find the value of X, round to the nearest 10th

Answer:

$2,725

Step-by-step explanation:

The maximum number of days is 7.

The cost per days is $375.

The cost for 7 days is 7 * $375 = $2,625.

The owner applies a $100 fee for cleaning which must be added to the cost of the days.

$2,625 + $100 = $2,725

The greatest value for the range is the greatest cost there can be which is $2,725.

a) The proportion of male Internet users who use social networking is approximately 0.6747, and the proportion of female Internet users who use social networking is approximately 0.7358.

b) The difference in proportions is approximately -0.0611.

c) The standard error of the difference is approximately 0.0181.

d) The 95% confidence interval for the difference between these proportions is (-0.096, -0.026).

To calculate the standard error of the difference and find a 95% confidence interval for the difference between the proportions, we can use the formulas for proportions and their differences.

Let [tex]p_1[/tex] be the proportion of male Internet users who use social networking, and [tex]p_2[/tex] be the proportion of female Internet users who use social networking.

a) Proportion for male Internet users: [tex]p_1[/tex] = 517/766 = 0.6747

Proportion for female Internet users: [tex]p_2[/tex] = 692/941 = 0.7358

b) Difference in proportions: [tex]p_1 - p_2[/tex] = 0.6747 - 0.7358 = -0.0611

c) The standard error of the difference (SE) can be calculated using the formula:

[tex]SE = \sqrt{(p_1(1-p_1)/n_1) + (p_2(1-p_2)/n_2)}[/tex]

Where [tex]n_1[/tex] and [tex]n_2[/tex] are the sample sizes for male and female Internet users, respectively.

For male Internet users: [tex]n_1[/tex] = 766

For female Internet users: [tex]n_2[/tex] = 941

Plugging in the values, we have:

[tex]SE = \sqrt{(0.6747(1-0.6747)/766) + (0.7358(1-0.7358)/941)}[/tex]

d) To find the 95% confidence interval for the difference between these proportions, we can use the formula:

[tex]CI = (p_1 - p_2) \± (Z * SE)[/tex]

Where Z is the critical value corresponding to a 95% confidence level. For a large sample size, Z is approximately 1.96.

CI = (-0.0611) ± (1.96 * SE)

CI = -0.0611 ± 0.0355

CI = (-0.096, -0.026)

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Answer:

1.202

Step-by-step explanation:

Answer:

V = 135π in3; S = 105π in2

Step-by-step explanation:

Answer:

The difference between the absolute values of these two temperatures is 19°F.

Step-by-step explanation:

|-13| = 13

|6| = 6

13 + 6 = 19°F

Answer:

19

Explanation:

an absolute value is the value of a number without considering its sign.

thus, we can calculate the difference as such:

6 - (- 13) = 6 + 13 = 19

the difference between the absolute values of these two temperatures is 19.

i hope this helps! :D

To verify that a matrix A satisfies the conditions A € M2x2(R), A = [a b; c d], and det(A) = 0, we can use the formula for the determinant of a 2x2 matrix:

det(A) = ad - bc

In this case, since det(A) = 0, we have:

ad - bc = 0

This formula allows us to check whether a given matrix satisfies the given conditions.

To find three matrices A when a = 5 and det(A) = 27, we can use the formula:

ad - bc = 27

Let's assume b = 1, c = 0, and d = 27/a.

Substituting these values into the formula, we get:

5 * (27/a) - 1 * 0 = 27

135/a = 27

a = 135/27

a = 5

Therefore, one possible matrix A that satisfies the conditions is:

A = [5 1; 0 27/5]

Similarly, we can find two more matrices by choosing different values for b, c, and d, as long as the determinant condition is satisfied.

Now, let's suppose B is a matrix such that det(B) = det(A):

B = [p q; r s]

To show that det(B) = det(A), we can equate their determinants:

det(B) = det(A)

ps - qr = ad - bc

Since we already know that ad - bc = 0, we can conclude that:

ps - qr = 0

This equation shows that the determinant of B is also zero, satisfying the condition det(B) = 0.

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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.

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:

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

Answer:

am not sure but

Step-by-step explanation:

since they are similar they must have similar ratio

so 12/4 =3/1

so 3:1

4*3=12

for other sides I think

9*3 =27

and

6*3=18

y=27

x=18

what? bro I am confused is this a question?

