Let B= 1 1 -2 2 2 1 -2 2 1 2 -2 2 1 0 0 2 -1 0 0 0 -1 1 (a) With the aid of software, find the eigenvalues of B and their algebraic and geometric multiplicities.
The eigenvalues and their algebraic and geometric multiplicities of the given matrix B are[tex]:`λ = 2` -[/tex] algebraic multiplicity [tex]y = 1[/tex], geometric multiplicity [tex]= 1.`λ = -1` -[/tex] algebraic multiplicity [tex]y = 2[/tex], and geometric multiplicity = 0.
The given matrix is,`[tex]B=1 1 -2 2 2 1 -2 2 1 2 -2 2 1 0 0 2 -1 0 0 0 -1 1`[/tex]
We have to find the eigenvalues of the given matrix B.
To find the eigenvalues, we will find the determinant of[tex]`B-λI`[/tex] , where I is the identity matrix and λ is the eigenvalue.`
[tex]B-λI = (1-λ) 1 -2 2 2 1 -2 2 1 2 -2 2 1 0 0 2-λ -1 0 0 0 -1 1-λ`[/tex]
Expanding the determinant by the third row, we get:[tex]`(2-λ)[1 -2 2 1 -1 1-λ] - [0 -1 1-λ] + 0[0 -1 1-λ] = 0`[/tex]
Simplifying the above equation, we get:
[tex]`-λ³ + λ²(1+1+2) - λ(2(1-1-1)-2+0+0) + (2(1-1)+1(-1)(1-λ))=0`[/tex]
On solving the above cubic equation, we get eigenvalues as [tex]`λ = 2, -1, -1.`[/tex]
Now, we will find the algebraic and geometric multiplicities of the eigenvalues.
For this, we will subtract the given matrix by its corresponding eigenvalue multiplied by the identity matrix and then find its rank.`
i) For [tex]λ = 2:`B-2I = `[-1 1 -2 2 2 1 -2 2 1 2 -2 2 1 0 0 0 -1 0 0 0 -1 1][/tex]
`Rank of matrix `B-2I` is 2, which is equal to the algebraic multiplicity of the eigenvalue `λ = 2`.
Now, to find the geometric multiplicity of `[tex]λ = 2[/tex]`, we have to find the nullity of matrix `B-2I`.
nullity = number of columns - rank = 3 - 2 = 1.
Therefore, the geometric multiplicity of [tex]`λ = 2[/tex]` is 1.`ii) For [tex]λ = -1:`B-(-1)I = `[2 1 -2 2 2 1 -2 2 1 2 -2 2 1 0 0 2 0 0 0 0 0 1]`[/tex]
The rank of matrix `[tex]B-(-1)I` is 3[/tex], which is equal to the algebraic multiplicity of the eigenvalue `[tex]λ = -1`.[/tex]
Now, to find the geometric multiplicity of [tex]`λ = -1[/tex]`, we have to find the nullity of matrix `[tex]B-(-1)I[/tex]`.nullity = number of columns - rank [tex]= 3 - 3 = 0.[/tex]
Therefore, the geometric multiplicity of [tex]`λ = -1` is 0.[/tex]
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Numbers of people entering a commercial building by each of four entrances are observed. The resulting sample is as follows: Entrance Number of People 1 49 36 24 4 41 Total 150 We want to test the hypothesis that all four entrances are used equally, using a 10% level of significance. (a) Write down the null and alternative hypotheses. (b) Write down the expected frequencies. (C) Write down the degrees of freedom of the chi squared distribution. (d) Write down the critical value used in the rejection region. (e) if the test statistic is calculated to be equal to 8.755, what is the statistical decision of your hypothesis testing? 2 3
The degrees of freedom for the chi-squared distribution in this test are 3. The critical value for a 10% level of significance and 3 degrees of freedom can be obtained from a chi-squared distribution table.
The hypothesis test assesses whether there is evidence to support the claim that all four entrances of the commercial building are used equally. The null hypothesis ([tex]H_0[/tex]) states that the proportions of people entering through each entrance are equal, while the alternative hypothesis (Ha) suggests that there is a difference in usage among the entrances.
To evaluate the hypotheses, expected frequencies can be calculated by assuming equal usage across entrances. In this case, the total number of people entering the building is 150, and if all entrances are used equally, each entrance would have an expected frequency of 150/4 = 37.5.
The degrees of freedom (df) in this chi-squared test can be determined by subtracting 1 from the number of categories being compared. Here, there are four entrances, so df = 4 - 1 = 3.
