Harrison has a rectangular plank of wood that is 29 inches long. He creates a ramp by resting the plank against a wall with a height of 14 inches, as shown. Using Pythagoras' theorem, work out the horizontal distance between the wall and the bottom of the ramp. Give your answer in inches to 1 d.p. Not drawn accurately​

Answer:

$18.68

Step-by-step explanation:

We Know

Ivan is buying $18.81 worth of produce.

He has his own bag and gets a $0.13 discount.

How much will Ivan pay after the discount?

We Take

18.81 - 0.13 = $18.68

So, Ivan will pay $18.68 after the discount.

1)  the three transformations are a reflection across the x-axis, a horizontal shift 3 units to the left, and a vertical stretching by a factor of 2.

2) The Firework is 500 feet  the ground at two different times: t = 15/4 (or 3.75) seconds and t = 8 seconds.

Q1: To determine the three transformations that will produce the graph of y = -2(x+3)^2 from the original function g(x) = x^2, we can analyze the given equation:

1. Reflection: The negative sign in front of the 2 in y = -2(x+3)^2 indicates a vertical reflection of the graph. This means that the graph will be reflected across the x-axis.

2. Vertical Translation: The term (x+3) in y = -2(x+3)^2 represents a horizontal shift of the graph. Since it is inside the parentheses, we shift the graph 3 units to the left. This means the vertex of the parabola will now occur at x = -3.

3. Vertical Scaling: The coefficient -2 in y = -2(x+3)^2 represents a vertical scaling of the graph. It indicates that the graph will be stretched vertically by a factor of 2.

In summary, the three transformations are a reflection across the x-axis, a horizontal shift 3 units to the left, and a vertical stretching by a factor of 2.

Q2: To find the time(s) at which the firework reaches a height of 500 feet, we can set the equation h(t) = -16t^2 + 180t + 20 equal to 500 and solve for t:

-16t^2 + 180t + 20 = 500

Rearranging the equation, we get:

-16t^2 + 180t - 480 = 0

Dividing the entire equation by -4, we obtain:

4t^2 - 45t + 120 = 0

Next, we can solve this quadratic equation by factoring, completing the square, or using the quadratic formula. Let's use factoring:

(4t - 15)(t - 8) = 0

Setting each factor equal to zero, we have:

4t - 15 = 0    or    t - 8 = 0

Solving for t in each equation, we get:

t = 15/4    or    t = 8

Therefore, the firework is 500 feet above the ground at two different times: t = 15/4 (or 3.75) seconds and t = 8 seconds.

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It seems like the function f(x) and the interval are not provided in the question. However, I can still give you a general idea of how to approach this problem using the terms Fourier series and period.

Given a function f(x) with a period of 2, we want to show that its Fourier series representation exists on a specified interval. The Fourier series of a periodic function is a representation that combines sine and cosine functions with different frequencies, in the form:

f(x) = a0 + Σ(an * cos(nπx/L) + bn * sin(nπx/L))

Here, L is half the period of the function, which in this case is L = 2/2 = 1.

To determine the Fourier coefficients (an and bn), you'll need to use the following formulas on the given interval:

an = (1/L) * ∫(f(x) * cos(nπx/L) dx) from -L to L

bn = (1/L) * ∫(f(x) * sin(nπx/L) dx) from -L to L

a0 = (1/(2L)) * ∫(f(x) dx) from -L to L

Once you have calculated the coefficients, plug them into the Fourier series formula and check if the representation is accurate on the given interval. This would demonstrate that the Fourier series exists for f(x) on that interval.

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The snowfall in February should be greater than the difference between the average winter snowfall and the sum of snowfall in December and January.

To determine how much snow is required in February to exceed the average winter snowfall, we need to calculate the total snowfall for the three months and compare it to the average.

Let's assume the average winter snowfall for December, January, and February is represented by the variable "A" (in inches).

Given that the city receives "B" inches of snow in December and "C" inches of snow in January, we need to find the snowfall in February, denoted by "D," such that the total snowfall for the three months exceeds the average.

The total snowfall for the three months is given by the sum of the snowfall in each month:

Total snowfall = B + C + D

To exceed the average, we need the total snowfall to be greater than the average:

Total snowfall > A

Substituting the values, we have:

B + C + D > A

To find the required snowfall in February, we isolate the variable "D" on one side of the inequality:

D > A - (B + C)

Therefore, the snowfall in February should be greater than the difference between the average winter snowfall and the sum of snowfall in December and January.