The length M is 12

The measure of the angle BEC is 102

The measure of the arc AB is 128

The length PQ is 18.3

The length M can be calculated using

M² = 8 * (8 + 10)

So, we have

M² = 144

Take the square roots

M = 12

The measure of the angle BEC can be calculated using

BEC = 1/2 * (BC + AD)

So, we have

BEC = 1/2 * (156 + 48)

Evaluate

BEC = 102

The measure of the arc ABcan be calculated using

AB = 180 - 2 * BC

So, we have

AB = 180 - 2 * 26

Evaluate

AB = 128

The length PQ can be calculated using

x² = (12 + 8)² - 8²

So, we have

x² = 336

Take the square roots

x = 18.3

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By applying the the FOIL method, which stands for First, Outer, Inner, Last  we obtained the result -84 + 80i for (4 + 10i)^2.

To calculate (4 + 10i)^2, we can:

First, we multiply the first terms of each binomial:

(4 + 10i) * (4 + 10i) = 16 + 40i

Next, we multiply the outer terms of each binomial:

(4 + 10i) * (4 + 10i) = 16 + 40i

Then, we multiply the inner terms of each binomial:

(4 + 10i) * (4 + 10i) = 16 + 40i

Finally, we multiply the last terms of each binomial:

(4 + 10i) * (4 + 10i) = 100i^2

We know that i^2 is equal to -1, so we can substitute that in:

100(-1) = -100

Putting it all together, we get:

(4 + 10i)^2 = 16 + 40i + 40i + (-100)

= -84+80i

Therefore, by applying this method for squaring a complex number, we obtained the result -84 + 80i for (4 + 10i)^2.

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To determine the standard error of the estimated slope coefficient and its statistical significance, more information is needed, such as the t-statistic or the p-value associated with the estimated slope coefficient. The options provided do not include the necessary details to make a conclusion.

The standard error of the estimated slope coefficient measures the precision or variability of the estimated coefficient. It provides information about how much the estimated slope coefficient could vary across different samples.

The t-statistic and the p-value, on the other hand, are used to assess the statistical significance of the estimated slope coefficient. The t-statistic measures the number of standard errors the estimated coefficient is away from zero, while the p-value indicates the probability of observing a coefficient as extreme as the estimated one under the null hypothesis that the true coefficient is zero.

Without the t-statistic or p-value, it is not possible to determine the statistical significance of the estimated slope coefficient at the 5% level.

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(a) There are 840 distinguishable permutations of the letters in the word "initial." (b) There are 180 distinguishable permutations of the letters in the word "Hawaii." (c) There are 420 distinguishable permutations of the letters in the word "decreed."

(a) For the word "initial," we have a total of 7 letters, with 2 "I"s, and 1 occurrence of each of the remaining letters. Applying the formula, we get:

n! / (3!1!1!1!1!) = 7! / (3!1!1!1!1!) = (7 × 6 × 5 × 4 × 3 × 2 × 1) / (3 × 2 × 1 ×1 × 1 × 1 × 1) = 840

(b) For the word "Hawaii," we have a total of 6 letters, with 1 "H," 2 "A"s, and 2 "I"s. Applying the formula, we get:

n! / (1!2!1!2!) = 6! / (1!2!1!2!) = (6 × 5 × 4 × 3 × 2 × 1) / (1 × 2 × 1 × 2 × 1 × 1) = 180

(c) For the word "decreed," we have a total of 7 letters, with 2 "E"s, 3 "D"s, and 1 occurrence of each of the remaining letters. Applying the formula, we get:

n! / (2!3!1!1!) = 7! / (2!3!1!1!) = (7 × 6 × 5 × 4 × 3 × 2 × 1) / (2 × 1 × 3 × 2 × 1 × 1 × 1) = 420

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Answer:

The equation of the line that passes through the given points is ;

7y = -x + 12

Step-by-step explanation:

Here, we want to get the equation of the line that passes through the given points

The general equation form

is;

y = mx + b

where m is the slope and b is the y-intercept

Now, let us substitute the x and y coordinate values of each of the points;

for (-2,2); we have

2 = -2m + b

b = 2m + 2 •••••(i)

for F;

1 = 5m + b

b = 1-5m ••••••(ii)

Equate both b

1-5m = 2m + 2

1-2 = 2m + 5m

7m = -1

m = -1/7

Recall;

b = 2m + 2

b = 2(-1/7) + 2

b = -2/7 + 2

b = (-2 + 14)/7 = 12/7

The equation of the line is thus;

y = -1/7x + 12/7

Multiply through by 7

7y = -x + 12

Answer:

