Solve for x and graph the solution on the number line below.
1≥-x-1 and -x-1≥ −13

Answer:

3

Step-by-step explanation:

Don't know how to explain it I just know that 27 has a perfect cube of 3.

Answer:

n = 9

Step-by-step explanation:

n3 = 27

n3/3 = 27/3

n = 9

The value of x for the given quadratic equation is (19+\(\sqrt{1261}\))/50,

(19-\(\sqrt{1261}\))/50.

It is in the form of a\(x^{2} +bx+c\). It is simply an equation and we have to solve for x.

If we solve the given equation we will be able to get the following equation

\(25x^{2} -19x-9=0\)

x=(-b+-\(\sqrt{b^{2}-4ac }\))/2a

when we put b=19 a =25 c =-9

we will get x=\((19+\sqrt{1261} )/50 , (19-\sqrt{1261} )/50\).

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Answer:

Other whole numbers that can be raised to a power to get 4,096 are  4, 8, 16 and 64

Step-by-step explanation:

Given;

2¹² = 4096

Other whole numbers that can be raised to a power to get 4,096 are obtained as follows;

\(if \ (a^x)^y = a^{xy}\\\\ (2^2)^6 = 4,096\\\\(4)^6 = 4,096\\\\Thus, \ the \ first \ whole \ number \ is \ 4\\\\(2^3)^4 = 4,096\\\\(8)^4 = 4,096\\\\Thus, \ the \ second \ whole \ number \ is \ 8\\\\(2^4)^3 = 4,096\\\\(16)^3 = 4,096\\\\Thus, \ the \ third \ whole \ number \ is \ 16\\\\(2^6)^2 = 4,096\\\\(64)^2 = 4,096\\\\Thus, \ the \ fourth \ whole \ number \ is \ 64\)

Therefore, Other whole numbers that can be raised to a power to get 4,096 are  4, 8, 16 and 64

Answer:

For the first triangle the missing sides are 7 and 7√2 For the second triangle,the missing sides are 13√3 and 13

Step-by-step explanation:

For the first triangle,

cos(45°)=7/hypotenuse

hypotenuse×cos45=7

hypotenuse×√2/2=7

hypotenuse=14/√2=7√2

We can now find the adjacent side using Pythagorean theorem,

√(7√2)²-7²=7

For the second triangle,

cos(30°)=adjacent/hypotenuse

but cos 30=√3/2

√3/2=adjacent/26(cross multiply and simplify)

26√3/2=13√3

To find the opposite length,

√(26)²-(13√3)²=13

The best estimate of the solution to the system of equations will be (1, 4). Then the correct option is C.

The allocation of weights to the important variables that produce the calculation's optimum is referred to as a direct consequence.

The system of the equations is given below.

2x + 3y = 12            ...1

4x + 2y = 10           ...2

Divide the equation 2 by 2, then we have

2x + y = 5            ...3

Subtract equation 3 from equation 2, then we have

2x + 3y - 2x - y = 12 - 5

2y = 7

y = 3.5

y ≈ 4

Then the value of 'x' is calculated as,

2x + 3.5 = 5

2x = 1.5

x = 0.75

x ≈ 1

The best gauge of the answer for the arrangement of conditions will be (1, 4). Then, at that point, the right choice is C.

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Answer:

x = 48

Step-by-step explanation:

Multiply both sides by 6

x = 6 * 8

x = 48

Check:

48/6 = 8

8 = 8

Answer:

\( \frac{x}{6} = 8 \\ \\ x = 8 \times 6 \\ \\ x = 48\)

The probability of winning on the fourth ticket is 0.83%.

Given, The probability of winning based on the type of lottery tickets we purchase is 0.05 or 1 in 20.

This means that the probability of winning is 1/20=0.05.We will play each Saturday until we win.

This statement gives us a hint that we need to find the probability of winning after four attempts/tries

Let the probability of not winning be (1-0.05)=0.95.

Now, the probability of not winning after 4 tries is:P(N) = 0.95 x 0.95 x 0.95 x 0.95 = 0.8145

The probability of winning on the fourth ticket is equal to the probability of not winning in three tickets (0.8145) multiplied by the probability of winning on the fourth ticket (0.05).

Thus, the probability of winning on the fourth ticket is:0.8145 x 0.05 = 0.040725 or 0.04

Summary: The probability of winning based on the type of lottery tickets we purchase is 0.05 or 1 in 20. We will play each Saturday until we win. The probability of winning on the fourth ticket is 0.83%.

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After solving the system of equations using Gaussian elimination we get the values as x = 5 , y = -11 and z=3

Given we have the system of equations as follows:

2x - y + 4z = 33

x + 2y - 3z = -26

-5 x - 3y +5z = 23

Rewrite the system in matrix form and solve it by Gaussian elimination.

