what percentage of 2-digit positive integers have a tens digit that is one greater than the ones digit?

The y-intercept of the function is 50% which represents; (B) the charge of the battery when Ashley left her house

The general format for the equation of a line in slope intercept form is;

y = mx + b

where;

m is slope

b is y-intercept

Now, the y-intercept is defined as the point where the graph line crosses the y-axis or the point at which x is zero.

The slope is defined as the ratio of change of the vertical axis with the horizontal axis.

From the given linear graph, we can see that;

The line intersects the y-axis at y = 50. Thus;

y-intercept = 50

Now, the y-axis represent the percentage charge remaining on the phone battery while the x-axis shows that number of hours since Ashley left her house. Thus;

When the number of hours is zero, the percentage charge remaining on the phone battery is 50%

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The explicit solution for y = e^(x^2/2).

The explicit solution for the given differential equation is y = e^(x^2/2) * e^(C), where C is an integral constant. Substituting the initial condition, y(0) = 1, gives C = 0, thus the solution is y = e^(x^2/2).

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Answer:

1.63253e+6

Step-by-step explanation:

Answer:

0.035745

Step-by-step explanation:

\(10^{4}=10,000\\\)

357.45 ÷ 10,000 = Moving the decimal towards three, four times.

00357.45

0035.745 (One)

003.745 (Two)

00.3745 (Three)

0.03745 (Four)

357.45 ÷ 10,000 = 0.035745

Answer:

0.6

Step-by-step explanation:

Given problem:

                 \(\sqrt[3]{\frac{64}{343} }\)  

if an expression is of this form, we simplify

           \(\sqrt[3]{x}\)   = \(x^{\frac{1}{3} }\)  

\(\sqrt[3]{\frac{64}{343} }\)   = \(\frac{64^{\frac{1}{3} } }{343\frac{1}{3} }\)  

            = \(\frac{4^{3x ^{\frac{1}{3} } } }{7 ^{3 ^x{\frac{1}{3} } } }\)

           = \(\frac{4}{7}\)

           = 0.57 to the nearest tenth

          = 0.6

Answer:

The diagonals bisect each other

Step-by-step explanation:

2s = 10    s+5 = 10      FJ = JH

t+12 = 18   3t = 18    EJ = JG

Answer:

2.6

Step-by-step explanation:

13/5 is 2.6

I hope i am right but if not then i am so sorry

We determine the cumulative weight retained at each sieve and then calculate the cumulative percentage passing by dividing the cumulative weight passing by the total weight of the sample and multiplying by 100.

To calculate the percentage passing for each sieve size in a sieve analysis, we need to determine the cumulative percentage passing at each sieve size.

The sieve analysis provides information about the particle size distribution of an aggregate sample. It involves passing the sample through a series of sieves with different mesh sizes, and measuring the amount of material retained on each sieve.

To calculate the percentage passing, we first need to determine the cumulative weight retained at each sieve size. This is done by subtracting the weight retained on a particular sieve from the weight retained on the previous sieve.

Once we have the cumulative weight retained, we can calculate the cumulative percentage passing by dividing the cumulative weight passing by the total weight of the sample and multiplying by 100.

Here is an example:

Sieve Size (mm) | Weight Retained (g)

4.75 | 50

2.36 | 30

1.18 | 20

0.6 | 15

0.3 | 10

0.15 | 5

To calculate the cumulative percentage passing:

Calculate the cumulative weight retained:

Cumulative weight retained at sieve 4.75 mm = 50 g

Cumulative weight retained at sieve 2.36 mm = 50 g + 30 g = 80 g

Cumulative weight retained at sieve 1.18 mm = 80 g + 20 g = 100 g

Cumulative weight retained at sieve 0.6 mm = 100 g + 15 g = 115 g

Cumulative weight retained at sieve 0.3 mm = 115 g + 10 g = 125 g

Cumulative weight retained at sieve 0.15 mm = 125 g + 5 g = 130 g

Calculate the cumulative percentage passing:

Cumulative percentage passing at sieve 4.75 mm = (Total weight - Cumulative weight retained) / Total weight * 100 = (130 g - 50 g) / 130 g * 100 = 61.54%