14

Step-by-step explanation:

separate the figure into two  shapes. On the little one is 2x1 which the answer is 2 then on the larger shape is 6x2 which is 12 then you add 12+2 and then you get your answer

a) The probability of finding   a meter stick with a length of more than 100.04cm is 0.44013.

b) The probability of finding a group of 42 meter sticks with a mean length of less than 99.82 cm is 0.65866.

c) The probability of finding a group of 50 meter sticks with a mean length of more than 99.87 cm is 0.44013.

d) The probability of finding   a group of 28 meter sticks with a mean length of between 99.82and 99.86 cm is 0.11974.

e) The mean length that would be at the 92nd percentile for a random sample of 32 meter sticks is 99.89714 cm.

a) The probability of finding a meter stick   with a length of more than 100.04cm is

P(X >   100.04 ) =1 - P(X <= 100.04)

= 1- Φ((100.04   - 99.84) / 0.2)

= 1 - Φ(0.12)

= 1 - 0.55987

= 0.44013

b) The probability of finding a group of 42 meter sticks with a mean length of less than 99.82 cm is

P(¯X < 99.82) = 1 - P(X >= 99.82)

= 1 - Φ((99.82 - 99.84) / 0.2 / √42)

= 1 - Φ(-0.1)

= 1 - 0.34134

= 0.65866

c) The probability of finding a group of 50 meter sticks with a mean length of more than 99.87 cm is

P(X > 99.87) = 1 - P(X <= 99.87)

= 1 - Φ((99.87 - 99.84) / 0.2 / √50)

= 1 - Φ(0.15)

= 0.44013

d) The   probability of finding a group of 28 meter sticks with a mean length of between 99.82 and 99.86 cm    is

P(99.82 < X  < 99.86) = Φ  ((99.86 - 99.84)/ 0.2 / √28) - Φ((99.82 - 99.84) / 0.2/ √28)

= Φ(0.15) - Φ(0.12)

= 0.55987 - 0.44013

= 0.11974

e) The mean length that would be at the 92nd percentile for a random sample of 32-meter sticks is

X₉₂ = μ + z₉₂ σ / √n

= 99.84 + z₉₂ (0.2) / √32

= 99.84 + 1.85 (0.2) / √32

= 99.84 + 0.05714

= 99.89714

Therefore, the mean length that would be at the 92nd percentile for a random sample of 32 meter sticks is 99.89714 cm.

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Answer:

31 degrees

Step-by-step explanation:

1. since angle x and angle y are congruent, and segment xw and segment yw are congruent, you can assume that angle xzw and angle wzy are also congruent.

2. set angle xzw and angle wzy equal to each other

8x-1 = 5x+11

3. combine like terms

3x = 12

4. simplify to find the value of x

x = 4

5. plug x into the equation to find the degree of angle wzy

5(4)+11

20+11

=31 degrees

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]

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:

Answer:

James will spend $119.94

Step-by-step explanation:

Multiply $19.99 by 6.

$19.99 x 6 = $119.94

Answer:

(x,y) = (-1,3)

Step-by-step explanation:

hope this helps!

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 general solution to the given differential equation, (x³+ ye^xy) dx + (xe^xy-sin3y) = 0, involves two steps: identifying an integrating factor and then integrating the resulting equation. The integrating factor is found to be e^(3xy).  We find F(x, y) = ∫(e^(x^4/4 + ye^xy) (x³+ ye^xy)) dx + g(y),

To solve the given differential equation, we first determine an integrating factor. Since the coefficient of dx, x³ + ye^xy, is a function of x and y only, we can identify the integrating factor as e^(∫(x³ + ye^xy) dx). Evaluating the integral, we obtain e^(x^4/4 + y∫e^xy dx). Simplifying further, the integrating factor is found to be e^(x^4/4 + ye^xy).

Next, we multiply the entire differential equation by this integrating factor. This step transforms the equation into an exact differential equation, which is easier to solve. Multiplying through, we have e^(x^4/4 + ye^xy) (x³+ ye^xy) dx + e^(x^4/4 + ye^xy) (xe^xy-sin3y) = 0.

After multiplying, we can observe that the left-hand side of the equation is now the total derivative of a function F(x, y). By integrating with respect to x, we find F(x, y) = ∫(e^(x^4/4 + ye^xy) (x³+ ye^xy)) dx + g(y), where g(y) is the constant of integration with respect to x. Finally, the general solution is obtained by solving for y in terms of x and the constant g(y).

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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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