Please note that the values for "A," "B," and "C" need to be provided in order to calculate the required snowfall in February.

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The values of the dummy variable X2 used to indicate the two levels of the qualitative variable are:
Level 1: X2 = 0
Level 2: X2 = 1

To indicate the two levels of the categorical independent variable, let's assign the dummy variable X2 with values of 0 and 1.

Level 1: For level 1 of the categorical variable, we assign X2 = 0.
Level 2: For level 2 of the categorical variable, we assign X2 = 1.

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The type of sampling that was used is a cluster.

furthered explained below

A cluster in a data set occurs when several of the data points have a commonality. The size of the data points has no affect on the cluster just the fact that many points are gathered in one location.

Clusters can be found by examining a graph or dot plot for data points grouped in a certain location. Clusters can also be found by analyzing a data set for a value that most of the data points are near.

In the given question above, each American Airlines flight is a group. 100 of them are chosen randomly, and in each group chosen, every passenger is surveyed. Hence cluster sampling was used.

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To prove that 3 divides n^3 + 2n for any positive integer n, we need to show that there exists an integer k such that n^3 + 2n = 3k.

Let's proceed with the proof using mathematical induction:

Base case:

For n = 1, we have 1^3 + 2(1) = 1 + 2 = 3, which is divisible by 3. So the statement holds true for n = 1.

Inductive hypothesis:

Assume that the statement holds true for some positive integer k, i.e., k^3 + 2k = 3m, where m is an integer.

Inductive step:

We need to prove that the statement holds true for k + 1, i.e., (k + 1)^3 + 2(k + 1) = 3p, where p is an integer.

Expanding the expression (k + 1)^3 + 2(k + 1):

= k^3 + 3k^2 + 3k + 1 + 2k + 2

= (k^3 + 2k) + 3k^2 + 3k + 3

= 3m + 3k^2 + 3k + 3

= 3(m + k^2 + k + 1)

From the inductive hypothesis, we know that k^3 + 2k = 3m. Substituting this in the above expression:

= 3m + 3k^2 + 3k + 3

= 3(m + k^2 + k + 1)

We can see that the expression is a multiple of 3, with (m + k^2 + k + 1) as the coefficient.

Since m, k, and 1 are integers, (m + k^2 + k + 1) is also an integer. Therefore, (k + 1)^3 + 2(k + 1) is divisible by 3.

By using mathematical induction, we have proved that for any positive integer n, 3 divides n^3 + 2n.

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The wavelength of the ripples is approximately 3.6 meters, the frequency is approximately 0.476 cycles/second, and the speed of the ripples is approximately 1.714 meters/second.

Nick and Kara were relaxing on rafts in the shallow waters of Lake Bluebird beach, with a distance of 1.8 meters between them. As a motorboat sped by, it created ripples that propagated towards Nick and Kara. The rafts started to oscillate, experiencing exactly 4 complete cycles of upward and downward motion in a time span of 8.4 seconds. At the high point of Nick's raft, Kara's raft was at its low point, and there were no crests between their rafTo determine the wavelength, frequency, and speed of the ripples, we can use the given information.

The number of complete cycles (up and down motion) is 4, and the time it took for these cycles to occur is 8.4 seconds.

Frequency (f) can be calculated as the number of cycles divided by the time:

f = 4 cycles / 8.4 seconds = 0.476 cycles/second

The wavelength (λ) is the distance between two consecutive crests or troughs. Since there are no crests between Nick and Kara's rafts, the distance between them (1.8 meters) corresponds to half a wavelength (λ/2).

Therefore, the wavelength can be calculated as:

λ = 1.8 meters × 2 = 3.6 meters

The speed of the ripples can be calculated using the formula:

v = λ × f

Substituting the values, we get:

v = 3.6 meters × 0.476 cycles/second ≈ 1.714 meters/second

Therefore, the wavelength of the ripples is approximately 3.6 meters, the frequency is approximately 0.476 cycles/second, and the speed of the ripples is approximately 1.714 meters/second.

