Choose the correct way to write a comparison of seven-twelfths and ten-twelfths.

Answer:

\(\large\boxed{ \sf Area = 25\ ft .^2}\)

Step-by-step explanation:

We need to find out the area of the triangle which has a base of 12.5ft and s height of 4ft.

We know that the formula for calculating the area of the triangle is ,

\(\sf:\implies \pink{Area_{\triangle}=\dfrac{1}{2}\times (b)\times (h)}\\\)

where,

F I G U R E : -

\( \setlength{\unitlength}{1cm}\begin{picture}(6,5)\linethickness{.4mm}\put(1,1){\line(1,0){4.5}}\put(1,1){\line(0,1){3.5}}\qbezier(1,4.5)(1,4.5)(5.5,1)\put(.3,2.5){$\large\bf 4\ ft $}\put(2.8,.3){$\large\bf 12.5\ ft$}\put(1.02,1.02){\framebox(0.3,0.3)}\put(.7,4.8){\large\bf A}\put(.8,.3){\large\bf B}\put(5.8,.3){\large\bf C}\qbezier(4.5,1)(4.3,1.25)(4.6,1.7)\end{picture}\)

Now on substituting the respective values, we have;

\(\sf:\implies Area = \dfrac{1}{2}\times (12.5) \times (4) \ ft.^2 \\\)

Simplify,

\(\sf:\implies \underline{\underline{\boxed{\sf Area = \frak{25\ ft.^2} }}} \\\)

Hence the area of the triangle is 25ft.²

The probability of the interval -1.62 < z < 2.01 in a standard normal distribution is approximately 0.9262 or 92.62%.

In a standard normal distribution, the mean is 0 and the standard deviation is 1. The z-score represents the number of standard deviations a data point is from the mean. To find the probability of a specific interval, we calculate the area under the curve between the corresponding z-values.

Given the interval -1.62 < z < 2.01, we need to find the area under the standard normal curve between these two z-values. This can be done using a standard normal distribution table or by using a statistical software or calculator.

By looking up the z-values in the table or using software, we find the corresponding probabilities: P(z < -1.62) = 0.0526 and P(z < 2.01) = 0.9788.

To find the probability of the interval -1.62 < z < 2.01, we subtract the probability of the lower bound from the probability of the upper bound: P(-1.62 < z < 2.01) = P(z < 2.01) - P(z < -1.62 = 0.9788 - 0.0526 = 0.9262.

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The best profit Kristen can make each week is $458 by producing 20 T50 and 26 D200.

To maximize profit, Kristen should make the most profitable tuner until she runs out of the necessary resources.

First, let's calculate how many T50 and D200 can be made with the available resources:

- With 224 ounces of plastic, Kristen can make 37 T50 (224/6) or 56.5 D200 (224/4).
- With 276 ounces of metal, Kristen can make 69 T50 (276/4) or 46 D200 (276/6).

Since she can only make a maximum of 20 T50 each week, she should start with making 20 T50. This will use up 120 ounces of plastic and 80 ounces of metal, leaving her with 104 ounces of plastic and 196 ounces of metal.

Next, Kristen should make as many D200 as possible with the remaining resources. She can make 26 D200 with the remaining plastic (104/4) and 32.6 D200 with the remaining metal (196/6). However, since she can only make whole units, she should make 26 D200 to use up the remaining plastic.

So the optimal production plan is:

- 20 T50 (using 120 ounces of plastic and 80 ounces of metal)
- 26 D200 (using 104 ounces of plastic and 156 ounces of metal)

The total profit will be:

- 20 T50 x $6 profit per unit = $120
- 26 D200 x $13 profit per unit = $338
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Answer:

20 percent

Step-by-step explanation:

If the fraction of self-employed to employed lawyers would be 1/5, then you would divide 1 by 5 which gives you .20 percent out of 1, equaling 20%

Answer:

a

Step-by-step explanation:

x² - 3 = 2x ( subtract 2x from both sides )

x² - 2x - 3 = 0 ← in standard form

consider the factors of the constant term (- 3) which sum to give the coefficient of the x- term (- 2)

the factors are - 3 and + 1 , since

- 3 × + 1 = - 3 and - 3 + 1 = - 2 , then

x² - 2x - 3 = (x - 3)(x + 1) = 0 ← in factored form

equate each factor to zero and solve for x

x + 1 = 0 ⇒ x = - 1

x - 3 = 0 ⇒ x = 3

Considering the graphs given here between the scatter plot, its line of best fit and residual plot; linear regression equation is more appropriate for the data because it help to determine a regression correlation in two variables.

In statistics, a regression equation is used to determine whether there is any link between two sets of data. A variable's value can be predicted using linear regression analysis based on the value of another variable.

