The statement is generally true.
What is bionomial distribution?The binomial distribution is a probability distribution that describes the number of successes in a fixed number of independent trials, where each trial can either result in a success or a failure
According to the given information:
The statement is generally true. According to the Central Limit Theorem, as the sample size increases, the distribution of sample means approaches a normal distribution. In the case of a binomial distribution, the sample mean represents the proportion of successes in the sample. Therefore, when the sample size is large enough (typically n ≥ 30), the distribution of sample proportions closely approximates a normal distribution, and the mean and standard deviation of the sample proportion can be used to approximate the mean and standard deviation of a normal distribution. However, there may be cases where the normal approximation is not appropriate due to skewness or other factors, so it is always important to consider the context and assumptions of the problem.
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To indirectly measure the distance across a lake, Nachelle makes use of a couple landmarks at points D and E. She measures CF, FD, and FG as marked. Find the distance across the lake (DE), rounding your answer to the nearest hundredth of a meter
The distance across the lake (DE) is 207.68 m.
How to find the distance across the lake (DE)?The corresponding side lengths of two triangles that are similar are always proportional to each other.
Thus,
ΔCDE and ΔCFG are similar to each other
FG = 142.1 m
FC = 130 m
DF = 60 m
DC = 130 + 60 = 190 m
Thus, DE/FG = DC/FC
Substituting
DE/142.1 = 190/130
DE = (190*142.1)/130
DE = 207.68 m (nearest hundredth).
Therefore, the distance across the lake (DE) to the nearest hundredth is 207.68 m.
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Complete Question
Check attached image
Answer the questions below to find the total surface area of the can.
(Help fast please)
The calculated value of the total surface area of the can is 9.54 square cm
Calculating total surface area of the can.From the question, we have the following parameters that can be used in our computation:
The can
To calculate the total surface area of a net, you need to add up the areas of all its faces.
The shapes in the can are
Rectangle of: 1.5 by 4Pair of Circles of radius = 0.75Using the above as a guide, we have the following:
Area = 1.5 * 4 + 2 * (22/7 * 0.75^2)
Evaluate
Area = 9.54
Hence, the surface area is 9.54 square cm
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Pls help (part 3)
Give step by step explanation!
The total area to be painted is 886.5 cm².
The volume of the object is 1,834.5 cm³.
What is the total area to be painted?
The total area to be painted is calculated by subtracting the area of he circular hole from total surface area of the prism.
Total area of the prism is calculated as;
S.A = bl + (s₁ + s₂ + s₃)l
where;
b is the base of the trianglel is the length of the triangles is the faces of the triangleS.A = (16 x 20) + (16 + 17 + 17) x 20
S.A = 1,320 cm²
The circular area of the hole is calculated as;
A = 2πr(r + h)
A =2π x 3(3 + 20)
A = 433.54 cm²
Area to be painted = 1,320 cm² - 433.54 cm² = 886.5 cm²
The volume of the object is calculated as;
V = (¹/₂blh) - πr²h
V = (¹/₂ x 16 x 20 x 15) - π(3)²(20)
V = 1,834.5 cm³
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Solve the system using substitution. Check your solution
4x-y=62
2y=x
Answer:
(x, y) (124/7, 62/7)
Step-by-step explanation:
substitute x with 2y we get
4(2y)-y=62
8y-y=62
7y=62
y=62/7
substitute the value of y into the second eqaution
2(62/7)=x
124/7=x
substitute your values of x and y into the first eqaution to check if they are solutions
4(124/7)-62/7=62
you will get
62=62
which means they are solutions
Answer the question below in the picture. Thank you! Have a wonderful day.
Answer:
1) Statistical
2)Not statistical
3)Not statistical
Step-by-step explanation:
If your not sure just visit it will tell you the answers.
Hope it helps!!
suppose z has a standard normal distribution with a mean of 0 and standard deviation of 1. the probability that z is between -2.33 and 2.33 is
The probability that z is between -2.33 and 2.33 for a standard normal distribution with a mean of 0 and standard deviation of 1 is approximately 0.9802, or 98.02%. Here, he probability that z is between -2.33 and 2.33 for a standard normal distribution with a mean of 0 and a standard deviation of 1, you'll need to use a standard normal distribution table or a calculator with a built-in z-table function.
Step-by-step explanation:
Step:1. Identify the given values: Mean (µ) = 0, Standard Deviation (σ) = 1, and the range of z-scores is between -2.33 and 2.33.
Step:2. Use a standard normal distribution table or a calculator with a built-in z-table function to find the probabilities associated with z = -2.33 and z = 2.33.
Step:3. Look up the probability of z = -2.33 in the table, which should be approximately 0.0099.
Step:4. Look up the probability of z = 2.33 in the table, which should be approximately 0.9901.