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The relationship that exists between the temperature and coffee sales is: y = -x + 26

The general formula for the equation of a line in slope intercept form is:

y = mx + c

where:

m is slope

c is y-intercept

The formula for the equation of a line between two coordinates is:

(y - y₁)/(x - x₁) = (y₂ - y₁)/(x₂ - x₁)

The coordinates we will use here are:

(6, 20) and (23, 3)

Thus:

(y - 20)/(x - 6) = (3 - 20)/(23 - 6)

(y - 20)/(x - 6) = -1

y - 20 = -x + 6

y = -x + 26

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In summary, using the sign test with Table I, the normal approximation to the binomial distribution, and the signed-rank test with Table X, we fail to reject the null hypothesis. There is not enough evidence to conclude that the mean of the population is different from 19.4 minutes.

To perform the sign test at the 0.05 level of significance, we will compare the number of observations above and below the hypothesized mean of 19.4 minutes.

Given the sample data:

18.1, 20.3, 18.3, 15.6, 22.5, 16.8, 17.6, 16.9, 18.2, 17.0, 19.3, 16.5, 19.5, 18.6, 20.0, 18.8, 19.1, 17.5, 18.5, 18.0

Step 1: Count the number of observations above and below 19.4 minutes.

Observations below 19.4 minutes: 9

Observations above 19.4 minutes: 11

Step 2: Determine the critical value using Table I (sign test).

Since the sample size is 20, we need to look at the row for n = 20 in Table I. At the 0.05 level of significance, the critical value is 7.

Step 3: Compare the number of observations below the mean to the critical value.

Since the number of observations below the mean (9) is less than the critical value (7), we do not reject the null hypothesis. There is not enough evidence to conclude that the mean of the population is different from 19.4 minutes.

Alternatively, we can use the normal approximation to the binomial distribution to perform the sign test.

step 1: Calculate the proportion of observations below the mean.

Proportion below the mean = 9/20 = 0.45

Step 2: Calculate the standard error using the formula:

SE = sqrt(p * (1 - p) / n)

= sqrt(0.45 * 0.55 / 20)

≈ 0.098

Step 3: Calculate the test statistic (z-score) using the formula:

z = (p - 0.5) / SE

= (0.45 - 0.5) / 0.098

≈ -0.51

Step 4: Determine the critical value at the 0.05 level of significance.

Using the standard normal distribution table, the critical value for a two-tailed test at the 0.05 level of significance is approximately ±1.96.

Step 5: Compare the test statistic to the critical value.

Since the test statistic (-0.51) falls within the range -1.96 to 1.96, we do not reject the null hypothesis. There is not enough evidence to conclude that the mean of the population is different from 19.4 minutes.

Lastly, to perform the signed-rank test using Table X, we need the absolute differences between the observations and the hypothesized mean.

The absolute differences are:

0.3, 1.1, 1.1, 3.8, 3.1, 2.6, 1.9, 2.5, 1.4, 2.4, 0.1, 2.9, 0.1, 0.8, 0.6, 0.6, 0.3, 1.9, 0.9, 1.4

Step 1: Rank the absolute differences.

Ranking the absolute differences gives us:

1, 16, 16, 20, 18, 19, 17, 21, 15, 22, 3, 23, 3, 8, 6, 6, 1, 17, 7, 15

Step 2: Calculate the sum of the positive ranks and the sum of the negative ranks.

Sum of positive ranks (W+): 187

Sum of negative ranks (W-): 33

Step 3: Calculate the test statistic using the formula:

W = min(W+, W-)

= min(187, 33)

= 33

Step 4: Determine the critical value using Table X.

Since the sample size is 20, we need to look at the row for n = 20 in Table X. At the 0.05 level of significance, the critical value is 44.

Step 5: Compare the test statistic to the critical value.

Since the test statistic (33) is less than the critical value (44), we do not reject the null hypothesis. There is not enough evidence to conclude that the mean of the population is different from 19.4 minutes.

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The correct interpretation of each slope in multiple regression is option b: "The predicted change in the response variable for a one unit increase in that predictor variable, while holding all other predictor variables constant."

This means that for each predictor variable, we are estimating how much the response variable will change when that predictor variable increases by one unit, assuming all other predictor variables remain constant. This allows us to isolate the effect of each predictor variable on the response variable and determine which variables are most important in predicting the response variable.