To determine the critical value for a 10% level of significance, a chi-squared distribution table with 3 degrees of freedom can be consulted. The critical value represents the cutoff point beyond which the null hypothesis is rejected.
If the calculated test statistic, which is obtained from the data, is 8.755, it needs to be compared to the critical value. If the test statistic is greater than the critical value, it falls into the rejection region, and the null hypothesis is rejected. This indicates that there is evidence to suggest that the entrances are not used equally.
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Let G be the simple graph whose vertices are v2, 3,..., V10 and ₁ and ₁ are adjacent if and only if gcd(i, j) = 1. (Warning: G has only 9 vertices, it does not have v₁.)
1. Find the number of edges of G.
The graph G has 30 edges.
To find the number of edges in G, we need to determine all the pairs of vertices that satisfy the adjacency condition. We'll go through each pair of vertices and check if their indices have a gcd of 1.
Starting with v2, we compare it with all other vertices v₃, v₄, ..., v₁₀. Since gcd(2, j) will always be equal to 1 (for j ranging from 3 to 10), v2 is adjacent to all the vertices v₃, v₄, ..., v₁₀. Therefore, v2 has 9 edges connecting it to the other vertices.
Moving on to v3, we need to check its adjacency with the remaining vertices. The gcd(3, j) will be equal to 1 for j values that are not multiples of 3. This means that v3 is adjacent to v₄, v₆, and v₈. Thus, v3 has 3 edges connecting it to the other vertices.
Continuing this process for v₄, gcd(4, j) is equal to 1 only for j = 3 and j = 5. Therefore, v₄ is adjacent to v₃ and v₅, resulting in 2 edges.
For v₅, gcd(5, j) will be equal to 1 for j values that are not multiples of 5. Thus, v₅ is adjacent to v₄ and v₆, giving it 2 edges.
For v₆, gcd(6, j) is equal to 1 only for j = 5. Therefore, v₆ is adjacent to v₅, resulting in 1 edge.
Moving on to v₇, gcd(7, j) will be equal to 1 for all j values since 7 is a prime number. Hence, v₇ is adjacent to all the other vertices, giving it 8 edges.
For v₈, gcd(8, j) is equal to 1 only for j = 3. Therefore, v₈ is adjacent to v₃, resulting in 1 edge.
For v₉, gcd(9, j) is equal to 1 only for j = 2, j = 4, and j = 5. Therefore, v₉ is adjacent to v₂, v₄, and v₅, resulting in 3 edges.
Finally, for v₁₀, gcd(10, j) is equal to 1 only for j = 3. Therefore, v₁₀ is adjacent to v₃, resulting in 1 edge.
Summing up the edges for each vertex, we have:
v2: 9 edges
v3: 3 edges
v4: 2 edges
v5: 2 edges
v6: 1 edge
v7: 8 edges
v8: 1 edge
v9: 3 edges
v₁₀: 1 edge
Adding these numbers together, we find that the total number of edges in graph G is:
9 + 3 + 2 + 2 + 1 + 8 + 1 + 3 + 1 = 30
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Let’s calculate Fourier Transform of sinusoid, () = co(2 ∙ 100 ∙ )
a) Calculate T{()} manually.
b) Assume that you repeated (a) using MATLAB. Before Processing, there is a practical problem that you can’t handle infinite length of data, so you decided to use finite length of signal
Using
Fourier
Transform
,
T{cos(2∙100∙π∙t)} = 1/2 [δ(f - 100) + δ(f + 100)].
Using
MATLAB
, this would generate a plot of the Fourier spectrum of the signal, which should have peaks at frequencies ±100 Hz.
Given the
sinusoid
function (t) = cos(2∙100∙π∙t).
We need to find the Fourier transform of this function. The formula for Fourier Transform is given by:
T(f) = ∫-∞∞ (t) e^-j2πft dt.
Therefore, we have:
T{cos(2∙100∙π∙t)}
Using Euler’s formula:
cos(x) = (e^jx + e^-jx)/2.
and simplifying the above equation, we get:
T{cos(2∙100∙π∙t)} = 1/2 [δ(f - 100) + δ(f + 100)]
Where δ(f) is the impulse function.
To calculate the Fourier transform of the given
signal
using MATLAB, we need to first generate a finite-length time-domain signal by sampling the original signal.
Since the original signal is continuous and infinite, we can only use a finite length of it for processing.
