Find the lateral area of this square
based pyramid.
10 in
5 in
[ ? ] in

Answer:

[tex]2x^{3} +10[/tex]

Step-by-step explanation:

[tex]x*2x*x+10=2x^{3} +10[/tex]

slope is 3

y-intercept is 0,-5

The function described by the points in this table is nonlinear.

Based on the given points in the table, we can determine whether the function is linear or nonlinear by examining the relationship between the x and y values.

Let's look at the x and y values:

x y

-3 9

-1 1

0 0

1 1

3 9

If we observe that for every change in x, the corresponding change in y remains constant, then the function is linear. In other words, if the ratio of the change in y to the change in x is constant, the function is linear.

Let's calculate the ratios:

For x = -3 to x = -1:

Change in y = 1 - 9 = -8

Change in x = -1 - (-3) = 2

Ratio = -8/2 = -4

For x = -1 to x = 0:

Change in y = 0 - 1 = -1

Change in x = 0 - (-1) = 1

Ratio = -1/1 = -1

For x = 0 to x = 1:

Change in y = 1 - 0 = 1

Change in x = 1 - 0 = 1

Ratio = 1/1 = 1

For x = 1 to x = 3:

Change in y = 9 - 1 = 8

Change in x = 3 - 1 = 2

Ratio = 8/2 = 4

As we can see, the ratios are not constant. The ratio changes from -4 to -1, then to 1, and finally to 4. Therefore, the function described by the points in this table is nonlinear.

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Answer:

2

Step-by-step explanation:

The probability that exactly ten requests are received during a particular 2-hour period, with a rate of α = 4 requests per hour, is approximately 0.0194 or 1.94%.

Let's denote the random variable X as the number of requests received during a 2-hour period. Since the rate of requests per hour is α = 4, we can calculate the rate for a 2-hour period as λ = α × 2 = 4 × 2 = 8.

The probability mass function (PMF) of a Poisson distribution is given by the formula:

[tex]P(X = k) = (e^{-\lambda} \times \lambda ^k) / k![/tex]

where e is Euler's number (approximately 2.71828), λ is the average number of events (rate) during the given time period, and k is the number of events we are interested in.

In this case, we want to find the probability of exactly ten requests, so k = 10 and λ = 8. Plugging these values into the formula, we get:

P(X = 10) = (e⁻⁸ * 8¹⁰) / 10!

To calculate this probability, we need to evaluate the values of e⁻⁸, 8¹⁰, and 10!.

e⁻⁸ is approximately 0.0003354626 (rounded to 10 decimal places).

8¹⁰ is equal to 1,073,741,824.

10! (10 factorial) is equal to 10 × 9 × 8 × 7 × 6 × 5 × 4 × 3 × 2 × 1, which is 3,628,800.

Plugging these values back into the formula, we have:

P(X = 10) = (0.0003354626 * 1,073,741,824) / 3,628,800

Evaluating this expression gives us the probability that exactly ten requests are received during the two-hour period.

P(X = 10) ≈ 0.0194 or 1.94%.

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Answer:

V = 135π in3; S = 105π in2

Step-by-step explanation:

Answer:

a) The floor of the room, each edge and the top of the table.

b) The edge of one side and one leg of the table.

c) The angle formed between the sides of the table and the angle between the legs of the table and its edges.

d)  The vertices of the top of the table.

e) These are same lines.

Step-by-step explanation:

An angle is the amplitude between the two lines. Plane is an object which consists of two dimensions and infinite points. The segment is a fragmented line. A ray is a line which a starting point and a direction.

A) Tres planos que surgen a partir de la mesa de mi casa son la superficie de la mesa, la superficie del suelo sobre el cual se apoya la mesa, y la superficie de la pared sobre la cual reposa la mesa.

B) Dos rectas de planos distintos pueden ser el borde de la mesa, por una parte, y la pared, por el otro.

C) Dos ángulos de un plano y dos de otro son el vértice de la mesa y el ángulo formado entre el borde de la misma y un vaso, por un lado, y el ángulo formado por una baldosa y la pata de la mesa y el ángulo recto formado por las líneas de una baldosa, por la otra.

D) Dos rayas pueden ser la línea a ras del suelo y la línea a ras de la mesa.