Step:5. Subtract the probability for z = -2.33 from the probability for z = 2.33 to find the probability of z being between these two values: P(-2.33 < z < 2.33) = P(z = 2.33) - P(z = -2.33) = 0.9901 - 0.0099 = 0.9802
The probability that z is between -2.33 and 2.33 for a standard normal distribution with a mean of 0 and standard deviation of 1 is approximately 0.9802, or 98.02%.
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Potential real GDP is equal to $10,000 and the current level of real GDP is equal to $9,000. The output gap is therefore equal to: Select one: a.
The output gap, which represents the difference between potential real GDP and the current level of real GDP, is equal to $1,000.
Step 1: Potential real GDP refers to the maximum level of output that an economy can produce without generating inflation. In this case, it is given as $10,000.
Step 2: Current level of real GDP refers to the actual output produced by the economy at a given point in time. In this case, it is given as $9,000.
Step 3: To calculate the output gap, we subtract the current level of real GDP from the potential real GDP: $10,000 - $9,000 = $1,000.
Therefore, the output gap is equal to $1,000, which represents the difference between potential real GDP and the current level of real GDP.
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when testing partial correlation, the impact of a third variable is ______.a. addedb. removedc. deletedd. reduced
When testing partial correlation, the impact of a third variable is removed.
Partial correlation is a statistical technique used to measure the relationship between two variables while controlling for the effect of one or more additional variables, known as "covariates" or "control variables." By removing the effect of the covariates, the partial correlation measures the direct relationship between the two variables of interest. This technique is useful when we want to examine the relationship between two variables after accounting for the effect of one or more confounding variables.
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use newton's method to approximate the indicated solution of the equation correct to six decimal places. the positive solution of e3x = x 7
the positive solution of e³ˣ= x⁷ is approximately 0.411582.
How to solve the question?
To use Newton's method, we first need to have a function whose root we want to find. In this case, we want to find the positive solution of the equation e³ˣ= x⁷. Let's define f(x) =e³ˣ- x⁷
Now we need to choose a starting point for the iteration. Let's choose x_0 = 1.
The iterative formula for Newton's method is:
x_n+1 = x_n - f(x_n)/f'(x_n)
where f'(x) is the derivative of f(x). In this case, f(x) = e³ˣ- x⁷, so
f'(x) = 3e³ˣ- 7x⁶.
Now we can apply the formula to find x_1:
x_1 = x_0 - f(x_0)/f'(x_0) = 1 - (e³ - 1)/20.0855 = 0.408294
We continue iterating until we reach the desired level of accuracy. For example, to find x_2, we use x_1 as the starting point:
x_2 = x_1 - f(x_1)/f'(x_1) = 0.408294 - (-0.00883753)/3.41171 = 0.411794
We can repeat this process until we reach the desired level of accuracy. For example, after a few more iterations, we get:
x_3 = 0.411582
x_4 = 0.411582
x_5 = 0.411582
We can see that the approximation has converged to 0.411582. To check our answer, we can substitute this value into the original equation:
e to the power (3*0.411582) - 0.41158⁷ = 0.000001
This is very close to zero, so our answer is correct to at least six decimal places. Therefore, the positive solution of e³ˣ= x⁷is approximately 0.411582.
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the positive solution of e³ˣ= x⁷ is approximately 0.411582.
How to solve the question?
To use Newton's method, we first need to have a function whose root we want to find. In this case, we want to find the positive solution of the equation e³ˣ= x⁷. Let's define f(x) =e³ˣ- x⁷
Now we need to choose a starting point for the iteration. Let's choose x_0 = 1.
The iterative formula for Newton's method is:
x_n+1 = x_n - f(x_n)/f'(x_n)
where f'(x) is the derivative of f(x). In this case, f(x) = e³ˣ- x⁷, so
f'(x) = 3e³ˣ- 7x⁶.
Now we can apply the formula to find x_1:
x_1 = x_0 - f(x_0)/f'(x_0) = 1 - (e³ - 1)/20.0855 = 0.408294
We continue iterating until we reach the desired level of accuracy. For example, to find x_2, we use x_1 as the starting point:
x_2 = x_1 - f(x_1)/f'(x_1) = 0.408294 - (-0.00883753)/3.41171 = 0.411794
We can repeat this process until we reach the desired level of accuracy. For example, after a few more iterations, we get:
x_3 = 0.411582
x_4 = 0.411582
x_5 = 0.411582
We can see that the approximation has converged to 0.411582. To check our answer, we can substitute this value into the original equation:
e to the power (3*0.411582) - 0.41158⁷ = 0.000001
This is very close to zero, so our answer is correct to at least six decimal places. Therefore, the positive solution of e³ˣ= x⁷is approximately 0.411582.
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The positive solution of the equation [tex]e^{3x}=x^7[/tex]is approximately 0.411582.
How to use Newton method?
