HEYYYYYY!!!!!!
In the figure shown below, triangle PQR is transformed to create triangle P'Q'R'.

Point S will be transformed the same way as triangle PQR. Which sentence could describe how point S will be transformed?

a. Point S will be translated to (4, 3) and then reflected to (4, -3).

b. Point S will be translated to (6, 0) and then rotated to (0, 6).
c. Point S will be translated to (4, 3) and then reflected to (-4, 3).
d. Point S will be translated to (6, 0) and then rotated to (0, -6).

The average temperature change per hour should be represented by the value such as = 3.2 °f /hr

The temperature decrease of 20.8f° = 6.5 hrs

The decrease of temperature of xf° = 1 hr

Mathematically;

20.8°f = 6.5 hrs

X °f = 1 HR

Make X the subject of formula;

X = 20.8/6.5

= 3.2 °f /hr

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To solve this problem :
A = P(1 + r/n)^(nt)
Where:
A = the final amount
P = the principal amount (the initial investment)
r = the annual interest rate (as a decimal)
n = the number of times the interest is compounded per year
t = the number of years
In this case, we have:
P = $46,950.00
r = 6.78% = 0.0678
n = 2 (since the interest is compounded semi-annually)
t = 12 (since we are investing for 12 years and withdrawing at the end of every three months)

To find the amount that can be withdrawn, we need to solve for A when t = 12/4 = 3 (since we are withdrawing every three months):
A = P(1 + r/n)^(nt)
A = $46,950.00(1 + 0.0678/2)^(2*3)
A = $46,950.00(1.0339)^6
A = $46,950.00(1.2307)
A = $57,789.27
So the sum of money that can be withdrawn from the fund is $57,789.27.

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Answer:

Step-by-step explanation:

To show that P(M > k) = [P(M > 1)]k for k > 0, we first need to find the probability that the maximum of the simple random walk is greater than a given value k.

Let A be the event that the maximum of the random walk is greater than k. We can express this event as the union of events Bn, where Bn is the event that the maximum up to time n is greater than k, but the maximum up to time n-1 is less than or equal to k.

That is, A = B1 ∪ B2 ∪ B3 ∪ ...

To find the probability of A, we can use the union bound:

P(A) ≤ P(B1) + P(B2) + P(B3) + ...

Now, let's focus on one of the events Bn. To calculate its probability, we can use the Markov property of the simple random walk. That is, given that the maximum up to time n-1 is less than or equal to k, the maximum up to time n can only be greater than k if the random walk hits k at some point after time n-1.

Let Hk be the hitting time of k, i.e., the first time that the random walk reaches k. Then,

P(Bn) ≤ P(Hk > n-1)

Using the reflection principle, we can show that the probability that the random walk hits k at or after time n is equal to the probability that the random walk hits -k at or after time n, which is:

P(Hk > n) = 2q^n

Therefore, we have:

P(Bn) ≤ 2q^(n-1)

Now, we can use this bound to bound the probability of A:

P(A) ≤ Σ P(Bn) ≤ Σ 2q^(n-1)

Using the formula for the sum of a geometric series, we get:

P(A) ≤ 2q/(1-q)

Finally, we can use the fact that the maximum of the random walk is a non-decreasing process to get:

P(M > k) = P(A) ≤ 2q/(1-q)

To get the desired result, we need to show that P(M > 1) = 2q/(1-q), which can be easily verified using the above formula with k = 1.

Therefore, we have:

P(M > k) = P(A) ≤ 2q/(1-q) = [P(M > 1)]^k

as desired.

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The calculated value of the mode of the number of pets among the families is 1

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

The histogram

As a general rule, the mode of an histogram is the data set that has the highest frequency

In this case, n = 1 has the highest frequency of 500

This means that we can conclude that the mode has a value of 1 (with a frequency of 500)

Hence, the mode from the histogram/distribution is 1

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An equation to represent the number of bricks that will be needed for 2 walls is m = 2x

Here, a house has x bricks and 10 pounds of glue to build a wall.

this means that to build one wall, it requires 'x' number of bricks.

Let us assume that for 2 wall it will need 'm' number of bricks.