E) Dos semirrectas pueden ser ambas patas de la mesa.

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The probability of getting exactly seven fours in ten rolls of a fair die is approximately 0.0574.

To determine the probability of exactly seven fours in 10 rolls of a fair die, we can use the binomial distribution formula:

P(X = k) = (nCk) * p^k * (1-p)^(n-k)

Where:

P(X = k) is the probability of getting exactly k successes (in this case, rolling a four) in n trials (in this case, rolling a die 10 times),

nCk is the number of combinations of n items taken k at a time,

p is the probability of success on a single trial (rolling a four), and

(1-p) is the probability of failure on a single trial (not rolling a four).

In this case, n = 10, k = 7, p = 1/6 (since there is a 1/6 chance of rolling a four on a fair die), and (1-p) = 5/6.

Plugging these values into the formula:

P(X = 7) = (10C7) * (1/6)^7 * (5/6)^(10-7)

Calculating the combinations:

(10C7) = 10! / (7! * (10-7)!) = 10! / (7! * 3!) = (10 * 9 * 8) / (3 * 2 * 1) = 120

Substituting the values:

P(X = 7) = 120 * (1/6)^7 * (5/6)^(10-7)

Calculating the probability:

P(X = 7) = 120 * (1/6)^7 * (5/6)^3 ≈ 0.0595

Therefore, the probability that exactly seven fours will appear in 10 rolls of a fair die is approximately 0.0595 (rounded to 4 decimal places).

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Answer:

A=2, B=10, C=-18

The answer is the first one.

Step-by-step explanation:

[tex]5x^{2} -3x^{2} +x+9x-18=0[/tex]

[tex]2x^{2} +10x-18=0[/tex]

Formula: [tex]f(x)=ax^{2} +bx+c[/tex]

Answer:

3

5

(

−

2

)

Step-by-step explanation:

Simplify then multiple the numbers

Answer:

4

Step-by-step explanation:

Answer:

4

Step-by-step explanation:

to me when you divide with a farction it already is divsion but when u use it in divson i make nubmer bigger (if it's the 2nd number ) so thats way 2÷1/2=4

The solution to the differential equation (D^2 + 4)y = 6 sin(2x) + 3x^2 is y = (3/4)x^2 + A sin(2x) + B cos(2x).

To solve the given differential equation (D^2 + 4)y = 6 sin(2x) + 3x^2, where D represents the derivative operator, we can use the method of undetermined coefficients.

y = y_h + y_p

y = A sin(2x) + B cos(2x) + (3/4)x^2

Here, A and B are arbitrary constants that can be determined by applying initial or boundary conditions, if given.

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Answer:

w = 8, y = 4.

Step-by-step explanation:

i think this is right i am not sure

Answer:

[tex]x = 8 \\ y = 4[/tex]

Step-by-step explanation:

Let x be the number of one point shots, and y the number of two point shots.

We have

[tex]x + y = 12 \\ y = 12 - x[/tex]

And

[tex]x + 2y = 16[/tex]

Substituting the first equation in we get

[tex]x + 2(12 - x) = 16 \\ x + 24 - 2x = 16 \\ - x = - 8 \\ x = 8[/tex]

Since

[tex]y = 12 - x \\ y = 12 - 8 = 4[/tex]

(a) The probability that X is less than 3, P(X < 3), is 0.

(b) The mean of X, denoted as E(X), is 71/24, which is approximately 2.9583 when rounded off to four decimal places.

(c) Given Y = e^X, the mean of Y, denoted as E(Y), is approximately 15.75 when rounded off to two decimal places.

(a) It is required to compute P(X<3). Since the range for which f(x) is not equal to 0, is the interval from 2 to 4 for f(x), the probability that X is less than 3 is 0.

Similarly, for X > 4, P(X > 4) = 0.