[ 2  -1  4     [ 33

 1  2  -3   =  -26

-5  -3  5 ]      23 ]

Now divide row 1 by row 2.

[ 1  -0.5  2        [ 16.5

 1     2   -3    =  -26

-5    -3  5 ]         23 ]

Now R₂ - 1R₁ → R₂

and R₃ + 5R₁ → R₃

[ 1  -0.5  2        [ 16.5

 0   2.5  -5    =  -42.5

 0  -5.5 15 ]       105.5 ]

Divide row 2 by 2.5.

[ 1  -0.5  2        [ 16.5

 0     1   -2    =  -17

 0  -5.5 15 ]       105.5]

R₁+0.5R₂ → R₁

R₃ + 5.5R₂ → R₃

[ 1   0  1          [ 8

 0   1   -2    =  -17

 0    0   4 ]        12 ]

Divide R₃ by 4

[ 1   0  1          [ 8

 0   1   -2    =  -17

 0    0   1 ]         3 ]

Therefore, R₁-1R₃→R₁

R₂ + 2R₃ → R₂

[ 1   0  1          [ 5

 0   1   0    =    -11

 0    0   1 ]        3 ]

therefore x = 5, y=-11 and z = 3.

Hence we solved the system of equations using Gaussian elimination.

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Yes, its true that the questionnaire is very carefully constructed by an individual to provide the measurement instrument.  

A questionnaire is a studies device which includes a sequence of questions for the motive of amassing facts from respondents. Questionnaires may be concept of as a form of written interview. A questionnaire is a listing of questions or gadgets used to collect facts from respondents approximately their attitudes, experiences, or opinions.

Questionnaires may be used to acquire quantitative and/or qualitative facts. Questionnaires are generally utilized in marketplace studies in addition to withinside the social and fitness sciences. Questionnaires are typically taken into consideration to be excessive in reliability. This is due to the fact it's miles feasible to invite a uniform set of questions. Any troubles withinside the layout of the survey may be ironed out after a pilot study. The greater closed questions used, the greater dependable the studies.

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In mathematics, the place value chart is a tool that helps students understand the value of digits in a number. It is a visual representation of how digits are grouped and arranged to represent numbers. The place value chart is arranged in columns, with each column representing a different place value.

The place value chart starts with the ones place, also called units place. This is the rightmost column and it represents the ones digit in a number. The next column is the tens place, which represents the tens digit in a number. The hundredth place represents the hundreds digit and so on. Each column is ten times larger than the previous one.

A place value chart can be used to understand the value of a digit in a number.

Place value chart also helps to understand decimal numbers, which are numbers that have a decimal point. The decimal point separates the whole numbers from the fractional numbers. Each place to the right of the decimal point represents a smaller value.

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The trigonometric identity that is true is:

sin G = cos I. Option D

First, we need to know that;

One acute angle in a right triangle has a sine value equal to the cosine value of the other acute angle.

From the information given, we have;

In a right scalene triangle GHI, where both angle G and angle I are acute, the value of sin G is equivalent to cos I.

Several alternatives, including sin G = sin I, cos G = cos I, tan G = tan I, sin G = tan I, sin G being the inverse of cos I, and cos G being the inverse of cos I, are invalid for a right scalene triangle with a known right angle.

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The probability that the sample mean is more than 105 is 0.0384. The probability that the sample mean is less than 95 is 0.0384. The probability that the sample mean is between 95 and 105 is 0.9232.

The probability that the sample mean is more than 105 can be calculated using the following formula: P(X > 105) = P(Z > (105 - 100) / (20 / √50))

where:X is the sample mean

Z is the z-score

100 is the population mean

20 is the population standard deviation

50 is the sample size

Substituting these values into the formula, we get: P(X > 105) = P(Z > 1.77)

The z-table shows that the probability of a z-score greater than 1.77 is 0.0384. Therefore, the probability that the sample mean is more than 105 is 0.0384.

The probability that the sample mean is less than 95 can be calculated using the following formula: P(X < 95) = P(Z < (95 - 100) / (20 / √50))

Substituting these values into the formula, we get: P(X < 95) = P(Z < -1.77)

The z-table shows that the probability of a z-score less than -1.77 is 0.0384. Therefore, the probability that the sample mean is less than 95 is 0.0384.

The probability that the sample mean is between 95 and 105 can be calculated using the following formula: P(95 < X < 105) = P(Z < (105 - 100) / (20 / √50)) - P(Z < (95 - 100) / (20 / √50))

Substituting these values into the formula, we get: P(95 < X < 105) = P(Z < 1.77) - P(Z < -1.77)

The z-table shows that the probability of a z-score between 1.77 and -1.77 is 0.9232. Therefore, the probability that the sample mean is between 95 and 105 is 0.9232.