The Linear Regression equation can be understandable by following justification:

Y= mX +b

Given, Y = { 2,4,6,8,10,12}

           X = {9, 2,1,12,25,48}

         ∵  y = 3.93x - 11.33

          ∵ r = 0.8241

∴ Value of Y = 3

∴ Value of X = {0.8241 + 11.33r} ÷ {0.93}

Thus for the scatter plot dots more understandable with linear equation and for residual plot dots depicts non-linear equation. The two variables X and Y.

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The mean of of −26,39,−10,−16,12,31 is 5 which is determined by summing up the numbers and dividing by 6

What is the mean?

The mean is the sum of the integers divided by the number of integers therein, in other words, the mean is determined sum , having computed the sum we divide by 6 since there are six numbers in the distribution

sum=-26+39-10-16+12+31

sum=30

mean=sum/n

n=6(there are six numbers)

mean=30/6

mean=5

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The area in blue is equal to the complete area minus the area in white in the middle

The big rectangle is 16 by 6, so its area is 16x6 = 96 square inches

The small white rectangle is 4 by 2, so it area is 4x2 = 8 square inches

The area in blue = 96 - 8 = 88 square inches

Answer:

88 square inches

Answer:

Mike is not correct.

Step-by-step explanation:

The probability is an "out of" statement. meaning out of all 6 marbles if 2 are red how what is the probability of choosing a red marble the answer is 2 out of 6 or 1/3 or 0.3333333etc. For green the probability is 1 out of 6 or 1/6 or 0.16666666etc

The false statement among the given options is statement iv: "The sample means calculated from the samples of size 10 give a biased estimate of the true population mean compared with those from the samples of size 100."

Statements i, ii, and iii are true:
i. Each of the means calculated from the samples of size 100 is an unbiased estimate of the population mean. This is true because unbiased estimates are obtained when the sample mean is equal to the population mean on average.
ii. The standard deviation of the means calculated from the samples of size 10 is likely to be larger than the standard deviation of the means calculated from the samples of size 100. This is true because larger sample sizes tend to provide more precise estimates, resulting in smaller variability or standard deviation.
iii. Each of the means calculated from the samples of size 10 is an unbiased estimate of the population mean. This is true because unbiasedness is not dependent on sample size but on the sampling method itself.

Statement iv is false because the sample means calculated from samples of size 10 are unbiased estimates of the population mean, just like those calculated from samples of size 100. Unbiasedness is not influenced by sample size, but rather by the sampling method. The only difference is that the standard deviation of the means calculated from the samples of size 10 is expected to be larger than the standard deviation of the means calculated from the samples of size 100, as mentioned in statement ii.

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There is a 3.51% probability that a group of 10 persons will exceed the load limit of the elevator.

To find the probability that a group of 10 persons will exceed the load limit of the elevator, we need to calculate the probability that the total weight of the group exceeds 2000 lb.

Since the weights of the people are normally distributed with a mean of 185 lb and a standard deviation of 22 lb, we can use the properties of the normal distribution to solve this problem.

First, we need to calculate the mean and standard deviation of the total weight of the group. The mean of the total weight is simply the mean weight of a person multiplied by the number of persons, which is 185 lb * 10 = 1850 lb.

The standard deviation of the total weight is calculated by taking the square root of the sum of the variances of each person's weight. Since the weights are independent, the variance of the total weight is equal to the sum of the variances of each person's weight. So, the standard deviation of the total weight is sqrt(10) * 22 lb ≈ 69.296 lb.

Next, we can use the normal distribution to calculate the probability that the total weight exceeds 2000 lb. We standardize the value using the formula z = (x - mean) / standard deviation, where x is the threshold value of 2000 lb.

Calculating the z-score: z = (2000 - 1850) / 69.296 ≈ 1.81

Finally, we look up the probability corresponding to this z-score in the standard normal distribution table or use a calculator to find the area under the curve to the right of the z-score. The probability that the group of 10 persons will exceed the load limit of the elevator is approximately 0.0351, or 3.51%.

Therefore, there is a 3.51% probability that a group of 10 persons will exceed the load limit of the elevator.

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why did you comment literally nothing helpful on my question and steal the points

Answer: 4.5

Step-by-step explanation:

Answer:

400

Step-by-step explanation:

(8*11*4)+(2*8*3)=400

^you find volume of each and then add together

pls mark brainliest :)

Answer:

400 cubic centimeters

Step-by-step explanation:

First box:

11(4)(8) = 352

Second box:

2(8)(3) = 48

352 + 48 = 400 cubic cm

False. Each triangle in the STL file is defined by the vertices, but not necessarily by the inward pointing surface normal vector. The surface normal vector is often calculated based on the vertex positions.