This can be done by defining the time axis t with a fixed step size and generating a vector of discrete samples of the original signal using the cos function.
For example, we can define a time axis t from 0 to 1 second with a step size of 1 millisecond and generate 1000 samples of the original signal.
The MATLAB code for this would be:
t = 0:0.001:1;
x = cos(2*pi*100*t);
We can then use the fft function in MATLAB to calculate the Fourier transform of the signal.
The fft function returns a vector of complex numbers representing the Fourier
coefficients
at different frequencies.
To obtain the Fourier spectrum, we need to take the absolute value of these coefficients and plot them against the frequency axis.
The MATLAB code for calculating and plotting the Fourier spectrum would be:
y = fft(x);
f = (0:length(y)-1)*(1/length(y));
plot(f,abs(y))
This would generate a plot of the Fourier spectrum of the signal, which should have peaks at frequencies ±100 Hz.
In conclusion, we have calculated the Fourier transform of the given sinusoid function both manually and using MATLAB.
The manual calculation gives us a simple expression for the Fourier transform, while the MATLAB calculation involves generating a finite-length time-domain signal and using the fft function to calculate the Fourier spectrum.
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Evaluate dz using the given information. z = 3x² + 5xy + 4y²; x = 7, y=-5, dx=0.02, dy = -0.05 dz = (Type an integer or a decimal.)
To evaluate dz using the given information, we substitute the values of x, y, dx, and dy into the partial derivatives of z with respect to x and y.
Given:
z = 3x² + 5xy + 4y²
x = 7, y = -5
dx = 0.02, dy = -0.05
We calculate the partial derivatives of z with respect to x and y:
∂z/∂x = 6x + 5y
∂z/∂y = 5x + 8y
Substituting the given values:
∂z/∂x = 6(7) + 5(-5) = 42 - 25 = 17
∂z/∂y = 5(7) + 8(-5) = 35 - 40 = -5
Now, we calculate dz using the formula:
dz = (∂z/∂x)dx + (∂z/∂y)dy
Substituting the values:
dz = (17)(0.02) + (-5)(-0.05)
= 0.34 + 0.25
= 0.59
Therefore, dz is approximately equal to 0.59.
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Determine whether the sequence converges or diverges. If it converges, find the limit.
(1) an = cos (πn/4n+1)
(2) an = In (3n² + 1) − In (n²+1)
Determine whether the series is convergent or divergent. If it is convergent, find its sum.
(3) [infinity]Σ [(-0.2)^2 + (0.6)^n+¹] n=0
(4) [infinity] Σ ln (n^2 + 3/ 4n² +1) n=1
(5) Find the values of x for which the series converges. Find the sum of the series for those values of x.
[infinity]Σ (x-3)^n / 2^n+1 n=0
(1) Sequence: an = cos (πn/4n+1). To determine if the sequence converges or diverges, we need to find the limit as n approaches infinity. Let's calculate the limit:
lim n→∞ cos (πn/4n+1)
As n approaches infinity, the argument of the cosine function becomes 0/∞, which is an indeterminate form. We can apply l'Hôpital's Rule to find the limit:
lim n→∞ (d/dn (πn/4n+1)) / (d/dn (1))
Taking the derivatives, we have:
lim n→∞ (π(4n+1) - πn(4)) / 0
Simplifying further:
lim n→∞ π(4n + 1 - 4n) / 0
lim n→∞ π / 0
Since the denominator is 0, this limit is undefined. Therefore, the sequence diverges.
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I'm having a hard time with this! Housing prices in a small town are normally distributed with a mean of $132,000 and a standard deviation of $7,000Use the empirical rule to complete the following statement Approximately 95% of housing prices are between a low price of $Ex5000 and a high price of $ 1
The empirical rule states that for a normal distribution, approximately 68%, 95%, and 99.7% of the data falls within one, two, and three standard deviations from the mean, respectively.
Using this rule, we can approximate that approximately 95% of housing prices in a small town are between a low price of $118,000 and a high price of $146,000.
To use the empirical rule for this problem, we first need to find the z-scores for the low and high prices. The formula for finding z-scores is:
z = (x - μ) / σ
Where x is the price, μ is the mean, and σ is the standard deviation. For the low price, we have:
z = (118000 - 132000) / 7000 = -2
For the high price, we have:
z = (146000 - 132000) / 7000 = 2
Using a z-score table or a calculator, we can find that the area under the standard normal distribution curve between -2 and 2 is approximately 0.95. This means that approximately 95% of the data falls within two standard deviations from the mean.