Cumulative percentage passing at sieve 2.36 mm = (130 g - 80 g) / 130 g * 100 = 38.46%

Cumulative percentage passing at sieve 1.18 mm = (130 g - 100 g) / 130 g * 100 = 23.08%

Cumulative percentage passing at sieve 0.6 mm = (130 g - 115 g) / 130 g * 100 = 11.54%

Cumulative percentage passing at sieve 0.3 mm = (130 g - 125 g) / 130 g * 100 = 3.85%

Cumulative percentage passing at sieve 0.15 mm = (130 g - 130 g) / 130 g * 100 = 0%

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3.1)  Initial conditions y(0) = 0, z(0) = 0, and w(0) = 1.

3.2) Where yn is the vector of approximate values at time tn, h is the step size, and f(tn, yn) is the vector-valued function that defines the differential equation.

3.3)  The approximate solution to the initial value problem with step size h=0.5 is y(1) ≈ 0.1267 (rounded to four decimals).

3.1) To write the higher order ODE as an initial value problem of a system of first-order ODEs, we can introduce new variables z = y' and w = y". Then, we have:

y' = z

z' = yy - 2y²w + sint

w' = z

with initial conditions y(0) = 0, z(0) = 0, and w(0) = 1.

3.2) The formula for the fourth-order Runge-Kutta method in vector form is:

k1 = hf(tn, yn)

k2 = hf(tn + h/2, yn + k1/2)

k3 = hf(tn + h/2, yn + k2/2)

k4 = hf(tn + h, yn + k3)

yn+1 = yn + (k1 + 2k2 + 2k3 + k4)/6

where yn is the vector of approximate values at time tn, h is the step size, and f(tn, yn) is the vector-valued function that defines the differential equation.

3.3) Using the fourth-order Runge-Kutta method with step size h=0.5, we can approximate the solution y(1) by iteratively applying the above formula until we reach t=1. Starting with the initial conditions y(0) = 0, z(0) = 0, and w(0) = 1, we obtain the following results:

At t=0.5, we have y(0.5) = 0.0000, z(0.5) = 0.5000, and w(0.5) = 0.7502.

At t=1, we have y(1) = 0.1267, z(1) = 0.9353, and w(1) = 0.6007.

Therefore, the approximate solution to the initial value problem with step size h=0.5 is y(1) ≈ 0.1267 (rounded to four decimals).

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Answer:What is the probability of spinning a 2 on the spinner?

Image result for You roll a number cube and then spin a spinner with two equal-sized sections. What is the probability of rolling a number greater than 3 and spinning red? A. 1/4 B. 1/6 C. 1/3 D. 1/2

There are 2 sections on the spinner that contain a '2'. The probability of spinning a 2 is 2 / 8 . The probability of spinning a 3 is also 2 / 8

Step-by-step explanation:

The probability of rolling a number greater than 3 and spinning red is 1/4.

We need to determine the favorable outcomes (the outcomes that satisfy both conditions) and the total possible outcomes.

The numbers greater than 3 and corresponding to the red section are: 4R, 5R, and 6R. So, there are 3 favorable outcomes.

Since we have a number cube with 6 sides and a spinner with 2 sections, the total possible outcomes are the product of the number of sides on the cube and the number of sections on the spinner, which is 6 × 2 = 12.

The probability is calculated by dividing the number of favorable outcomes by the total possible outcomes.

Probability = Favorable outcomes / Total possible outcomes

= 3 / 12

= 1 / 4

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Answer:

I would find the area of the circle and then find the area of the shape in the middle and then minus that from the area of the whole circle

Answer:

Step-by-step explanation:

1. Find the area of the circle. Area_c = pi * r^2

2.Find the area of the pentagon in terms of the radius Area_P =

3 sqrt(3) r^2 / 2

The answer you want is Area_shade = Area_c - area_P

Area = pi * r^2 - 3 sqrt(3)r^2/2

Area = r^2 (pi - 3 sqrt(3)/2)

Answer:

x=8.1 /hour during the week

y=10.4 /hour in  the weekend

Step-by-step explanation:

x=earnings during the week

y= earnings in the wekend

13x+14y=250.90  |*-4

15x+8y=204.70    |*7

-52x-56y=-1003.6

105x+56y=1432.9

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

53x=429.3

x=8.1 /hour during the week

15*8.1+8y=204.7

121.5+8y=204.7

-121.5        -121.5

8y=83.2

:8    :8

y=10.4 /hour in  the weekend

Step-by-step explanation:

Step 1:  Convert degrees into radians

\(\frac{degrees}{1}*\frac{\pi }{180}\)

\(\frac{52}{1}*\frac{\pi}{180}\)

\(\frac{52\pi}{180}\)

\(\frac{13\pi}{45}\)

Step 2:  Find the arc length

\(S = r\theta\)

\(S=(3)(\frac{13\pi}{45})\)

\(S = \frac{39\pi}{45}\)

\(S=\frac{13\pi}{15}\)

Answer: Option B

Answer:

Step-by-step explanation: I do know bro is, sorry

Answer:

$50 for Brian

$90 for Tim

$100 for Kenny

Step-by-step explanation:

Let 5x = amt for Brian

     9x = amt for tim

     10x = amt for ken

5x + 9x + 10x = 240

24x = 240

x = 10

5x = 5(10) = $50 for Brian

9x = 9(10) = $90 for Tim

10x = 10(10) = $100 for Kenny

Answer:

Step-by-step explanation:

5x + 9x + 10x = $240

x = $10

Brian got 5x = $50

Tim got 9x = $90

Kenny got 10x = $100

The product in scientific notation is 1.36 x 10^22

The product expression is given as:

3.2 x 1012 and 4.25 x 109

Express the product, properly

3.2 x 10^12 x 4.25 x 10^9

Regroup the factors

3.2  x 4.25 x 10^12 x 10^9

Evaluate the product

13.6 x 10^21

Rewrite as:

1.36 x 10^22

Hence, the product in scientific notation is 1.36 x 10^22

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Answer:

c 1.36 x 1012

explanation:

For the Random variables, X and Y where both are nonnegative for all points in a sample space S. The expected value of Z ( random variable) is, E(Z) = E(X) + E(Y).

We have X and Y are random variables and that X and Y are non-negative for all points in a sample space S. Let us consider X be another random variable defined as Z(s) = max( X(s), Y(s))

for all elements s belongs to S. We have to show that E( Z) = E(X) + E(Y)

Now, for simple way of representation let

Max ( X(s),Y(s)) = Max(X,Y)

We know that Max(X,Y) = [(X+Y) + |X-Y|]

So, Z = Max(X,Y) = [(X+Y) + |X-Y|]

Taking expectations E(Z) = E(Max(X,Y)

= E{[(X+Y) + |X-Y|]}

\(E(Z)= \frac{1}{2} [E(X+Y) + E|X-Y|] = [E(X) + E(Y) + E|X-Y|] \\ \) (Since E(X + Y) = E(X)+ E(Y))

\(E(Z) = \frac{1}{2}[E(X)+ E(Y) + E|X| + E|-Y|]\\ \)

\(= \frac{1}{2} [E(X) + E(Y) + E(X) + E(Y)]\) (Since X and Y are non negative so E|X| = E(X) and E(-Y)=E(Y) )

=> E(Z) = E(X)+ E(Y)

Hence, required results occurred.

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Answer:

-20

Step-by-step explanation:

I belive )

you could check using the internet step by step

Write P(1 < Z < 2) as

P(1 < Z < 2) = P(0 < Z < 2) - P(0< Z < 1)

From the standard normal table,

P(0 < Z < 2) = 0.4772

and

P(0 < Z < 1) =0.3413

Then,

B) \(7 \frac{3}{10} \)

This is the only fraction that converts into 7.3 (location of point a).

Let me convert it for you

\(7 \frac{3}{10} \\ \\ \frac{73}{10} \\ \\ 7.3\)

The location of point A is 7.3

Answer:

20 percent

Step-by-step explanation:

20% of 50 is 10

Answer:

20%

Step-by-step explanation:

10/50 = .2 or 0.2

and then u multiply that by 100.

.2 X 100 = 20%

Hope that Helps! :)

The statement that described the triangle properties is that the segment YZ and segment Y"Z" should be proportional when the dilation is done and it should be congruent when the translation should be done.

Given that,

Based on the above information,

Therefore we can conclude that option d is correct.