To use Newton's method, we first need to have a function whose root we want to find. In this case, we want to find the positive solution of the equation[tex]e^{3x}=x^7[/tex]. Let's define f(x) =[tex]e^{3x}-x^7[/tex]
Now we need to choose a starting point for the iteration. Let's choose
[tex]x_0[/tex] = 1.
The iterative formula for Newton's method is:
[tex]x_{n+1} = x_n -\frac{ f(x_n)}{f'(x_n)}[/tex]
where f'(x) is the derivative of f(x). In this case, f(x) = [tex]e^{3x}-x^7[/tex], so
=> f'(x) = [tex]3e^{3x}- 7x^6.[/tex]
Now we can apply the formula to find [tex]x_1:[/tex]
=> [tex]x_1 = x_0 -\frac{ f(x_0)}{f'(x_0)} = 1 - \frac{(e^3 - 1)}{20.0855} = 0.408294[/tex]
We continue iterating until we reach the desired level of accuracy. For example, to find [tex]x_2[/tex], we use [tex]x_1[/tex] as the starting point:
=> [tex]x_2 = x_1 - \frac{f(x_1)}{f'(x_1)} = 0.408294 - \frac{(-0.00883753)}{3.41171} = 0.411794[/tex]
We can repeat this process until we reach the desired level of accuracy. For example, after a few more iterations, we get:
=> [tex]x_3 = 0.411582[/tex]
=> [tex]x_4 = 0.411582[/tex]
=> [tex]x_5 = 0.411582[/tex]
We can see that the approximation has converged to 0.411582. To check our answer, we can substitute this value into the original equation:
=> [tex]e^{(3*0.411582)} - 0.41158^7 = 0.000001[/tex]
This is very close to zero, so our answer is correct to at least six decimal places. Therefore, the positive solution of [tex]e^{3x}=x^7[/tex]is approximately 0.411582.
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The positive solution of the equation [tex]e^{3x}=x^7[/tex]is approximately 0.411582.
How to use Newton method?
To use Newton's method, we first need to have a function whose root we want to find. In this case, we want to find the positive solution of the equation[tex]e^{3x}=x^7[/tex]. Let's define f(x) =[tex]e^{3x}-x^7[/tex]
Now we need to choose a starting point for the iteration. Let's choose
[tex]x_0[/tex] = 1.
The iterative formula for Newton's method is:
[tex]x_{n+1} = x_n -\frac{ f(x_n)}{f'(x_n)}[/tex]
where f'(x) is the derivative of f(x). In this case, f(x) = [tex]e^{3x}-x^7[/tex], so
=> f'(x) = [tex]3e^{3x}- 7x^6.[/tex]
Now we can apply the formula to find [tex]x_1:[/tex]
=> [tex]x_1 = x_0 -\frac{ f(x_0)}{f'(x_0)} = 1 - \frac{(e^3 - 1)}{20.0855} = 0.408294[/tex]
We continue iterating until we reach the desired level of accuracy. For example, to find [tex]x_2[/tex], we use [tex]x_1[/tex] as the starting point:
=> [tex]x_2 = x_1 - \frac{f(x_1)}{f'(x_1)} = 0.408294 - \frac{(-0.00883753)}{3.41171} = 0.411794[/tex]
We can repeat this process until we reach the desired level of accuracy. For example, after a few more iterations, we get:
=> [tex]x_3 = 0.411582[/tex]
=> [tex]x_4 = 0.411582[/tex]
=> [tex]x_5 = 0.411582[/tex]
We can see that the approximation has converged to 0.411582. To check our answer, we can substitute this value into the original equation:
=> [tex]e^{(3*0.411582)} - 0.41158^7 = 0.000001[/tex]
This is very close to zero, so our answer is correct to at least six decimal places. Therefore, the positive solution of [tex]e^{3x}=x^7[/tex]is approximately 0.411582.
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Debbie and her friends are making snack mix. They use 1/3 cup of oat cereal and 2/3 cup corn cereal for each bag. How many cups of cereal do they use for each snack bag?
Answer: 1 cup
Step-by-step explanation:
1/3 + 2/3= 1
A 16 ounce box of pasta costs $1.12. A 32 ounce box cost 1.92. A 5 pound box cost $4.00. Which box is the best deal?
Answer:
To find the best deal, we must get the value of 1 oz for each of the boxes.
Box 1: 1.12 divided by 16 equals 0.07 / oz
Box 2: 1.92/32 equals 0.06 / oz
5 LB Box = 80 OZ
Box 3: 4/80 = 0.05 / oz
The third box is the best deal.
If X and Y are mutually exclusive events with P(X) = 0.295, P(Y) = 0.32, then P(X ½ Y) =
a. 0.0000 b. 0.6150 c. 1.0000 d. 0.0944
The answer is b. 0.6150. Since X and Y are mutually exclusive events, they cannot occur at the same time. Therefore, P(X ½ Y) = P(X or Y) = P(X) + P(Y) = 0.295 + 0.32 = 0.6150.