Using Unitary method the number of bricks needed for 2 walls would be,

⇒ m = 2 × x

⇒ m = 2x

This means that to build two walls, it will take 2x number of bricks, where x is the number of bricks needed to build a single wall.

Therefore,  an equation that represents the number of bricks that will be needed for 2 walls: 2x

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The event that will have a sample space of S = {h, t} is (a) Flipping a fair, two-sided coin

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

Sample space of S = {h, t}

The sample size of the above is

Size = 2

Analyzing the options, we have

Hence, the event is (a)

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A) The probability of a randomly selected catch being a mouse caught by Cyd 40%.

b) If Cyd didn't catch the bird, then no other cat did.

c) The probability of a randomly selected is 0.333

d) The probability that a catch being a mouse caught by Greg is 0

e) The probability of a randomly selected catch is a mouse caught by Rom is 0. 2 is verified by the catch made by Ken is a mouse.

F) The probability that a catch which is a mouse was made by Cyd is 40%.

a) The probability of a randomly selected catch being a mouse caught by Cyd can be calculated as follows:

Probability of Mouse caught by Cyd = 0.20

Probability of any catch being a Mouse = 0.50 (given in the problem statement)

Therefore, Probability (Mouse caught by Cyd) = 0.20 / 0.50 = 0.40 or 40%

b) To calculate the probability of a bird not caught by Cyd, we need to subtract the probability of a bird caught by Cyd from 1 (since the event of a bird not caught by Cyd is complementary to the event of a bird caught by Cyd).

Probability of Bird caught by Cyd = 1 - Probability of any catch being a Mouse = 1 - 0.50 = 0.50

Probability of any catch not being a Mouse = 1 - Probability of any catch being a Mouse = 1 - 0.50 = 0.50

Therefore, Probability (Bird caught by Cyd) = 0.50 / 0.50 = 1.

And, Probability (Bird not caught by Cyd) = 1 - 1 = 0.

c) Greg's catches are equally likely to be a mouse, a bird, or a vole. We can calculate the probability of a catch being a mouse caught by Greg as follows:

Given, Probability of Mouse caught by Greg = Probability of Vole caught by Greg = Probability of Bird caught by Greg = 0.45 / 3 = 0.15

Therefore, Total Probability of any catch caught by Greg = 0.15 + 0.15 + 0.15 = 0.45

Hence, Probability (Mouse caught by Greg) = 0.15 / 0.45 = 1/3 or 0.333 (approx.)

d) We are given that the probability of a randomly selected catch being a mouse caught by Ken is 0.5. We need to find the probability that a catch being a mouse is caught by Greg.

So, the probability of any catch being caught by Ken = 50 / 100 = 0.5.

We know that the total probability of any catch caught by Greg is 0.45 (as calculated in part c).

Therefore, Probability (Mouse caught by Greg) = x, Probability (Vole caught by Greg) = x, and Probability (Bird caught by Greg) = 0.45 - 2x (since the probabilities must add up to 0.45).

Probability (Mouse) = Probability (Mouse caught by Ken) + Probability (Mouse caught by Greg)

0.5 = 0.5 + x

x = 0

This means that there is no probability of a mouse being caught by Greg, since all of the mice are already accounted for by Ken.

e) We are given that the probability of a randomly selected catch being a mouse caught by Rom is 0.2. We need to verify if the catch made by Ken is a mouse.

So, the probability of any catch being caught by Rom = 20 / 100 = 0.2.

We know that the probability of a catch being a mouse caught by Ken is 0.5.

Probability of Mouse caught by Rom | Mouse caught by Ken = 1 (since all mice are assumed to be distinct)

Probability (Mouse caught by Ken) = 0.5

Probability (Mouse caught by Rom) = 0.2

Therefore, Probability (Mouse caught by Ken | Mouse caught by Rom) = 1 * 0.5 / 0.2 =0.25 or 25% (approx.)