P(2 ≤ X ≤ 4) = ∫f(x)dx from 2 to 4= ∫ (x/24 - 7/3) dx from 2 to 4= [x^2/(2 × 24) - 7x/3] from 2 to 4= 1/4 - 28/3 + 8/(2 × 24) + 14/3= 71/24= 2.9583(rounded off to four decimal places)

(b) The mean of X can be computed as follows:

E(X) = ∫xf(x)dx from -∞ to ∞= ∫ (x/24 - 7/3) dx from 2 to 4= [x^2/(2 × 24) - 7x/3] from 2 to 4= 1/4 - 28/3 + 8/(2 × 24) + 14/3= 71/24= 2.9583(rounded off to four decimal places)

(c) Y = e^X

The mean of Y can be computed as follows:

E(Y) = E(e^X)= ∫ e^x f(x) dx from -∞ to ∞= ∫ e^x (x/24 - 7/3) dx from 2 to 4= [e^x (x - 31)/(24)] from 2 to 4= (e^4/6 - 31e^4/24 - e^2/6 + 31e^2/24) ≈ 15.75(rounded off to two decimal places).

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Answer:

Step-by-step explanation:

The expectation is 0.25.

Poisson distribution is a discrete distribution which is used to model events that occur in the specified interval of time. Parameter of Poisson distribution is [tex]\lambda[/tex], which describes the average number of events occurring in the given interval of time.

The given information is:

E(X) = In 2

X ~ Poi( [tex]\lambda[/tex] ) where  [tex]\lambda[/tex], = In 2

[tex]f(x)=\frac{e^-^\lambda\lambda^x}{x!}[/tex]

It is known that cos([tex]\pi x[/tex])[tex]=(-1)^x[/tex], for x = 1, 2, 3...

To calculate the value of the required expectation.

[tex]E(cos(\pi x))=\sum^\infty_x_=_0 (-1)^xf(x)\\\\E(cos(\pi x))=\sum^\infty_x_=_0(-1)^x\frac{e^-^\lambda(\lambda)^x}{x!}\\ \\E(cos(\pi x))=e^-^\lambda\sum^\infty_x_=_0\frac{(-\lambda)^x}{x!}[/tex]

Expansion of exponential function is as follows

[tex]e^a=\sum^\infty_x_=_0\frac{(a)^x}{x!}[/tex]

Therefore, further calculation can be done as

[tex]E(cos(\pi x))=e^-^\lambda \,e^-^\lambda\\\\E(cos(\pi x))=e^-^2^\lambda\\\\E(cos(\pi x))=e^-^2^(^I^n^ 2^)\\\\E(cos(\pi x))=e^(^I^n^ 2^)^2\\\\E(cos(\pi x))=\frac{1}{4}[/tex]

Therefore, the expectation is 0.25.

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The given question is incomplete, complete question is:

Let X be a Poisson random variable with E(X) =In 2. Calculate [tex]E[cos(\pi x)][/tex].

Answer:

Linear: The first and third one. (0,5) & (1,1)

Exponential: The second one (above). (-2, 1/16)

Quadratic function: The last one (below). (-3,35)

Step-by-step explanation:

The quotient of (2x^2 + 5x + 8) divided by (x + 2) is 2x + 1, and the remainder is 12.

To divide the polynomial[tex](2x^2 + 5x + 8) by (x + 2)[/tex] using synthetic division, we follow these steps:

1. Set up the synthetic division table by placing the divisor (x + 2) on the left side of the table and writing down the coefficients of the dividend (2x^2 + 5x + 8) in descending order on the top row of the table.

  | 2   5   8

-2 |

2. Bring down the first coefficient, which is 2, from the top row and write it underneath the horizontal line.

 | 2   5   8

-2 | 2

3. Multiply the divisor (-2) by the number beneath the line (2) and write the result in the next column.

  | 2   5   8

-2 | 2  -4

4. Add the result to the next coefficient in the top row and write the sum in the next column.

  | 2   5   8

-2 | 2  -4   4

5. Repeat steps 3 and 4 until all coefficients have been processed.

  | 2   5   8

-2 | 2  -4   4

    ___________

     2   1  12

The last number in the bottom row, 12, is the remainder. The other numbers in the bottom row represent the coefficients of the quotient.

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The error of rejecting the null hypothesis when it is actually true is known as a Type I error or alpha error. It represents the incorrect rejection of a null hypothesis that is true in reality.

Type I errors are associated with the significance level (alpha) chosen for a statistical test and occur when the test incorrectly concludes that there is a significant effect or relationship when there isn't one.