If X and Y are mutually exclusive events, it means they cannot occur at the same time. In this case, P(X) = 0.295 and P(Y) = 0.32. The probability of the union of two mutually exclusive events, denoted as P(X ∪ Y), is the sum of their individual probabilities. Therefore, P(X ∪ Y) = P(X) + P(Y) = 0.295 + 0.32 = 0.615. So, the answer is: b. 0.6150
Probability distribution refers to a type of probability distribution in which the probability distribution is defined by the probability distribution's parameters. The parameters are usually numeric values that define the distribution's probability density function (PDF) or probability mass function (PMF).The probability distribution is usually used to model a population's characteristics.
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give the laplace transofrm of -6 0<=x and x
The Laplace transform of -6 for the given conditions is -6/s + 1/s^2
The Laplace transform is a mathematical operation that transforms a function of time into a function of a complex variable s, commonly used in solving linear ordinary differential equations. The Laplace transform of a function f(t), denoted by L{f(t)}, is defined as:
L{f(t)} = F(s) = ∫[f(t)e^(-st)]dt, where s is a complex variable.
In this case, the given function is -6 for 0<=x and x. Since the function is constant, it can be represented as a step function, where the value of the function changes abruptly at x=0. The step function is denoted as u(x), where u(x) = 0 for x<0, and u(x) = 1 for x>=0.
So, the given function can be written as -6u(x), where u(x) is the step function.
Now, applying the definition of the Laplace transform, we get:
L{-6u(x)} = ∫[-6u(x)e^(-sx)]dx
Since u(x) = 0 for x<0, the integral becomes:
L{-6u(x)} = ∫[0*e^(-sx)]dx = 0
Since u(x) = 1 for x>=0, the integral becomes:
L{-6u(x)} = ∫[-6*e^(-sx)]dx = -6∫[e^(-sx)]dx
Integrating e^(-sx) with respect to x, we get:
L{-6u(x)} = -6 * (-1/s) * e^(-sx) + C, where C is the constant of integration.
Finally, substituting back u(x) = 1, we get:
L{-6u(x)} = -6 * (-1/s) * e^(-sx) + C = 6/s * e^(-sx) + C
So, the Laplace transform of -6 for the given conditions is -6/s * e^(-sx) + C, which can also be written as -6/s + C/s, where C is a constant.
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Find the perimeter of the triangle:
The perimeter is 58.9
How to find the perimeter?Here we have an isosceles triangle.
To find the length of the sides that aren't the base we can use a trigonometric equation.
sin(60°) = 4*√15/hypotenuse
hypotenuse = 4*√15/sin(60°) = 18.8
The side in the left also measures that.
Now we need the base, we can define the base as:
(b/2)² + (4√15)² = 18.8²
b²/4 + 16*15 = 18.8²
b = √((18.8² - 16*15)*4)
b = 21.3
Then the perimeter is:
21.3 + 18.8 + 18.8 = 58.9
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Priscilla can make 3 bracelets in 15 minutes. At this rate, how many bracelets can she make in 45 minutes?
Answer:
9
Step-by-step explanation:
because if she can make 3 in 15minutes then 45 minutes is triple the time so triple the bracelets please give brainliest bye have a good day :D
The areas of 10 cities are given in the table.
How much greater is the range for the cities in the south than the cities in the north?
Enter your answer in the box.
mi²
Northern Cities Southern Cities
Portland 145 mi² Orlando 111 mi²
Seattle 84 mi² New Orleans 350 mi²
New York City 305 mi² Los Angeles 503 mi²
Detroit 143 mi² San Diego 372 mi²
Minneapolis 58 mi² Atlanta 132 mi²
The range for the southern cities is 145 mi² greater than the range for the northern cities.
How to find the range of the cities?We must determine the difference between the largest and smallest areas in each group in order to determine the range of the cities.
Minneapolis has the smallest area (58 miles2) and the largest (305 miles2) of the northern cities. Therefore, the northern cities' range is:
305 mi² - 58 mi² = 247 mi²
For the southern cities, the smallest area is 111 mi² (Orlando) and the largest area is 503 mi² (Los Angeles). So the range for the southern cities is:
503 mi² - 111 mi² = 392 mi²
To find how much greater the range is for the southern cities, we subtract the range for the northern cities from the range for the southern cities:
392 mi² - 247 mi² = 145 mi²
As a result, the cities in the south have a range that is 145 miles longer than the cities in the north.
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calculate the poh of 490 ml of a 0.81 m aqueous solution of ammonium chloride (nh4cl) at 25 °c given that the kb of ammonia (nh3) is 1.8×10-5.
The pOH of the 0.81 M aqueous solution of ammonium chloride (NH4Cl) at 25 °C is approximately 4.74.