This means that if we know that Rom caught a mouse, the probability of Ken catching a mouse is actually higher than the overall probability of any catch being a mouse.

f) Finally, we need to find the probability that a catch which is a mouse was made by Cyd. We can use Bayes' Theorem again to calculate this:

Probability (Mouse | Mouse caught by Cyd) = 1 (since all mice are assumed to be distinct)

Probability (Mouse caught by Cyd) = 0.2 (since Cyd catches 20% of all creatures)

Probability (Mouse) = 0.5 (since half of all creatures caught are mice)

Therefore, Probability (Mouse caught by Cyd | Mouse) = 1 * 0.2 / 0.5 = 0.4 or 40%.

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The solutions are

i)  x = 2

ii) Therefore, there is no integer x that satisfies the congruence.

iii) x = 2

What is the equivalent expression?

Equivalent expressions are expressions that perform the same function despite their appearance. If two algebraic expressions are equivalent, they have the same value when we use the same variable value.

i. To solve 7 × 3 = 3 (mod 11), we need to find an integer x such that 7 × 3 is congruent to 3 modulo 11.

First, we can simplify 7 × 3 by calculating 73 = 343 and then taking the remainder when 343 is divided by 11. We get:

7 × 3 = 343 = 31 × 11 + 2

So, we have:

7 × 3 = 2 (mod 11)

To solve for x, we can try multiplying both sides by the modular inverse of 7 modulo 11.

The modular inverse of 7 modulo 11 is 8, because 7 x 8 is congruent to 1 modulo 11. So, we have:

8 × 7 × 3 = 8 × 2 (mod 11)

Simplifying:

56 × 3 = 16 (mod 11)

5 × 3 = 16 (mod 11)

We can check the values of x = 2 and x = 7 to see which one satisfies the congruence:

5 × 23 = 30 = 2 (mod 11)

5 × 73 = 365 = 9 (mod 11)

So the solution is x = 2.

ii. To solve 3.14 = 5 (mod 11), we need to find an integer x such that 3.14 is congruent to 5 modulo 11.

Since 3.14 is not an integer, we cannot directly apply modular arithmetic to it.

Instead, we can use the fact that 3.14 is equal to 3 + 0.14, and try to solve the congruence for each part separately.

First, we can find an integer k such that 3 + 11k is congruent to 5 modulo 11. This means:

3 + 11k = 5 + 11m for some integer m

Simplifying:

11k - 11m = 2

Dividing by 11:

k - m = 2/11

Since k and m are integers, the only possible value of k - m is 0. Therefore, we have:

k - m = 0

k = m

Substituting k = m, we get:

3 + 11k = 5 + 11k

This is not possible, since 3 is not congruent to 5 modulo 11. Therefore, there is no integer x that satisfies the congruence.

iii. To solve x8 = 10 (mod 11), we need to find an integer x such that x8 is congruent to 10 modulo 11.

We can try raising each integer from 0 to 10 to the power of 8, and check which one is congruent to 10 modulo 11:

0⁸ = 0 (mod 11)

1⁸ = 1 (mod 11)

2⁸ = 256 = 10 (mod 11)

3⁸ = 6561 = 10 (mod 11)

4⁸ = 65536 = 1 (mod 11)

5⁸ = 390625 = 10 (mod 11)

6⁸ = 1679616 = 1 (mod 11)

7⁸ = 5764801 = 5 (mod 11)

8⁸ = 16777216 = 1 (mod 11)

9⁸ = 43046721 = 10 (mod 11)

10⁸ = 10000000000 = 1 (mod 11)

Therefore, the solutions are x = 2,

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Answer:

5xy + 6y

Step-by-step explanation:

4x(2y) + 3y(2-x)

= 8xy + 6y - 3xy

= 5xy + 6y

So, the answer is 5xy + 6y

The simplified expression is:5xy + 6y

Expanding the expression gives:

4x(2y) + 3y(2 - x) = 8xy + 6y - 3xy

Combining like terms, we get:

8xy - 3xy + 6y = 5xy + 6y

Therefore, the simplified expression is:

5xy + 6y

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The p-value for the given test statistic of z=2.603 and the null hypothesis Ha: p ≠ 71% can be calculated using a standard normal distribution table or a statistical software package. The p-value represents the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true.