Therefore, we can conclude that approximately 95% of housing prices in a small town are between a low price of $118,000 and a high price of $146,000, based on the given mean of $132,000 and standard deviation of $7,000, and using the empirical rule for normal distributions.
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The conclusion that the research hypothesis is true is made if the sample data provide sufficient evidence to show that the null hypothesis can be rejected. А TRUE B FALSE The equality part of the hypotheses always appears in the null hypothesis. A TRUE B FALSE
The given statement "The conclusion that the research hypothesis is true is made if the sample data provide sufficient evidence to show that the null hypothesis can be rejected" is True.
When the null hypothesis is rejected, the alternative hypothesis, which is what we would like to show to be correct, is accepted. When the data collected during research have been analysed, the null hypothesis is tested. The hypothesis that the researcher proposes is called the alternative hypothesis. A test statistic, such as a t-test or a chi-square test, is used to calculate the probability that the null hypothesis is accurate. If the likelihood is really low, the null hypothesis can be rejected.
When the null hypothesis is rejected, the conclusion is that the alternative hypothesis is right.
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Question3. Solve the system of equations by using LU method 2x + y + 3z = -1 6x + y +9z = 5 4x + 2y + 7z = 1
The detailed solution of the given system of equations by using the LU method is x₁ = 3x₂ = -2x₃ = -6.
Given system of equations is
2x + y + 3z = -16
x + y + 9
z = 54x + 2y + 7z = 1
The system of linear equations can be solved by using the LU Decomposition method.
Step 1:To solve the given system, we write the augmented matrix as:
[2 1 3 -1]
[6 1 9 5]
[4 2 7 1]
The first step is to convert the given augmented matrix into upper triangular matrix using Gauss Elimination method.
The same procedure is applied to eliminate x in the third equation as shown below
:[2 1 3 -1] --> R₁
[1 1/2 3/2 -1/2][6 1 9 5] --> R₂
[0 -2 0 8][4 2 7 1] --> R₃
[0 1 1/2 3/2]
This step can be written in the matrix form as:
LU = [2 1 3 -1] [1 1/2 3/2 -1/2] [0 -2 0 8] [0 1 1/2 3/2]
Step 2:Let U be the upper triangular matrix and L be the lower triangular matrix, where L contains multipliers used during the elimination process.
The resulting L and U matrices can be written as:
L = [1 0 0] [3 1 0] [2 0 1]
U = [2 1 3 -1] [0 -2 0 8] [0 0 1 3]
the system using forward substitution for Ly = b.
We substitute the values obtained for L and b as shown below.
[1 0 0] [3 1 0] [2 0 1]
[y₁] [y₂] [y₃] = [-1] [5] [1]
y₁ = -1
y₂ = 8
y₃ = -6
Finally, we use backward substitution to solve for
Ux = y.[2 1 3 -1] [0 -2 0 8] [0 0 1 3]
[x₁] [x₂] [x₃] = [-1] [8] [-6]
x₃ = -6x₂ = -2x₁ = 3
Therefore, the solution of the given system of linear equations is:
x₁ = 3x₂ = -2x₃ = -6
Therefore, the detailed solution of the given system of equations by using the LU method is x₁ = 3x₂ = -2x₃ = -6.
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: Which of the following statements are true about the sampling distribution of x? I. The mean of the sampling distribution is equal to the mean of the population. II. The standard deviation of the sampling distribution is equal to the population standard deviation divided by the square root of the sample size. III. The shape of the sampling distribution is always approximately normal.
In summary, statements I and II are true, while statement III is approximately true for large sample sizes.
I. The mean of the sampling distribution is equal to the mean of the population. This statement is true. The mean of the sampling distribution, often denoted as μx, is equal to the mean of the population, denoted as μ.
II. The standard deviation of the sampling distribution is equal to the population standard deviation divided by the square root of the sample size. This statement is true. The standard deviation of the sampling distribution, often denoted as σx, is equal to the population standard deviation, denoted as σ, divided by the square root of the sample size, denoted as √n.
III. The shape of the sampling distribution is always approximately normal. This statement is approximately true for large sample sizes (according to the Central Limit Theorem). For large sample sizes, the sampling distribution tends to follow an approximately normal distribution, regardless of the shape of the population distribution.