In hypothesis testing, the null hypothesis represents the assumption of no effect or no relationship between variables. The alternative hypothesis, on the other hand, suggests the presence of an effect or relationship. The significance level (alpha) is the threshold set by the researcher to determine the probability of rejecting the null hypothesis.

A Type I error occurs when the null hypothesis is true, but the statistical test incorrectly rejects it, leading to a false conclusion of a significant effect or relationship. This error is also known as a false positive. The probability of making a Type I error is denoted by alpha.

Type I errors are considered undesirable because they lead to incorrect conclusions and may result in wasted resources or inappropriate actions based on flawed evidence.

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The average of a sample of high daily temperature, the 90% confidence interval for the average temperature in the desert, based on the given sample data, is within a specific range.

To calculate the 90% confidence interval, we can use the formula:

Confidence Interval = Average ± (Critical Value) * (Standard Deviation / √Sample Size)

Since the sample size is 26 and we want a 90% confidence interval, we need to determine the critical value for a 90% confidence level. By referring to a t-distribution table or using statistical software, we can find that the critical value for a 90% confidence level with a sample size of 26 is approximately 1.708.

Substituting the values into the formula, we get:

Confidence Interval = 114 ± (1.708) * (5 / √26)

Calculating this expression, we obtain the confidence interval for the average temperature. The lower bound of the interval will be 113.36 degrees F, and the upper bound will be 114.64 degrees F. Therefore, we can state that we are 90% confident that the true average temperature in the desert falls within the range of 113.36 to 114.64 degrees F, based on the given sample data.

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The probability that the sample mean body temperature will be between 36.5° and 37.10° can be determined using the z-score and the standard normal distribution table.

First, we need to calculate the z-scores for both temperatures using the formula:

z = (x - μ) / (σ / √n)

where x is the sample mean, μ is the population mean, σ is the standard deviation, and n is the sample size.

For the lower temperature of 36.5°:

z1 = (36.5 - 36.8) / (0.62 / √19)

For the higher temperature of 37.10°:

z2 = (37.10 - 36.8) / (0.62 / √19)

Next, we look up the corresponding probabilities associated with these z-scores in the standard normal distribution table. Subtracting the probability of the lower z-score from the probability of the higher z-score will give us the probability of the sample mean body temperature falling between the two values.

Let's calculate the z-scores:

z1 = (36.5 - 36.8) / (0.62 / √19) ≈ -1.350

z2 = (37.10 - 36.8) / (0.62 / √19) ≈ 0.775

Now, we look up the probabilities associated with these z-scores in the standard normal distribution table. The probability corresponding to z1 is approximately 0.0885, and the probability corresponding to z2 is approximately 0.7794.

Finally, we subtract the lower probability from the higher probability:

P(36.5° ≤ sample mean ≤ 37.10°) = 0.7794 - 0.0885 ≈ 0.6909

Therefore, the probability that the sample mean body temperature will be between 36.5° and 37.10° for a sample size of 19 people is approximately 0.6909.

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Answer:

D). irrational numbers between 10 and 30

Answer:

A

Step-by-step explanation:

the y intercept (where x is 0) should be -3 because of y<3x-3

There are 30 of the cupcakes are vanilla.

Subtraction in mathematics means that is taking something away from a group or number of objects. When you subtract, what is left in the group becomes less.

We have to given that;

Joanne is making 48 cupcakes for a bake sale.

And, 1/4 of the cupcakes are chocolate.

1/8 of the cupcakes are strawberry.

The remainder of the cupcakes are vanilla.

Hence, We get;

Amount of the cupcakes are vanilla is,

⇒ 48 - (1/4 of 48 + 1/8 of 48)

⇒ 48- (12 + 6)

⇒ 48 - 18

⇒ 30

Thus, There are 30 the cupcakes are vanilla.