Using a standard normal distribution table, we can find the area under the curve to the right of z=2.603 as follows:

p-value = P(Z > 2.603) = 0.0042 (rounded to 4 decimal places)

Alternatively, we can use a statistical software package such as Excel or R to calculate the p-value. In Excel, the p-value can be calculated using the following formula:

p-value = 2*(1-NORM.S.DIST(ABS(z),TRUE))

Where z is the test statistic and ABS() returns the absolute value of z. Plugging in the value of z=2.603, we get:

p-value = 2*(1-NORM.S.DIST(ABS(2.603),TRUE)) = 0.0042 (rounded to 4 decimal places)

In R, the p-value can be calculated using the following command:

pvalue <- 2*(1-pnorm(abs(z)))

Where z is the test statistic and abs() returns the absolute value of z. Plugging in the value of z=2.603, we get:

pvalue <- 2*(1-pnorm(abs(2.603))) = 0.0042 (rounded to 4 decimal places)

Therefore, the p-value for the given test statistic of z=2.603 and the null hypothesis Ha: p ≠ 71% is 0.0042, accurate to 4 decimal places. This indicates that the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true, is very small (less than 0.01). As such, we can reject the null hypothesis and conclude that the proportion of women over 40 who regularly have mammograms is significantly different from 71%.

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Answer:

89

Step-by-step explanation:

it is a straight line mean 180 degrees.

180 subtract 91 is 89

Answer:The measure of angle b is 89 degrees.

Step-by-step explanation:

Types of angles:

• Angles between 0 and 90 degrees (0°< θ <90°) are called acute angles.

• Angles between 90 and 180 degrees (90°< θ <180°) are known as obtuse angles.

• Angles that are 90 degrees (θ = 90°) are right angles.

• Angles that are 180 degrees (θ = 180°) are known as straight angles.

• Angles between 180 and 360 degrees (180°< θ < 360°) are called reflex angles.

• Angles that are 360 degrees (θ = 360°) are full turn.

We know that,

 Angles that are 180 degrees (θ = 180°) are known as straight angles.

In this question ,let

a= 91 and we have to find b=?

here,by straight angle

a+b=180

91+b=180

b=180-91

b=89

this is the required answer.

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75% of the time, a student who is just guessing will get 28 or below out of 107.

We have,

The probability of getting a question correct by guessing is 1/4.

Let X be the number of questions guessed correctly.

Since X follows a binomial distribution with n=10 and p=1/4, the expected value of X is given by E(X) = np = 10 * 1/4 = 2.5.

The variance of X is given by Var(X)

= np(1 - p)

= 10 x 1/4 x 3/4

= 1.875, and the standard deviation is the square root of the variance, which is √(1.875) ≈ 1.37.

To get the minimum passing score of 60%, you need to get at least 6 questions correct.

The probability of getting exactly 6 questions correct.

P(X=6) = (10 choose 6) x (1/4)^6 x (3/4)^4 ≈ 0.016.

To get any passing score, you need to get 6 or more questions correct. The probability of getting 6, 7, 8, 9, or 10 questions correct.

= P(X≥6) = P(X=6) + P(X=7) + P(X=8) + P(X=9) + P(X=10).

Using a binomial calculator, we find P(X ≥ 6) ≈ 0.078.

To find the score that a student who is just guessing will get 75% of the time or below out of 107, we can use the normal approximation to the binomial distribution.

The mean of the distribution is np = 26.75, and the standard deviation is sqrt(np(1-p)) = 3.27.

We can standardize the score by subtracting the mean and dividing by the standard deviation:

(75th percentile score - mean) / standard deviation

= (0.75 - 0.5) / 0.5 = 0.5.

Solving for the 75th percentile score, we get,

= (0.5 x 3.27) + 26.75

= 28.16.

Therefore,

75% of the time, a student who is just guessing will get 28 or below out of 107.

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When working with an ANOVA, the parameter we use is A) σ2.

When working with an ANOVA, the parameter we use is σ2. This parameter represents the population variance, which is important in comparing the means of different groups and determining if there is a significant difference between them.

The population variance, σ2, measures the spread or variability of the data within each group or treatment. It provides information about how much the individual observations deviate from the group mean.