To calculate the pOH of a 0.81 M aqueous solution of ammonium chloride (NH4Cl), we first need to find the concentration of hydroxide ions (OH-) using the Kb of ammonia (NH3). Here's a step-by-step explanation:
1. Write the dissociation reaction of NH4Cl in water and the equilibrium reaction of NH3 with water:
NH4Cl → NH4+ + Cl-
NH3 + H2O ⇌ NH4+ + OH-
2. Since NH4Cl is a strong electrolyte, its concentration will be equal to the initial concentration of NH4+. Therefore, [NH4+]initial = 0.81 M. Assume that x moles of OH- is formed at equilibrium, so [OH-] = x and [NH4+] = 0.81 - x.
3. Write the Kb expression for the equilibrium reaction:
Kb = [NH4+][OH-] / [NH3]
4. Substitute the given Kb value and the concentrations from step 2:
1.8×10⁻⁵ = (0.81 - x)(x) / [NH3]
5. Since NH4Cl dissociates completely, we can assume that the initial concentration of NH3 is also 0.81 M. Since x is small compared to 0.81, we can simplify the equation:
1.8×10⁻⁵ ≈ (0.81)(x) / 0.81
6. Solve for x, which is the concentration of OH-:
x ≈ 1.8×10⁻⁵
7. Calculate the pOH using the formula pOH = -log[OH-]:
pOH = -log(1.8×10⁻⁵) ≈ 4.74
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In the Picture. :) Ty
a) Amount of increase after the two years is: $6,772.5
b) The tuition fee after 10 years will cost approximately: $84957
How to solve exponential equation word problems?The general form of exponential growth equation is
y = a(1 + r)^x
where:
a = initial amount
r = growth rate
x = number of intervals
we are given:
Initial cost = $21000
Percentage increase = 15% in two years
Thus:
Amount in 2010 = 21000(1 + 0.15)²
= $27,772.5
Amount of increase = 27,772.5 - 21000 = $6,772.5
In ten years time, the tuition fee will be:
21000(1 + 0.15)¹⁰ = 84,956.71245 ≅ $84957
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Zach bought 200 shares of Goshen stock years ago for $21.35 per share. He sold all 200 shares today for $43 per share. What was his gross capital gain?
Answer: 8,600
Zach's gross capital gain can be calculated as follows:
Total proceeds from selling the stock = 200 shares x $43/share = $8,600
Total cost of buying the stock = 200 shares x $21.35/share = $4,270
Gross capital gain = Total proceeds - Total cost = $8,600 - $4,270 = $4,330
Therefore, Zach's gross capital gain from selling 200 shares of Goshen stock is $4,330.
How to evaluate this surface integral ∬Te(y−x)/(y+x)dA where T is the triangular region with vertices (0,0), (1,0) and (0,1)?
The value of the surface integral is (1 - ln(2))/2.
To evaluate the given surface integral ∬Te(y−x)/(y+x)dA over the triangular region T with vertices (0,0), (1,0) and (0,1), we can use the change of variables formula for surface integrals. Let u = y - x and v = y + x be the new variables, then the transformation (x, y) → (u, v) is a linear transformation with Jacobian determinant |J| = 2. The inverse transformation is given by x = (v - u)/2 and y = (v + u)/2.
The triangular region T in (x, y) coordinates corresponds to the parallelogram region R in (u, v) coordinates with vertices (0,0), (0,1), (1,-1) and (1,0), as shown below:
(1,0) T (1,-1) R
/\ /\
/ \ / \
/____\ /____\
(0,0) (0,1) (0,0) (1,0)
The surface integral can be written as:
∬Te(y−x)/(y+x)dA = ∬R(u/v)(1/2)|J|dudv
Substituting the Jacobian determinant and limits of integration, we get:
∬Te(y−x)/(y+x)dA = ∫0^1 ∫-u+1^1-u u/v du dv
Integrating with respect to u first and then with respect to v, we get:
∬Te(y−x)/(y+x)dA = ∫0^1 (ln(2) - ln(v)) dv = (1 - ln(2))/2
Therefore, the value of the surface integral is (1 - ln(2))/2.
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Widely known kite ABCD
35cm^2
. Gerrard made a kite
with the length of each diagonal
each twice the length of the diagonal of the kite
ABCD kite. Calculate the area of the kite
the new one !
The area of the kite the new one is 70 cm^2.
Calculating the area of the kite the new oneThe area of a kite is given by half the product of its diagonals. Let's call the diagonals of kite ABCD d1 and d2, and the diagonals of the new kite d1' and d2'.
We know that d1' = 2d1 and d2' = 2d2, so we can write:
Area of new kite = 1/2 * d1' * d2'
= 1/2 * (2d1) * (2d2)
= 2 * (1/2 * d1 * d2)
= 2 * Area of kite ABCD
= 2 * 35 cm^2
= 70 cm^2
Therefore, the area of the new kite is 70 cm^2.