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Answer:

12

Step-by-step explanation:

Answer:

the value of x is 0.1

Step-by-step explanation:

i hope this helped

have a good day

The degrees of freedom are (number of rows - 1) * (number of columns - 1) = 1 * 1 = 1. The critical value for a chi-square distribution with 1 degree of freedom and a significance level of 0.05 is 3.84.

What is rectangle?

A rectangle is a geometric shape that has four sides and four right angles (90 degrees) with opposite sides being parallel and equal in length.

To determine if the difference in hemorrhaging rates between the ancrod and placebo groups is statistically significant, we can perform a chi-square test. The null hypothesis is that there is no difference in hemorrhaging rates between the two groups, and the alternative hypothesis is that there is a difference.

First, we need to calculate the expected values for each cell under the null hypothesis. We can do this by multiplying the row and column totals for each cell and dividing by the total sample size:

Expected value for Hemorrhage/Ancrod cell = (13+235) * (13+5) / (13+5+235+247) = 118.2

Expected value for No Hemorrhage/Ancrod cell = (13+235) * (235+247) / (13+5+235+247) = 129.8

Expected value for Hemorrhage/Placebo cell = (5+247) * (13+5) / (13+5+235+247) = 9.8

Expected value for No Hemorrhage/Placebo cell = (5+247) * (235+247) / (13+5+235+247) = 242.2

Therefore, we need to determine the degrees of freedom and the critical value of the chi-square distribution for a significance level of 0.05. The degrees of freedom are (number of rows - 1) * (number of columns - 1) = 1 * 1 = 1. The critical value for a chi-square distribution with 1 degree of freedom and a significance level of 0.05 is 3.84.

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The chi-square value (3.745) is slightly less than the critical value (3.841), we fail to reject the null hypothesis and there is no statistically significant difference in hemorrhaging rates between the ancrod and placebo groups at the 0.05 significance level.

To determine whether the difference in hemorrhaging rates is statistically significant using a chi-square test, first set up the contingency table based on the given data:

|            | Ancrod | Placebo | Total |
|------------|--------|---------|-------|
| Hemorrhage |   13   |    5    |   18  |
| No Hemorrhage |  235  |   247   |  482  |
| Total      |  248   |   252   |  500  |

Next, calculate the expected frequencies for each cell:

E11 = (18 * 248) / 500 = 8.976
E12 = (18 * 252) / 500 = 9.024
E21 = (482 * 248) / 500 = 239.024
E22 = (482 * 252) / 500 = 242.976

Now, apply the chi-square formula:

χ² = Σ[(O - E)² / E] = (13 - 8.976)² / 8.976 + (5 - 9.024)² / 9.024 + (235 - 239.024)² / 239.024 + (247 - 242.976)² / 242.976 = 1.808 + 1.803 + 0.068 + 0.066 = 3.745

With 1 degree of freedom (df = (2-1)(2-1)), the critical value for a non-directional alternative hypothesis and α = 0.05 is 3.841 (from the chi-square distribution table).

Since the calculated chi-square value (3.745) is slightly less than the critical value (3.841), we fail to reject the null hypothesis. Therefore, there is no statistically significant difference in hemorrhaging rates between the ancrod and placebo groups at the 0.05 significance level.

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If Mr. Johnson orders gravel to cover his driveway, below is a top view of the driveway and the gravel will be spread 3 inches deep, then the depth of the gravel in feet is 0.25 feet

The gravel will be spread 3 inches deep

Here we have to convert the depth in inches to the depth in feet

To convert the inches to feet, we have to divide the inches by 12.

Then,

3 inches = 3/12 feet

= 0.25 feet

Hence, if Mr. Johnson orders gravel to cover his driveway, below is a top view of the driveway and the gravel will be spread 3 inches deep, then the depth of the gravel in feet is 0.25 feet

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The probability that the mean monitor life  would be greater than 91.4 months is 0.8666.

We have mean life as 93 months, and standard deviation as 9 months.

We need to check mean monitor life  will be greater than 91.4 months in the sample.

It means that on left side mean range is=93-91.4=1.8,and

right side mean range =93+91.4=184.4

So, we need to find the probability if mean range varies in between from 1.8 to 184.4.

So, we use z-score table to find the z-score for 1.8 and 184.4,we get

We use Z-formula which is given by

Z = (X-μ)/SE

where X is the standard mean.

Using z-score table, we get

Z = 0.16917 and -0.161917

Using z-score table, we get that P(0.16917)=0.4333.

Since, both of the probability occupies same space area, due to that total probability =0.4333×2=0.8666

Hence, the probability will be 0.8666.