False. The STL file is a mesh representation of the CAD model, and it does not contain all the information needed to fully reconstruct the original CAD model. It lacks information such as parametric features, assembly relationships, and design intent, making it difficult to recreate the exact original model.

The option "Increasing the heat exchange area for a heat exchanger" is NOT an advantage of using a lattice structure. Lattice structures are known for their lightweight properties, material-saving benefits, and simplified design and manufacturing processes.

However, increasing the heat exchange area for a heat exchanger is not typically associated with lattice structures. Heat exchangers usually rely on other design considerations, such as fin arrays or extended surfaces, to enhance heat transfer efficiency, rather than lattice structures.

Therefore, increasing heat exchange area is not a direct advantage of lattice structures.

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An angle bisector is a line that divides an angle into two equal parts

From the figure attached, we will observe that Line RU bisects Angle TRP into two parts (TRU & PRU)

Hence, the corect answer is a. (RU)

The total number of red marbles in the vase are 10.

A ratio is described as a comparison between two amounts with the same unit to determine the amount of 1 quantity is contained in the other. Ratios are divided into two sorts.

The first is a part-to-part ratio, and the second is a part-to-whole ratio. The part-to-part ratio expresses the relationship between 2 separate entities or groupings.

Now, according to the question;

Let 'x' be the red marbles in the vase.

Let 'y' be the orange marbles in the vase.

The total number of marbles in the vase are 60

x  + y = 60 (equation 1)

The ratio of red marbles to orange ones is 1:5.

Thus, x/y = 1/5

cross multiplying;

5x = y

or y = 5x

substitute the value of y in equation 1;

x  + y = 60 (equation 1)

x  + 5x = 60

6x = 60

x = 10  (red marbles)

Thus, the number of red marbles in the vase are 10.

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Answer:

Step-by-step explanation:a or b ?

Answer:

beleive its 35

Step-by-step explanation:

Answer:

The mode hear is 32

Step-by-step explanation:

The mode is the number seen the most in a selected group.

Here is a Mnemonic to help remember what the 3 M's are:

'Hey diddle, diddle

the medians in the middle

add and divide for the mean

the mode is the one that you see the most

and the range is the difference between'

The point where he  buried his treasure is (6.28,9.84)

First of all, we are going to find the equation of the line which describes the first path crossed by the horseman.  In order to find it we have to take into account that the vector V  provides us with the direction of this path. We can associate the direction with the slope of the line. The slope is defined by the ratio of vertical changes to horizontal changes between two points.  

According to the V=6i+5j, we can determine that:

Vertical change (y)= 5

Horizontal change (x)=6

Slope=\frac{5}{6}

Now, using the point-slope form:

y-y₁=m(x-x₁)

The chosen point is the point where the horseman began riding (-2,5). Therefore:

m=5/6

y1=5

x1=-2

y-5=5/6(x+2)

y=5x/6-10/3

Since the horseman at some point turned at a right angle towards village B  and he unchanged his direction until arrived in village B, the second path must be described by a line perpendicular to the first path.  

We should know that two lines are perpendicular if and only if their slopes are negative reciprocals This means m1*m2=-1

m₁=5/6

m₂=-1/m₁=-6/5

In order to find the equation of the second path, we will use again the point-slope form.

The chosen point is the point where is located Village B (2,11)

y-11=-6/5(x-2)

y=-6x/5+13.4

The coordinates of the point where the horseman buried a jar full of silver coins correspond to the intersection of path 1 and path 2. Therefore we are going to equal the two equations of each path.

5x/6-10/3=-6x/5+13.4

Solving this equality for x

X=6.28

Replacing this value in any of the equations of the paths

Y=9.84.

Finally, the point where he buried his treasure is (6.28,9.84).

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Answer:

Jane's rate is 21.25 mph.

Jack's rate is 41.25mph

Explanation:

Let x represent Jane's speed.

Jack's speed will be x+20.

Their combined speed is;

After 4 hours, their combined distance covered is 250 miles;

solving for x;

Jane's rate is 21.25 mph.

Since jack's rate is 20 mph faster than Jane's rate.

Jack's rate is;

Jack's rate is 41.25mph

Answer:

-24

Step-by-step explanation:

First find f(3), which is the value of the blue line when x =3

f(3) = -2

Then find g(-1) which is the value of the red line when x= -1

g(-1) = 6

-6 f(3) - 6*g(-1)

-6*-2 - 6(6)

12 - 36

-24

If f(x)=\((2-10x)(2-10x^2)(2-10x^3)(2-10x^4)(2-10x^5)(2-10x^6)\), then its derivative, f'(1)= 5/2.