By comparing the variances between groups and within groups, ANOVA allows us to assess if the observed differences in means are statistically significant or simply due to random variation.

The ANOVA test calculates a statistic called the F-statistic, which is the ratio of the between-group variability to the within-group variability. This F-statistic follows an F-distribution, and its significance determines whether the observed differences in means are likely due to the treatments or just random chance.

Therefore, the correct option is a) σ2.

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The rule for the table is y = -8x + 88.

The price of the shoes after 8 month is 24 dollars.

The table shows the discount prices for a pair of shoes over several months.

Therefore, the rule for the tables can be represented as follows:

y = mx + b

where

Therefore, using (1,80)(2, 72)

m = 72 - 80 / 2 - 1

m = -8

Hence,

y = -8x + b

using (1, 80)

80 = -8 + b

b = 88

Therefore,

y = -8x + 88

Therefore, let's find the price after 8 months

y = -8(8) + 88

y = -64 + 88

y = 24

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The mass percent of the vinegar solution is approximately 3.85%.

To calculate the mass percent of a vinegar solution containing 3.74 g of acetic acid in a total mass of 97.20 g, follow these steps:

1. Identify the mass of acetic acid (3.74 g) and the total mass of the solution (97.20 g).
2. Divide the mass of acetic acid by the total mass of the solution:

    3.74 g ÷ 97.20 g.
3. Multiply the result by 100 to get the mass percent:

    (3.74 g ÷ 97.20 g) × 100.

Thus, the mass percent of the vinegar solution is approximately 3.85%.

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The test statistic for testing the hypotheses H0: μ=100 vs Ha: μ<100 using the given sample results x = 91.7, s= 12.5 with n = 30 is -2.17 and the p-value is 0.019. We can reject the null hypothesis H0: μ=100 in favor of the alternative hypothesis Ha: μ<100 at a 5% level of significance.

(a) The test statistic for testing the hypotheses H0: μ=100 vs Ha: μ<100 using the given sample results x = 91.7, s= 12.5 with n = 30 can be calculated as:

t = (x - μ) / (s / sqrt(n))
= (91.7 - 100) / (12.5 / sqrt(30))
= -2.17 (rounded to two decimal places)

Using a t-table with 29 degrees of freedom (n - 1 = 30 - 1 = 29) and a 5% significance level (or 0.05), the corresponding p-value for a one-tailed test is found to be 0.019 (rounded to three decimal places). Therefore, the p-value for the given test statistic is 0.019.

(b) Since the p-value (0.019) is less than the significance level (0.05), we can reject the null hypothesis H0: μ=100 in favor of the alternative hypothesis Ha: μ<100. This implies that there is sufficient evidence to conclude that the population means μ is less than 100 at a 5% level of significance. In other words, the sample provides strong evidence that the true population mean is lower than the hypothesized value of 100.

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As per the given triangle, the value of sin A in decimal form, rounded to three decimal places, is approximately 0.946.

We can use the definition of sine to find sin A:

sin A = opposite/hypotenuse

In this case, the opposite side is the height of the triangle, which is 35, and the hypotenuse is 37. Therefore:

sin A = 35/37

This fraction cannot be simplified any further, so the value of sin A in fraction form is 35/37.

To find the equivalent decimal, we can divide the numerator by the denominator:

sin A = 35/37 ≈ 0.946

Therefore, the value of sin A in decimal form, rounded to three decimal places, is approximately 0.946.

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We have successfully drawn the given planes when working on a body centered cubic structure.

When working with a body centered cubic structure, it's important to understand that the unit cell consists of a cube with one additional atom at the center of the cube. This gives rise to unique properties and symmetry within the crystal structure.

To draw the planes (100), (010), and (101) within this structure, we can use the Miller indices notation. In this notation, each plane is represented by three integers that correspond to the intercepts of the plane with the three axes of the unit cell.

For example, the (100) plane intersects the x-axis at a point where x=1, and intersects the y- and z-axes at points where y=0 and z=0, respectively. Using the Miller indices notation, we can write this plane as (100).

Similarly, the (010) plane intersects the y-axis at a point where y=1, and intersects the x- and z-axes at points where x=0 and z=0. Therefore, this plane can be written as (010).