Option a is incorrect because it assumes that the predictor variable can be equal to 0, which may not be possible or meaningful for all predictor variables. Option c is incorrect because it does not account for the effects of other predictor variables. Option d is incorrect because it refers to the proportion of variability explained by a predictor variable, which is captured by the R-squared statistic, but not by the slope. Option e is partially correct, but the holding of all other predictor variables constant is the key aspect of the interpretation.

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The solution to the differential equation is y = ±ke^(-1/8x^8) where k is an arbitrary constant.

To solve the differential equation (4x^10)dy/dx = x^9y using separation of variables, we can start by rearranging the equation to have all the y terms on one side and all the x terms on the other side.
(4x^10)dy/dx = x^9y
dy/y = (1/4x)dx/x^9
Now we can integrate both sides with respect to their respective variables.
∫ dy/y = ∫ (1/4x)dx/x^9
ln|y| = (-1/8x^8) + c
Where c is the arbitrary constant of integration. We can exponentiate both sides of the equation to solve for y.
|y| = e^((-1/8x^8) + c)
|y| = e^(-1/8x^8) * e^c
Since c is arbitrary, we can replace e^c with another arbitrary constant, k.
|y| = ke^(-1/8x^8)
We can then remove the absolute value by noting that y can be either positive or negative.
y = ±ke^(-1/8x^8)

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(a) Here is a sketch of the normal distribution for the weights of male Persian cats:

```

                   |

                   |

                   |

                   |

                   |

                   |

                   |     . . . . . . . . . . . . . . . . . . . . . .

                   |   .                                               .

                   | .                                                 .

                   |.                                                   .

--------------------|----------------------------------------------------

                μ-3σ           μ             μ+3σ

```

The x-axis represents the weights of the cats, and the y-axis represents the probability density. The curve is symmetric around the mean (μ) and has a standard deviation (σ) of 0.5 kg.

(b) To find the proportion of male Persian cats weighing between 5.5 kg and 6.5 kg, we need to calculate the area under the normal distribution curve between these two weights.

Using statistical software or tables for the normal distribution, we can find the corresponding z-scores for the weights 5.5 kg and 6.5 kg. Let's assume these z-scores are z1 and z2, respectively.

Then, we can find the proportion by subtracting the cumulative probability for z2 from the cumulative probability for z1. This represents the proportion of cats within the weight range.

(c) To determine the expected number of cats in the group that have a weight of less than 5.3 kg, we first need to find the z-score corresponding to this weight. Let's assume this z-score is z3.

Next, we calculate the cumulative probability for z3. This represents the proportion of cats in the population with a weight less than 5.3 kg.

To find the expected number of cats in the group, we multiply this proportion by the total number of cats in the group (80).

(d) To estimate the value of x for the statement "12 of the cats weigh more than x kg," we need to find the z-score corresponding to the cumulative probability of 12 cats in a group of 80.

Using statistical software or tables for the normal distribution, we can find the z-score that corresponds to this cumulative probability.

Then, we can convert the z-score back to the weight scale to estimate the value of x.

(e) To find the probability that exactly one cat out of ten weighs over 6.25 kg, we can use the binomial probability formula:

[tex]P(X = 1) = (nCk) * p^k * (1-p)^{(n-k)}[/tex]

In this case, n = 10 (number of cats chosen), k = 1 (number of cats weighing over 6.25 kg), and p represents the probability of a cat weighing over 6.25 kg, which can be calculated using the normal distribution and the corresponding z-score.

By substituting these values into the formula, we can calculate the probability.

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Answer:

5x10^6

Step-by-step explanation:

[tex] \sf {3x}^{2} - 11x - 4 = 0[/tex]

[tex] \sf {3x}^{2} + x - 12x- 4[/tex]

[tex] \sf x(3x + 1) - 4(3x + 1)[/tex]

[tex] \sf (x- 4)(3x + 1)[/tex]

[tex]\sf x=4\: and\: x= \frac{-1}{3}[/tex]

The two solutions in the interval [0, π/2] are:

x = π/2

x = π/6

To solve the equation 5 cos x - 10 sin x cos x = 0 in the interval [0, π/2], we can manipulate the equation to isolate the variable x.

Starting with the given equation:

5 cos x - 10 sin x cos x = 0

We can factor out the common term cos x:

cos x (5 - 10 sin x) = 0

Now we have two possibilities:

cos x = 0

5 - 10 sin x = 0

For the first possibility, cos x = 0, we know that the cosine function equals zero at x = π/2.