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[tex]\huge\text{Hey there!}[/tex]

[tex]\mathsf{(\dfrac{4}{9})^2}[/tex]

[tex]\mathsf{= \dfrac{4}{9}\times\dfrac{4}{9}}[/tex]

[tex]\mathsf{= \dfrac{4^2}{9^2}}[/tex]

[tex]\mathsf{\dfrac{4\times4}{9\times9}}[/tex]

[tex]\mathsf{4 \times 4 = \bold{16}\leftarrow \underline{Numerator}}[/tex]

[tex]\mathsf{9\times9 = \bf 81}\leftarrow\mathsf{\underline{Denominator}}[/tex]

[tex]\boxed{\boxed{\large\textsf{Answer: \boxed{{\bf \dfrac{16}{81}}}}}}\huge\checkmark[/tex]

[tex]\text{Good luck on your assignment and enjoy your day!}[/tex]

~[tex]\frak{Amphitrite1040:)}[/tex]

Answer: 17.29 cm

Step-by-step explanation:

Given

The dimension of a rectangular prism is [tex]13\ cm\times 9\times \ cm\times 7\ cm[/tex]

The longest line which can be drawn in the rectangular prism is diagonal across the body which is shown in the figure

Length of rectangular is given by

[tex]\Rightarrow L=\sqrt{l^2+b^2+h^2}[/tex]

Putting values

[tex]\Rightarrow L=\sqrt{13^2+9^2+7^2}\\\Rightarrow L\sqrt{169+81+49}=\sqrt{299}\\\Rightarrow L=17.29\ cm[/tex]

Answer:

17.3

Step-by-step explanation:

The dimension of a rectangular prism is 13x9x7

you would normally get 17.29 but  you have to round

which gives us the answer= 17.3

The conditions that are required to validate the use of t for the significance test would be:

D). l and ll only

"Regression Line" is described as the line that most adequately fits the provided data in order to display the efficacy of the model.

In the given situation, the I and II exemplify the conditions which will validate the process for the significance test.

The normal distribution, and among x and y and the independent response of y over x display that it suits the data successfully.

Thus, option D is the correct answer.

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Answer: Answer is THREE only.

Step-by-step explanation: Took the test. Also for the other guy's solution, he said one and two were REQUIRED. Make sure you read the question first ya'll. He still answered it.

Answer:

33.94 cms of ribbon

Step-by-step explanation:

Because you need two diagonals to form the x, therefore the amount  of ribbon needed is the sum of the distance of both diagonals.

When crossing the diagonal, a rectangular angle is formed, where the diagonal would be the hypotenuse, we know that the distance of the hypotenuse can be calculated by means of the legs, which we know its value (12):

d ^ 2 = a ^ 2 + b ^ 2

a = b = 12

d ^ 2 = 12 ^ 2 + 12 ^ 2

d ^ 2 = 288

d = 288 ^ (1/2)

d = 16.97

16.97 cm is what it measures, a diagonal, therefore tape is needed:

16.97 * 2 = 33.94

A total of 33.94 cms of ribbon is needed

Answer from jmonterrozar

a. In the picture we can see that the scatterplot is given for the data in the given table.

b. It is not linear as we can see from scatterplot.

c. The correlation between y and x is 0.

d. when r = 0 there is no relationship between x and y.

Given that,

The data is given in the table.

We know that,

a. We have to make a scatterplot of y versus x.

In the picture we can see that the scatterplot is given for the data in the given table.

b. We have to describe the relationship between y and x.

When x increases y increases upto certain point after that y start to decrease but x is increases only

Therefore, it is not linear as we can see from scatterplot.

c. We have to find the correlation between y and x.

The formula for the correlation coefficient is

r = [tex]\frac{n\times \sum XY-\sum X \times\sum Y}{\sqrt{[n\sum X^2 - (\sum X)^2][n\sum Y^2 - (\sum Y)^2]} }[/tex]

Now we find summation of all X, Y and XY, [tex]X^2[/tex] and [tex]Y^2[/tex]

X          Y           XY            [tex]X^2[/tex]            [tex]Y^2[/tex]

25        10         250         625          100

35        30        1050        1225         900

45        50        2250       2025        2500

55        30        1650        3025        900

65        10          650        4225        100

Now, ∑X = 225

∑Y = 130

∑XY = 5850

∑[tex]X^2[/tex] = 11125

∑[tex]Y^2[/tex] = 4500

Now, Substitute the values in the formula

r = [tex]\frac{5\times 5850-225 \times130}{\sqrt{[5\times 11125 - (225)^2][5\times 4500 - (130)^2]} }[/tex]

r = 0

Therefore, The correlation between y and x is 0.

d. We have to find what important point about correlation does this exercise illustrate.

Therefore, when r = 0 there is no relationship between x and y.

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