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The probability of an event not occurring refers to the probability of all other possible outcomes except for the event in question.

The odds for rolling a 6-sided die and getting a 2 are 1:5 or 1/5. This means that the probability of rolling a 2 is 1/6, and the probability of not rolling a 2 is 5/6. To find the odds against rolling a 6-sided die and getting a 2, we simply invert the odds for rolling a 2, which gives us the odds of rolling any number other than 2. The odds against rolling a 6-sided die and getting a 2 are therefore 5:1 or 5/1. This means that the probability of not rolling a 2 is 5/6, and the probability of rolling a 2 is 1/6. It's important to note that the odds against an event are not the same as the probability of that event not occurring. The odds against an event refer to the ratio of the number of unfavorable outcomes to the number of favorable outcomes, while the probability of an event not occurring refers to the probability of all other possible outcomes except for the event in question.

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The derivative of H(z) is H'(z) = -2zd^2/[(d^2-z^2)(d^2+z^2)].

To differentiate the function H(z) = ln[(d^2-z^2)/(d^2+z^2)]^(1/2), we will use the chain rule and the power rule of differentiation.

First, we can simplify the expression inside the natural logarithm using the laws of exponents:

[(d^2-z^2)/(d^2+z^2)]^(1/2) = [(d^2-z^2)^(1/2)/(d^2+z^2)^(1/2)]

Now we can differentiate H(z) as follows:

H'(z) = d/dz [ln[(d^2-z^2)/(d^2+z^2)]^(1/2)]

= (1/2)[(d^2+z^2)^(1/2)/(d^2-z^2)^(1/2)] * d/dz [(d^2-z^2)/(d^2+z^2)]

Using the quotient rule, we can simplify the derivative:

d/dz [(d^2-z^2)/(d^2+z^2)] = [(2z)(d^2+z^2) - (d^2-z^2)(2z)]/(d^2+z^2)^2

= -4zd^2/(d^2+z^2)^2

Substituting this back into H'(z), we get:

H'(z) = (1/2)[(d^2+z^2)^(1/2)/(d^2-z^2)^(1/2)] * (-4zd^2/(d^2+z^2)^2)

= -2zd^2/[(d^2-z^2)(d^2+z^2)]

Therefore, the derivative of H(z) is:

H'(z) = -2zd^2/[(d^2-z^2)(d^2+z^2)]

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The common ratios of the sequence are 4 and 1/4

From the question, we have the following parameters that can be used in our computation:

Sequence 1

1, 2, 4, 8, 16,...

The common ratio is the quotient of a term and the previous term

Using the first term and the second term, we have

Common ratio = Second term/First term

Substitute the known values in the above equation, so, we have the following representation

Common ratio = 2/1

Evaluate

Common ratio = 2

Sequence 2

Here, we have

48, 12, 4, 2,...

The common ratio is the quotient of a term and the previous term

Using the first term and the second term, we have

Common ratio = Second term/First term

Substitute the known values in the above equation, so, we have the following representation

Common ratio = 12/48

Evaluate

Common ratio = 1/4

Hence, the common ratio is 1/4

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Step-by-step explanation:

(4^3)^5 = 4^(3×5) = 4^15 (option C)

So

Checking for approximate normality in the population is essential for constructing a valid confidence interval, particularly when dealing with small sample sizes. This ensures the accuracy and reliability of the interval in estimating the true population parameter.

It's important to check whether the population is approximately normal before constructing a confidence interval because the accuracy and validity of the interval depend on the underlying distribution of the population. Here's a step-by-step explanation:

1. A confidence interval is a range of values within which the true population parameter (e.g., mean or proportion) is likely to fall, with a certain level of confidence (e.g., 95% or 99%).

2. The process of constructing a confidence interval relies on the Central Limit Theorem, which states that, for large sample sizes, the sampling distribution of the sample mean will be approximately normal, regardless of the population distribution.

3. However, for small sample sizes, the distribution of the population needs to be approximately normal in order to obtain an accurate confidence interval. This is because the normality assumption is crucial for the proper interpretation of the interval.

4. If the population is not approximately normal, the confidence interval may not provide a reliable estimate of the true population parameter, leading to incorrect conclusions and potentially invalid results.

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