100-$200, etc.) and the y-axis should represent the frequency (i.e. the number of students who earned income within each range).

(c) If there are any outliers in the data set, we need to investigate them further to determine the reason for their unusual values. Possible reasons for outliers could be data entry errors, extreme values due to high- or low-income jobs, or unique situations such as unexpected windfalls or emergencies.

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Answer:

Step-by-step explanation:

Answer:

SA = 94 ft²

Step-by-step explanation:

To find the surface area of a rectangular prism, you can use the equation:

SA = 2 ( wl + hl + hw )

SA = surface area of rectangular prism

l = length

w = width

h = height

In the image, we are given the following information:

l = 4

w = 5

h = 3

Now, let's plug in the information given to us to solve for surface area:

SA = 2 ( wl + hl + hw)

SA = 2 ( 5(4) + 3(4) + 3(5) )

SA = 2 ( 20 + 12 + 15 )

SA = 2 ( 47 )

SA = 94 ft²

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The number of employees that must be included in the sample to be 95% confident that the sample mean is within 1.5 hours of the population mean is 107 employees.

To estimate the mean number of hours worked by all grocery store employees in the county with 95% confidence and a margin of error of 1.5 hours, we can use the sample size formula:

n = (Z * σ / E)²

where:
- n is the required sample size
- Z is the critical value (1.96 for a 95% level of confidence)
- σ is the population standard deviation (7.9 from the previous study)
- E is the margin of error (1.5 hours)

Plugging in the given values:

n = (1.96 * 7.9 / 1.5)²

n ≈ 106.56

Since you cannot have a fraction of an employee, you need to round up to the nearest whole number. Therefore, the researcher must include 107 employees in the sample to be 95% confident that the sample mean is within 1.5 hours of the population mean.

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1   Y is distributed as N(aμ + b, a^2σ^2), as desired.

2  We have shown that under these conditions, E[XY] = E[X]E[Y].

To prove that Y is distributed as N(aμ + b, a^2σ^2), we need to show that the mean and variance of Y match those of a normal distribution with parameters aμ + b and a^2σ^2, respectively.

First, let's find the mean of Y:

E(Y) = E(aX + b) = aE(X) + b = aμ + b

Next, let's find the variance of Y:

Var(Y) = Var(aX + b) = a^2Var(X) = a^2σ^2

Therefore, Y is distributed as N(aμ + b, a^2σ^2), as desired.

We can use the definition of covariance to prove that E[XY] = E[X]E[Y]. By the properties of expected value, we know that:

E[XY] = ∫∫ xy f(x,y) dxdy

where f(x,y) is the joint probability density function of X and Y.

Then, we can use the fact that X and Y are independent to simplify the expression:

E[XY] = ∫∫ xy f(x) f(y) dxdy

= ∫ x f(x) dx ∫ y f(y) dy

= E[X]E[Y]

where f(x) and f(y) are the marginal probability density functions of X and Y, respectively.

Therefore, we have shown that under these conditions, E[XY] = E[X]E[Y].

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Answer:

2) 4

Step-by-step explanation:

because 4 x 4= 16

\(\sqrt{16} = 4\)

Out of the 25 sheets of construction paper, 10% of each sheet is a secondary color. The numbers provided, such as 8, 10, 12, and 15, seem to represent the quantities of secondary-color sheets, but the specific distribution is not clear. Therefore, without further information, it is not possible to determine the exact number of secondary-color sheets.

The problem states that 40% of the sheets of construction paper are secondary colors. However, the given numbers (8, 10, 12, 15) do not directly correspond to the 40% distribution or the 25 total sheets. The numbers seem to represent quantities of secondary-color sheets, but the specific allocation is not clear.
To calculate the number of secondary-color sheets, we would need the distribution percentages or exact quantities for each secondary color (e.g., red, blue, green). Without this information, we cannot determine the exact number of secondary-color sheets.
Therefore, based on the provided information, we cannot determine the precise number of secondary-color sheets out of the 25 sheets of construction paper.

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