For the second possibility, 5 - 10 sin x = 0, we can solve for sin x:

10 sin x = 5

sin x = 1/2

We know that sin x equals 1/2 at x = π/6 in the interval [0, π/2].

So, the two solutions in the interval [0, π/2] are:

x = π/2

x = π/6

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The multiplicative inverse of a number [tex]x[/tex] is [tex]\dfrac{1}{x}[/tex].

[tex]x=11\mod 26=11[/tex]

Therefore

[tex]\dfrac{1}{x}=\dfrac{1}{11}[/tex]

An impulse response is a system's output when an impulse input is applied. In this case, the given LTI system has an impulse response of ℎ() = −(−2)( − 2).

This means that when an impulse input is applied, the system's output will be a scaled and shifted version of the function ℎ(). Specifically, the output will be a scaled and shifted version of the function −(−2)( − 2).

It's worth noting that the impulse response of an LTI system contains all the information necessary to describe its behavior. By convolving the input signal with the impulse response, we can determine the system's output for any input signal.

So, if we have a specific input signal, we can convolve it with the given impulse response to determine the system's output. But for an impulse input, we already know that the output will be a scaled and shifted version of ℎ().

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The forecasting method that is appropriate when the time series has no significant trend, cyclical, or seasonal effect is (d) moving averages.

This method calculates the average of the deviations of the actual values from the mean value. It is a simple and easy-to-use method that does not require any complex statistical calculations. The mean average deviation is calculated by adding up the absolute values of the deviations from the mean, and then dividing by the total number of observations. This method is useful when the data is relatively stable and does not exhibit any significant fluctuations or trends. It provides a good estimate of the central tendency of the data and can be used as a basis for further analysis. However, it is important to note that the mean average deviation is not suitable for data with outliers or extreme values, as it can be heavily influenced by these values.

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In the simple linear regression model, the equation y = β0 + β1x + ɛ implies that if x goes up by one unit, we expect y to change by β1 units, irrespective of the value of x.

This means that for every one unit increase in x, we expect a β1 unit increase (or decrease, depending on the sign of β1) in y. This is the slope of the regression line and represents the average change in y for every unit change in x. It is important to note that this relationship between x and y assumes a linear relationship, and that the error term ɛ represents the variation in y that is not explained by x. Therefore, the estimate of β1 is based on the variability of the data and the strength of the relationship between x and y.

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The pair of equations that would have (-1, 2) as a solution is (3) y = x² - 3x - 2 and y = 4x + 6.

To determine which pair of equations would have (-1, 2) as a solution, we can substitute the values x = -1 and y = 2 into each equation and see which pair satisfies both equations.

Let's test each option:

(1) y = x + 3 and y = 2^x:

Substituting x = -1 and y = 2 into the first equation:

2 = -1 + 3

2 = 2 (correct)

Substituting x = -1 and y = 2 into the second equation:

2 = 2^-1

2 = 1/2 (not correct)

(2) y = x - 1 and y = 2x:

Substituting x = -1 and y = 2 into the first equation:

2 = -1 - 1

2 = -2 (not correct)

Substituting x = -1 and y = 2 into the second equation:

2 = 2(-1)

2 = -2 (not correct)

(3) y = x² - 3x - 2 and y = 4x + 6:

Substituting x = -1 and y = 2 into the first equation:

2 = (-1)² - 3(-1) - 2

2 = 1 + 3 - 2

2 = 2 (correct)

Substituting x = -1 and y = 2 into the second equation:

2 = 4(-1) + 6

2 = -4 + 6

2 = 2 (correct)

(4) 2x + 3y = -4 and y :

Substituting x = -1 and y = 2 into the first equation:

2(-1) + 3(2) = -4

-2 + 6 = -4

4 = -4 (not correct)

Based on the tests, the pair of equations (3) y = x² - 3x - 2 and y = 4x + 6 would have (-1, 2) as a solution.

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We cannot determine the truth value of any of the statements given, as sets $B$ and $C$ are not defined in the context of the question.