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is 132 divisible by 3
Answer:
yes clearly
Step-by-step explanation:
using rules of divisibility it is divisible
using your calculator it is divisible
the answer is 44
Consider a linear model of the form:
y(x,theta)=theta0+∑=1thetaxy(xn,θ)=θ0+∑d=1Dθdxnd
where x=(x1,...,x)xn=(xn1,...,xnD) and weights theta=(theta0,...,theta)θ=(θ0,...,θD). Given the the D-dimension input sample set x={x1,...,x}x={x1,...,xn} with corresponding target value y={y1,...,y}y={y1,...,yn}, the sum-of-squares error function is:
(theta)=12∑=1{y(x,theta)−y}2ED(θ)=12∑n=1N{y(xn,θ)−yn}2
Now, suppose that Gaussian noise ϵn with zero mean and variance 2σ2 is added independently to each of the input sample xxn to generate a new sample set x′={x1+1,...,x+}x′={x1+ϵ1,...,xn+ϵn}. For each sample xxn, x′=(x1+1,...,x+)xn′=(xn1+ϵn1,...,xnD+ϵnd), where n and d is independent across both n and d indices.
(3pts) Show that y(x′,theta)=y(x,theta)+∑=1thetay(xn′,θ)=y(xn,θ)+∑d=1Dθdϵnd
Assume the sum-of-squares error function of the noise sample set x′={x1+1,...,x+}x′={x1+ϵ1,...,xn+ϵn} is (theta)′ED(θ)′. Prove the expectation of (theta)′ED(θ)′ is equivalent to the sum-of-squares error (theta)ED(θ) for noise-free input samples with the addition of a weight-decay regularization term (e.g. 2L2 norm) , in which the bias parameter theta0θ0 is omitted from the regularizer. In other words, show that
[(theta)′]=(theta)+z
Step-by-step explanation:
Part 1:
We know that y(x,θ) = θ0 + ∑d=1Dθdxnd and x′n = xn + ϵn.
So,
y(x′,θ) = θ0 + ∑d=1Dθd(xnd+ϵnd)
= θ0 + ∑d=1Dθdxnd + ∑d=1Dθdϵnd
Since ϵn is independent of the weights θ, we can take it outside the summation:
y(x′,θ) = y(x,θ) + ∑d=1Dθdϵnd
Therefore, we have shown that y(x′,θ) = y(x,θ) + ∑d=1Dθdϵnd.
Part 2:
The sum-of-squares error function for the noise sample set x′ is given by:
ED'(θ) = 1/2 ∑n=1N [y(x′n,θ) - yn]^2
Using the expression for y(x′,θ) derived in part 1, we have:
ED'(θ) = 1/2 ∑n=1N [y(xn,θ) + ∑d=1Dθdϵnd - yn]^2
Expanding the square term and taking the expectation with respect to the noise ϵ, we get:
E[ED'(θ)] = E[1/2 ∑n=1N [(y(xn,θ) - yn)^2 + 2(y(xn,θ) - yn)∑d=1Dθdϵnd + (∑d=1Dθdϵnd)^2]]
Now, since ϵ is a zero-mean Gaussian noise with variance 2σ^2, we have:
E[ϵnd] = 0
E[ϵnd^2] = σ^2
Using these properties, we can simplify the above expression:
E[ED'(θ)] = E[1/2 ∑n=1N [(y(xn,θ) - yn)^2 + 2(y(xn,θ) - yn)∑d=1DθdE[ϵnd] + (∑d=1Dθd^2E[ϵnd^2])]]
= E[1/2 ∑n=1N (y(xn,θ) - yn)^2] + E[θ]^T E[Z] E[θ]
where Z is a (D-1) x (D-1) matrix with (i,j)-th element being E[ϵiϵj], and E[Z] is the matrix obtained by adding σ^2 to the diagonal elements of Z. The terms involving the cross-product of ϵ are ignored as they are zero.
The first term in the above expression is just the sum-of-squares error for the noise-free input samples. The second term is the weight-decay regularization term, which is proportional to the L2 norm of the weights θ, with the bias parameter θ0 omitted.
Therefore, we have shown that:
E[ED'(θ)] = (theta)^T(theta) + z
where z is the weight-decay regularization term.
6) One hundred tickets numbered 1,2,3,...,100, are sold to 100 different people for a drawing. Three different prizes are awarded, including the grand prize (trip to Serbia), and no person can get more than one prize. a) How many ways are there to award prizes? b) In how many ways can you do this if person holding the ticket 23 must get a prize? c) In how many ways can you do this if the person holding ticket 8 and the person holding ticket 11 must win prizes? d) In how many ways can you do this if the grand prize winner is a person holding ticket 8,11 or 23?