Finally, the (101) plane intersects the x-axis at a point where x=1, the y-axis at a point where y=0, and the z-axis at a point where z=1. Using Miller indices notation, we can represent this plane as (101).

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Answer:

false

Step-by-step explanation:

False.

The statement is almost correct, but it is missing one important detail. The median in a frequency distribution is determined by identifying the value that corresponds to a cumulative frequency of 50% (not a cumulative percentage of 50%).

The cumulative frequency is the running total of the frequencies as you move through the classes in the frequency distribution. Once you reach a cumulative frequency of 50%, you have identified the median.

P(1) is true and assuming P(k) being true implies P(k+1) is true, we can conclude that the formula P(k) = (k-1) is true for all integers 1 ≤ k ≤ n by mathematical induction.

(a) To find the coefficient of x in (x+2)^11, we can expand the binomial using the binomial theorem. According to the binomial theorem, the expansion of (x+2)^11 can be written as:

(x+2)^11 = C(11,0) * x^11 * 2^0 + C(11,1) * x^10 * 2^1 + C(11,2) * x^9 * 2^2 + ... + C(11,11) * x^0 * 2^11

The coefficient of x is obtained from the term with x^10. Thus, the coefficient of x in (x+2)^11 is given by C(11,1) * 2^1 = 11 * 2 = 22.

Therefore, the coefficient of x in (x+2)^11 is 22.

(b) To show that the formula P(k) = (k-1) is true for all integers 1 ≤ k ≤ n using mathematical induction, we need to demonstrate two things:

Base case: Show that P(1) is true.

For k = 1, P(k) = (k-1) = (1-1) = 0. Therefore, P(1) is true.

Inductive step: Assume P(k) is true for some integer k ≥ 1, and prove that P(k+1) is true.

Assume P(k) = (k-1) is true.

We need to show that P(k+1) = ((k+1)-1) is also true.

P(k+1) = ((k+1)-1) = k

By assuming P(k) is true, we have shown that P(k+1) is also true.

Since P(1) is true and assuming P(k) being true implies P(k+1) is true, we can conclude that the formula P(k) = (k-1) is true for all integers 1 ≤ k ≤ n by mathematical induction.

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Natalia's minimum hourly wage to support her family of 4 is $16.98.

The minimum hourly wage can be determined using some of the basic mathematical operations, including multiplication, addition, and division.

The estimated yearly income to support the first person = $18,946

The additional income required to support each additional person in the family = $4,437

The number of family members in Natalia's = 4

Natalia's work week hours = 38

The number of weeks per year = 50

Total work week hours per year = 1,900 hours (38 x 50)

First person's income = $18,946

Additional income for 3 = $13,211 ($4,437 x 3)

Total income = $32,257

Hourly wage = $16.98 ($32,257 ÷ 1,900)

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A solution to the given expression is -44 4/9.

In order to evaluate and solve this expression, we would have to apply the PEMDAS rule, where mathematical operations within the parenthesis (grouping symbols) are first of all evaluated, followed by exponent, and then multiplication or division from the left side of the equation to the right. Lastly, the mathematical operations of addition or subtraction would be performed from left to right.

Based on the information provided, we have the following mathematical expression:

-36 4/9 - (-10 2/9) - (18 2/9)

By opening the bracket, we have the following:

-36 4/9 + 10 2/9 - 18 2/9

By converting the mixed fraction into an improper fraction, we have the following:

-328/9 + 92/9 - 164/9

(-328 + 92 - 164)/9 = -44 4/9.