Let's analyze each statement using the given terms and the set $A = \{a, b, \{a, b\}\}$:
A) $B \in C$
There is not enough information to evaluate this statement, as the sets $B$ and $C$ are not defined. We cannot determine if it is true or false
B) $C \subset P(A)$
Again, the set $C$ is not defined. Therefore, we cannot determine if it is a subset of the power set $P(A)$ or not.
C) $B \in A$
As previously mentioned, the set $B$ is not defined, so we cannot determine if it is an element of set $A$.
D) $B \subset A$
Without knowing the elements of set $B$, we cannot determine if it is a subset of set $A$.
In conclusion, we cannot determine the truth value of any of the statements given, as sets $B$ and $C$ are not defined in the context of the question.

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Answer: descriptive statistics

Step-by-step explanation: The average age of everyone in the class is an example of descriptive statistics.

Answer:

1

Step-by-step explanation:

x = ky², where k is a constant.

108 = k(3)² = 9k

k = 108/9 = 12.

x = ky²

12 = 12y²

y = 1

Answer :

Properties of parallelogram :

As per question AB and CD are opposite sides.

Since AB and CD are equal sides So, BC and AD must be equal.

AD = BC

[tex]\sf 3x - 2 = x + 8[/tex]

[tex]\sf 3x - x = 8 + 2 [/tex]

[tex]\sf 2x = 10 [/tex]

[tex]\sf x = \dfrac{10}{2}[/tex]

[tex]{\boxed{\sf {x = 5 }}}[/tex]

BC = x + 8 = 5 + 8 = 13

AD = 3x -2 = 3(5)- 2 = 15 - 2 = 13

In conclude we get BC and AD are equal sides.

Therefore for x = 5 the given quadrilateral ABCD is a parallelogram.

Hello !

A parallelogram has its opposite sides equal.

So BC must be equal to AD (AB and CD are already equal)

[tex]x + 8 = 3x - 2\\\\8 + 2 = 3x - x\\\\10 = 2x\\\\x = 10/2\\\\\boxed{x = 5}[/tex]

If x = 5, the quadrilateral ABCD is a parallelogram.

Answer:

it is a wrong question because the cannot not be fish chips 7c the cn onl be 0.67c

To compute the orthogonal projection of q onto the subspace spanned by p, we need to first find the projection vector. Let's call this projection vector v. We know that v must be orthogonal to the error vector e, where e is the difference between q and the projection of q onto the subspace spanned by p.

We can express v as a scalar multiple of p, so let's write v as v = ap, where a is a scalar. Then, using the inner product given by evaluation at −1, 0, and 1, we have:
=  =
Since we want v to be orthogonal to e, we need  to be 0. So, we have:
= 0
Expanding this out, we get:
2(6 - a) - 10/3(1 - a^2) = 0
Simplifying and solving for a, we get:
a = 3/5
So, v = 3/5p = 6/5t. Therefore, the orthogonal projection of q onto the subspace spanned by p is:
proj_p(q) = /||v||^2 * v = 9/5 - 18/5t

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By introducing an additional association between an input value and multiple output values, such as assigning 4 to both 1 and 3, we can make the relation not represent a function.

In order for a relation to represent a function, each input value (x) must have a unique corresponding output value (y). If there is any input value that is associated with multiple output values, the relation does not represent a function.

Looking at the given table:

Input: 7 7 4 5

Output: 2 5 1 2

We can see that the input value of 7 is associated with two different output values, 2 and 5. This violates the requirement for a function because an input value should have only one corresponding output value.

To make the relation not represent a function, we need to choose a value that will introduce another instance where an input value is associated with multiple output values.

Let's choose an input value that already exists in the table, such as 4. Currently, the input value 4 is associated with an output value of 1. To make the relation not represent a function, we can associate 4 with another output value, let's say 3.

Updated relation:

Input: 7 7 4 4 5

Output: 2 5 1 3 2

Now, the input value of 4 is associated with two different output values, 1 and 3. Therefore, the relation does not represent a function.

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The true statement about angle x is determined as x + 30 = 180 .

option D.

Corresponding angles in geometry are defined as the angles which are formed at corresponding corners when two parallel lines are intersected by a transversal.

From the given two parallel lines m and n, we can conclude the following;

angle formed by the intersection of line a and m = x ( corresponding angles are equal).

the angle formed by the intersection of line b and m, above angle 30 = x ( corresponding angles are equal)

So the angle on the same straight line with 30 is angle x

x + 30 = 180 ( sum of angles on a straight line)

x = 180 - 30

x = 150⁰

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