To find the derivative of the given function f(x), we can use the product rule of differentiation. Let's start by taking the natural logarithm of f(x) to simplify the calculation:

ln[f(x)] = ln[\((2-10x)(2-10x^2)(2-10x^3)(2-10x^4)(2-10x^5)(2-10x^6)\)]

= \(ln(2-10x) + ln(2-10x^2) + ln(2-10x^3) + ln(2-10x^4) + ln(2-10x^5) + ln(2-10x^6)\)

Now, we can take the derivative of both sides using the chain rule and product rule of differentiation:

[d/dx] ln[f(x)] = [d/dx] \([ln(2-10x) + ln(2-10x^2) + ln(2-10x^3) + ln(2-10x^4) + ln(2-10x^5) + ln(2-10x^6)]\)

d[f(x)]/f(x) = \(1/(2-10x) + 1/(2-10x^2) + 1/(2-10x^3) + 1/(2-10x^4) + 1/(2-10x^5) + 1/(2-10x^6)\)

Now, we can evaluate f'(1) by substituting x=1 into the above expression:

d[f(x)]/dx| x=1 = 1/(2-10) + 1/(2-10) + 1/(2-10) + 1/(2-10) + 1/(2-10) + 1/(2-10)

= -10/(-8) - 20/(-8) - 30/(-8) - 40/(-8) - 50/(-8) - 60/(-8)

= 5/2

Therefore, the value of f'(1) is 5/2.

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a) The population model for Betaburgh is:P(t) = -105004t + 3000 b) The population of Alphaville in 2005 was approximately 5062 people. c) The population of Betaburgh will be 5000 people 0.019 years (or approximately 7 days) after 1990.

a) The population model for Alphaville is given by:

P"(t) = 45

Integrating with respect to t twice, we get:

P'(t) = 45t + C1

where C1 is a constant of integration.

Integrating P'(t) with respect to t, we get:

P(t) = (45/2)t^2 + C1t + C2

where C2 is another constant of integration.

Using the initial condition that Alphaville had a population of 5500 in 1990 (when t=0), we get:

P(0) = C2 = 5500

Therefore, the population model for Alphaville is:

P(t) = (45/2)t^2 + C1t + 5500

Similarly, the population model for Betaburgh is given by:

P'(t) = -105004

Integrating P'(t) with respect to t, we get:

P(t) = -105004t + C3

where C3 is a constant of integration.

Using the initial condition that Betaburgh had a population of 3000 in 1990 (when t=0), we get:

P(0) = C3 = 3000

Therefore, the population model for Betaburgh is:

P(t) = -105004t + 3000

b) To find the population of Alphaville in 2005 (when t=15), we plug in t=15 into the population model:

P(15) = (45/2)(15)^2 + C1(15) + 5500

We still need to find the value of C1. To do this, we use the fact that the rate of change in population in Alphaville was 45 people per year in 1990 (when t=0):

P'(0) = 45 = C1

Substituting this value into the population model, we get:

P(15) = (45/2)(15)^2 + 45(15) + 5500

P(15) = 5062.5

Therefore, the population of Alphaville in 2005 was approximately 5062 people.

c)

To find when the population of Betaburgh will be 5000, we plug in P(t)=5000 into the population model and solve for t:

-105004t + 3000 = 5000

-105004t = 2000

t = -0.019

This means that the population of Betaburgh will be 5000 people 0.019 years (or approximately 7 days) after 1990. However, since time cannot be negative, we can conclude that the population of Betaburgh will never reach 5000 people.

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The following statements are true regarding the margin of error: Being more confident (increasing confidence level) will yield a larger margin of error and selecting a larger SRS from the population will yield a smaller margin of error.

A margin of error (MOE) is the degree of inaccuracy in estimating a population's true proportion or mean by analyzing a sample dataset. It represents the uncertainty or confidence level of a poll's findings. It is a critical element in political polls, scientific studies, and marketing research. The accuracy of the findings is expressed in the margin of error, which is given as a percentage. The standard deviation of the sampling distribution, not the standard deviation of the population, determines the margin of error. As a result, selecting a larger sample size, the standard deviation decreases, and the margin of error decreases. Therefore, selecting a larger SRS from the population will yield a smaller margin of error. Confidence intervals are used to determine the margin of error, and increasing the confidence level will result in a larger margin of error. As a result, being more confident (increasing confidence level) will yield a larger margin of error.

Thus, the correct options are (B) and (D). Option (A) is incorrect because a large confidence level requires a large value of 2*. Option (C) is incorrect because the margin of error is influenced by the standard deviation of the sampling distribution.

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