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To find the probability that the student will answer correctly on all three questions, we need to multiply the probabilities of answering each question correctly. Since there are 5 possible answers for each question, the probability of guessing the correct answer for one question is 1/5. However, for the first question, the student already knows that one of the answers is not correct, so the probability of guessing the correct answer for that question is 1/4. For the second question, the student knows that two of the answers are not correct, so the probability of guessing the correct answer for that question is 1/3. And for the third question, the student has no information, so the probability of guessing the correct answer is 1/5. Therefore, the probability of answering all three questions correctly is:

(1/4) * (1/3) * (1/5) = 1/60 or approximately 0.017 or 1.7%

To find the probability that the student will answer correctly to the first and third question and wrongly on the second, we need to multiply the probabilities of answering each question correctly or wrongly as given in the question. The probability of guessing the correct answer for the first question is 1/4 and the probability of guessing the correct answer for the third question is 1/5. For the second question, the student knows that two of the answers are not correct, so the probability of guessing the wrong answer for that question is 2/3. Therefore, the probability of answering the first and third questions correctly and the second question wrongly is:

(1/4) * (2/3) * (1/5) = 1/30 or approximately 0.033 or 3.3%

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The CES (Constant Elasticity of Substitution) production function is a mathematical model used to represent the relationship between inputs and output in production. To determine the concavity or convexity of the CES production function, we need to look at its second derivative.

The general CES production function is given by:

Q = A * [(α * L^ρ) + (β * K^ρ)]^(1/ρ)

Where:
Q = Output
A = Total factor productivity
L = Labor input
K = Capital input
α and β = Input share parameters
ρ = Elasticity of substitution parameter

To determine concavity or convexity, we examine the second derivatives with respect to L and K:

∂²Q/∂L² and ∂²Q/∂K²

If both second derivatives are negative, the production function is concave. If both are positive, it's convex. If the signs are different, the function exhibits neither concavity nor convexity.

In the case of the CES production function, the sign of the second derivatives will be determined by the value of the elasticity of substitution parameter (ρ). If ρ is positive, the production function exhibits convexity, whereas if ρ is negative, the production function exhibits concavity. If ρ equals zero, it is neither convex nor concave.

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Answer: 12

If you are trying to find the length of the long side of the triangle, use this formula: a^2 + b^2 = c^2

So, for you, it'd be 3^2 + 4^2 = 12^2

If it isn't, use this formula: a^2 - b^2 = c^2

EX: 3^2 - 12^2 = 4^2

The value of x, to the nearest tenth, is approximately 4.96. The steps involved using the tangent ratio and solving for the unknown side in a right triangle.

In a triangle, the angle opposite to the side x as angle A, and the side opposite to the angle 33° as side B, and the largest side as side C. So we have:

Angle A = 90° - 33° = 57° (since the sum of angles in a triangle is 180°)

Side B = 8

Side C = 15

Side x = ?

Write the formula for the tangent ratio in terms of the sides of the triangle. For angle A, we have:

tangent(A) = opposite/adjacent

Substitute the known values into the formula and solve for the unknown side. Substituting the values we have, we get

tangent(33°) = x/8

Multiplying both sides by 8, we get:

x = 8 * tangent(33°)

Use a calculator to find the value of the tangent of 33 degrees. We get:

tangent(33°) ≈ 0.6494

Substitute the value of the tangent into the formula we obtained in step 3 and solve for x. We get

x ≈ 8 * 0.6494

x ≈ 5.1952

Round the answer to the nearest tenth, since the question asks for the value of x to the nearest tenth. We get

x ≈ 4.96

Therefore, the value of x, to the nearest tenth, is approximately 4.96.

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The vector component of u orthogonal to v is (821/113)i - (56/113)j.

(a) The projection of u onto v can be found using the formula: proj_v u = (u . v / ||v||^2) * v, where "." denotes the dot product and "||v||" denotes the magnitude of v.

First, we find the dot product of u and v:

u . v = (3i + 4j) . (8i + 7j)

= 3(8) + 4(7)

= 44

Next, we find the magnitude of v:

||v|| = sqrt((8)^2 + (7)^2)

= sqrt(113)

Finally, we can use the formula to find the projection of u onto v:

proj_v u = (44 / 113) * (8i + 7j)

= (352/113)i + (308/113)j

Therefore, the projection of u onto v is (352/113)i + (308/113)j.

(b) The vector component of u orthogonal to v can be found by subtracting the projection of u onto v from u:

u - proj_v u = (3i + 4j) - ((352/113)i + (308/113)j)

= (821/113)i - (56/113)j

Therefore, the vector component of u orthogonal to v is (821/113)i - (56/113)j.

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