The following parts can be answered by the concept of Combination.
a. The total number of ways to award prizes is 100 x 99 x 98 = 970,200.
b. The total number of ways to award prizes in this scenario is 99 x 98 x 97 = 941,094.
c. The total number of ways to award prizes in this scenario is 98 x 97 x 96 = 912,192.
d. The grand prize winner is a person holding ticket 8,11 or 23 is 3 x 99 x 98 = 29,178.
a) There are a total of 100 choices for the first prize, 99 choices for the second prize (since one person already won a prize), and 98 choices for the third prize (since two people already won prizes). So, the total number of ways to award prizes is 100 x 99 x 98 = 970,200.
b) If person holding the ticket 23 must get a prize, then there are only 99 choices for the first prize (since ticket 23 is already taken), 98 choices for the second prize, and 97 choices for the third prize. So, the total number of ways to award prizes in this scenario is 99 x 98 x 97 = 941,094.
c) If the person holding ticket 8 and the person holding ticket 11 must win prizes, then there are only 98 choices for the first prize (since tickets 8 and 11 are already taken), 97 choices for the second prize, and 96 choices for the third prize. So, the total number of ways to award prizes in this scenario is 98 x 97 x 96 = 912,192.
d) If the grand prize winner is a person holding ticket 8,11 or 23, then there are only 3 choices for the first prize (since only these three tickets are eligible for the grand prize), 99 choices for the second prize (since one person already won a prize and the grand prize winner is not eligible for the second prize), and 98 choices for the third prize (since two people already won prizes). So, the total number of ways to award prizes in this scenario is 3 x 99 x 98 = 29,178.
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Let A be a set of n ≥ 2 distinct numbers and let a1a2 · · · an be a permutation of A. For i = 2, 3, . . . , n we say that position i in the permutation is a step if ai−1 < ai . We also go ahead and just consider position 1 a step. What is the expected number of steps in a random permutation of A?
This summation is known as the harmonic number H(n) - 1. The approximate value of H(n) is given by the natural logarithm: H(n) ≈ ln(n) + γ, where γ is the Euler-Mascheroni constant (≈ 0.577). The expected number of steps in a random permutation of A is approximately: E(steps) ≈ ln(n) + γ - 1.
In a random permutation of a set A with n distinct numbers (n ≥ 2), the expected number of steps can be found using the concept of linearity of expectation.
Consider the positions i = 1, 2, ..., n. Since position 1 is always considered a step, the probability of position 1 being a step is 1. For the other positions i (i = 2, 3, ..., n), the probability of position i being a step is the probability that ai-1 < ai. Since the numbers are distinct, there are (i - 1) smaller numbers than ai, so the probability of ai-1 < ai is (i - 1) / i.
Now, using the linearity of expectation, the expected number of steps E(steps) can be found by summing the probabilities of each position being a step:
E(steps) = 1 (for position 1) + (1/2) + (2/3) + ... + ((n - 1) / n).
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A bird flies against a wind that is going 4 miles per hour and takes 2 hours to travel a certain distance. When flying with the current, the bird only takes 0.5 hours to travel the same distance. Approximately how fast would the bird fly, in miles per hour, without wind current, assuming it flies at a constant rate?
Answer:
Let's call the speed of the bird without any wind current "x".
When flying against the wind, the effective speed of the bird is its speed (x) minus the speed of the wind (4 mph). So, the distance traveled can be expressed as:
distance = speed * time
distance = (x - 4) * 2
When flying with the wind, the effective speed of the bird is its speed (x) plus the speed of the wind (4 mph). So, the distance traveled can be expressed as:
distance = speed * time
distance = (x + 4) * 0.5
We know that these two distances are the same, since the bird is traveling the same distance in both cases. So:
(x - 4) * 2 = (x + 4) * 0.5
Simplifying this equation, we get:
2x - 8 = 0.5x + 2
1.5x = 10
x = 6.67
Therefore, the bird would fly at a constant speed of approximately 6.67 mph without any wind current.
if you want to be 99% confident of estimating the population mean to within a sampling error of ± 6 and the standard deviation is assumed to be , what sample size is required
Sample size of at least 23 is required to be 99% confident that our estimate of the population mean is within ±6.
How to calculate the sample size?To calculate the required sample size, we can use the formula:
n = (Zα/2 * σ / E)²
Where:
n = sample size
Zα/2 = the Z-score for the desired confidence level, which is 2.58 for 99%
σ = the population standard deviation (assumed to be given)
E = the desired margin of error, which is 6 in this case.
Substituting these values, we get:
n = (2.58 * σ / 6)²
Since the population standard deviation is not given, we cannot find the exact sample size. However, we can use an estimated value of σ based on prior knowledge or a pilot study.
For example, if we assume σ = 10, then the sample size required would be:
n = (2.58 * 10 / 6)² = 22.25 ≈ 23
Therefore, we would need a sample size of at least 23 to be 99% confident that our estimate of the population mean is within ±6.