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To calculate the covariance and correlation coefficient of U and V, we need to first find the expected value and variance of U and V.

The covariance of two variables is a gauge of their relationship. In other words, it is a measure of how much the values of two variables tend to fluctuate together. Positive covariance shows that the values of the two variables tend to rise or decrease together, whereas negative covariance indicates that the values of one variable tend to increase when the values of the other variable drop. In probability theory and statistics, covariance is frequently employed to determine the association between two variables. It is determined by multiplying the variances of the two variables from their respective means and dividing the result by the total number of observations. This metric can be helpful for seeing trends and patterns in data and aiding analysts in forecasting.

How to solve?

The expected value of U is $E[U] = E[2 - X_1 - 2X_2] = 2 - m - 2m = -2m. Similarly, the expected value of V is $E[V] = E[3 + 3X_2 - X_3] = 3 + 3m - m = 4m.

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To calculate the value of covariance and correlation coefficient of U and V, we have to find their expected value along with variance.

A measure of the link between two random variables and how much they fluctuate together is called covariance. Alternately, we may say that it establishes the relationship between the two variables' changes, i.e., that a change in one variable is equivalent to a change in the other.

When one variable changes, covariance shows the link between the other two variables. Both variables are said to have positive covariance if a rise in one causes an increase in the other. Reduced values of one variable also result in reduced values of the other.

for expected value of U ;

= $E[U]

= E[2 - X_1 - 2X_2]

= 2 - m - 2m = -2m.

Similarly, the expected value of V;

= $E[V]

= E[3 + 3X_2 - X_3]

= 3 + 3m - m

= 4m.

now we can easily calculate the covariance and correlation coefficient of U,V.

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Ii is the estimated value of the integral at the ith iteration, and I is the overall estimated value of the integral. We can stop the algorithm when the standard deviation σ is less than 0.01.

The standard deviation (SD, also written as the Greek symbol sigma or the Latin letter s) is a statistic that is used to express how much a group of data values vary from one another.

To estimate the integral I = ∫[1 to 0] \(e^{(x^2)\) dx using Monte Carlo simulation, we can use the following algorithm:

To stop when the standard deviation of the estimator is less than 0.01, we can keep track of the estimated value of the integral and the number of points generated at each iteration of the algorithm. We can compute the standard deviation of the estimator using the formula:

σ = √((1/N) * Σ[i=1 to N] (Ii - I)²)

where N is the number of iterations, Ii is the estimated value of the integral at the ith iteration, and I is the overall estimated value of the integral. We can stop the algorithm when the standard deviation σ is less than 0.01.

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Answer:

Step-by-step explanation:

The GCF of 8 and 9 is 1

Divide both terms by the GCF, 1:

8 ÷ 1 = 8

9 ÷ 1 = 9

The ratio 8 : 9 cannot be reduced further by dividing both terms by the GCF = 1 :

This ratio is already in lowest terms.

Therefore:

8 : 9 = 8 : 9

There are 7200 ways for the senate committee to sit around a circular table.

To solve this problem, we can use the formula for circular permutations: (n-1)!/d, where n is the total number of people and d is the number of ways in which they can be distinguished. In this case, n is 11 (5 democrats + 5 republicans + 1 independent) and d is 1 (since all the members of each party sit together, they are not distinguishable from one another). Plugging these values into the formula, we get

This means that there are 7200 ways for the senate committee to sit around a circular table.

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Answer:

4

Step-by-step explanation:

Answer:

-1/2 or \(-\frac{1}{2}\)

Step-by-step explanation:

to find the slope, use the formula

(y₁ - y₂)/(x₁ - x₂)

(2 - -3)/(-4 - 6)

(2 + 3)/(- 4 - 6)

5/-10

1/-2

-1/2

Assuming that a randomly selected subject is given a bone density test, the test scores are normally distributed with a mean score of 85 and a standard deviation of 12.

This means that 68% of subjects have bone density test scores within one standard deviation of the mean, which is between 73 and 97.

The probability of randomly selecting a subject with a bone density test score less than 60 is 0.0062 or 0.62%.

Given: Mean = 85

Standard Deviation = 12

Using the standard normal distribution table, we find that the probability of z being less than -2.08 is 0.0188.

Therefore, the probability of a randomly selected subject being given a bone density test, with a score less than 60 is 0.0188 or 1.88%.

Summary: The given problem is related to the probability of a randomly selected subject being given a bone density test with a score less than 60. Here, we have used the standard normal distribution table to calculate the probability. The calculated probability is 0.0188 or 1.88%.

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Answer:

x~11

Step-by-step explanation:

22:17=14:x

22/17=14/x

22x=17*14

22x=238

22x/22=238/22

x=238/22

x=10.818181818181818

x~11