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Assume that A is row equivalent to B. Find bases for Nul A and Col A. 106 4 A2-63 2B0 2 5 2 -24 2 11-6 -3 8 A basis for Col A is ! (Use a comma to separate vectors as needed.) A basis for Nul Ais (Use a comma to separate vectors as needed.)
the null space of A is the span of the vector:
(-2, 3, 1)
A basis for Nul A is:
{(-2, 3, 1)}
To find bases for Nul A and Col A, we can use the fact that A is row equivalent to B. This means that we can perform a sequence of elementary row operations on A to obtain B. Since elementary row operations do not change the null space or column space of a matrix, the null space and column space of A will be the same as the null space and column space of B.
To find a basis for Col A, we can find the pivot columns of A (or B, since they have the same column space). The pivot columns are the columns of A that contain a leading non-zero entry in the row reduced form of A. In this case, the row reduced form of A is:
1 0 0 -1
0 1 0 2
0 0 1 3
The pivot columns are columns 1, 2, and 3. Therefore, a basis for Col A is the set of corresponding columns from A:
{(1, 0, 2), (4, 2, 5), (2, -6, -3)}
To find a basis for Nul A, we can solve the homogeneous system Ax = 0. Since A is row equivalent to B, we can use the row reduced form of B to solve for x. The row reduced form of B is:
1 0 -2/53 0
0 1 3/53 0
0 0 0 1
The solution to the system Ax = 0 can be written in parametric form as:
x1 = 2/53 s
x2 = -3/53 s
x3 = s
where s is a scalar. Therefore, the null space of A is the span of the vector:
(-2, 3, 1)
A basis for Nul A is:
{(-2, 3, 1)}
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This question has several parts that must be completed sequentially. If you skip able to come back to the skipped part. Tutorial Exercise Find the dimensions of a rectangle with perimeter 120 m whose area is as large as possible. Step 1 If a rectangle has dimensions x and y, then we must maximize the area A= xy. Since the perimeter is 2x +2y = 120, then y= __ - x. Step 2 We must maximize the area A= xy x=(60-x)=60x- x^2,where 0
The dimensions of the rectangle with the largest possible area and a perimeter of 120 meters are 30 meters by 30 meters.
Explanation: -
To find the dimensions of a rectangle with a perimeter of 120 meters and the largest possible area, we need to follow these steps:
Step 1: Given the dimensions x and y, we have the area A = xy. then the perimeter of the rectangle is 2x + 2y = 120. Solving for y, we get y = 60 - x.
Step 2: To maximize the area A = xy, we substitute y with the expression from step 1: A(x) = x(60 - x) = 60x - x^2, where 0 < x < 60.
To find the maximum area, we can use calculus to find the critical points.
Step 3: Find the derivative of the area function, use the formula
d/dx(x^n) =nx^n-1
so that derivative is A'(x) = 60 - 2x.
Step 4: Set A'(x) = 0 and solve for x. In this case, 60 - 2x = 0, so x = 30.
Step 5: Plug x = 30 back into the expression for y: y = 60 - x = 60 - 30 = 30.
The dimensions of the rectangle with the largest possible area and a perimeter of 120 meters are 30 meters by 30 meters.
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QUADRATIC FUNCTIONS: The profit (in hundreds of dollars) that a corporation receives depends on the amount (in hundreds of dollars) the company spends on marketing according to the model 130+10X−0.5x2130+10X−0.5x2. What expenditure for advertising yields a maximum profit? What is the mathematical name of this point?
PROBLEM 4: POLYNOMIAL FUNCTIONS: Let f(x)=4x5−8x4−5x3+10x2+x−1f(x)=4x5−8x4−5x3+10x2+x−1. The graph is presented below:
Describe f (x) in terms of
Degree of polynomial
Main coefficient
Final behavior
Maximum number of zeros
Maximum number of exchange points (relative maximums and minimums)
Step-by-step explanation:
The profit (in hundreds of dollars) that a corporation receives is given by the quadratic function:
P(x) = 130 + 10x - 0.5x^2
where x is the amount spent on marketing (in hundreds of dollars).
To find the expenditure for advertising that yields a maximum profit, we need to find the vertex of the parabola. The vertex occurs at:
x = -b/(2a) = -10/(2*(-0.5)) = 10
Substituting x = 10 back into the equation for P(x), we get:
P(10) = 130 + 10(10) - 0.5(10)^2 = 180
Therefore, an expenditure of $1000 for advertising yields a maximum profit of $18000.
The mathematical name of the point is the vertex of the parabola.
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For the polynomial function:
f(x) = 4x^5 - 8x^4 - 5x^3 + 10x^2 + x - 1
Degree of polynomial: 5
Main coefficient: 4 (the leading coefficient)
Final behavior: As x approaches positive or negative infinity, f(x) also approaches positive infinity (since the leading term has a positive coefficient and has the highest degree).
Maximum number of zeros: 5 (since it is a fifth-degree polynomial)
Maximum number of exchange points: 4 (since there are 4 relative extrema, either maximum or minimum points)