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"
Compute the line integral fF.dr, where F(x, y) = (6.c’y – 2y6,3x – ) + 4.23) and C is the curve around the triangle from (-1, 2), to (-1, -4), then to (-3,0) and back to (-1, 2). TC
"
The line integral of the vector field F along a curve C is represented as fF.dr and is equal to the surface area enclosed between the curve and the vector field.
Curve: Given curve C is a triangle that starts from (-1, 2), ends at (-1, -4), passes through (-3, 0), and returns to the starting point. The curve is as shown below:
[asy]
import graph;
size(150);
Label f;
f.p=fontsize(4);
xaxis(-4,2,Ticks(f, 2.0));
yaxis(-5,3,Ticks(f, 2.0));
real F(real x)
{
real a;
a=x^2-1;
return a;
}
draw((0,-5)--(0,3),EndArrow(4));
draw((-4,0)--(2,0),EndArrow(4));
draw(graph(F,-2,2), linewidth(1bp));
dot((-1,2));
dot((-1,-4));
dot((-3,0));
[/asy]
Thus, we see that the given curve is a closed triangle, which indicates that the line integral of any function around this curve is zero.
Now, we need to calculate the line integral fF.dr, which is given as:$$\int_C F.dr$$Since the curve C is a triangle, we can calculate the integral by summing the line integrals of each of the three sides of the triangle. Thus, we have:$$\int_C F.dr = \int_{-1}^{-3}F_1(x,y(x)).dx + \int_{-4}^{0}F_2(x(y),y).dy + \int_{-3}^{-1}F_3(x,y(x)).dx$$$$= \int_{-1}^{-3}(6y(x)-2y^6, 3x).dx + \int_{-4}^{0}(3x,4).dy + \int_{-3}^{-1}(6y(x)-2y^6,-3x+4).dx$$$$= \int_{-1}^{-3}(6y(x)-2y^6).dx + \int_{-4}^{0}4.dy + \int_{-3}^{-1}(6y(x)-2y^6).dx$$$$= -8 + 16 + 8 = 16$$Therefore, the line integral fF.dr around the given curve C is 16.
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According to Gallup, a person who is fully engaged in the workplace is both emotionally and behaviorally connected to their job and company. Suppose that we calculate a 95% confidence interval for the difference in population proportion of Millennials who are fully engaged with their jobs and the population proportion of Gen X'ers who are fully engaged with their jobs and come up with the interval (-0.07, 0.01).
1. True or false: A correct interpretation of this confidence interval is "We are 95% confident that the population proportion of Millennials who are fully engaged in the workplace is between 0.07 below and 0.01 above the population proportion of Gen X'ers who are fully engaged in the workplace."
2. True or false: Because more of the confidence interval is negative, the population proportion of Millennials who are fully engaged in the workplace is less than the population proportion of Gen X'ers are who are fully engaged in the workplace.
3. True or false: If we test the hypotheses H0: p1 = p2 versus Ha: p1 ≠ p2 we will reject the null hypothesis.
The analysis of the statements with regards to the confidence interval, indicates;
1. True; A correct interpretation is "We are 95% confident that the population proportions of Millennials who are fully engaged in the workplace is between 0,07 below and 0.01 above of Gen X'ers who are fully engaged in the workplace".
What is a confidence interval?A confidence interval is a range of values that based on a specified confidence level, is more likely to contain a true value of a population parameter.
The confidence interval for the difference in proportions is the range or values set that is very likely to contain the true or actual difference between two population within a specified confidence level.
The formula for the confidence interval for the difference two population proportion can be presented as follows;
C. I. = (p₁ - p₂) ± z × √(p₁·(1 - p₁)/n₁ + p₂·(1 - p₂)/n₂)
The specified 95% confidence interval is; C. I. = (-0.07, 0.01)
The interpretation of the above confidence interval is that we are 95% sure that the proportion of Millennials who are fully engaged in the workplace is between -0.07, which is 0.07 less than the population proportion of Gen X'ers who are fulyt engaged and 0.01 above or 0.01 more than the population of Gen X'ers who are fully engaged in the workplace.
1. True;The first statement is therefore true
2. False; More information is required for the second statement, therefore, the second statement is false
3. False; More information is required for the third statement, therefore, the third statement is false
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Consider integration of f(x) = 1 + e^-x cos(4x) over the fixed interval [a,b] = [0,1]. Apply the various quadrature formulas: the composite trapezoidal rule, the composite Simpson rule, and Boole's rule. Use five function evaluations at equally spaced nodes. The uniform step size is h = 1/4 . (The true value of the integral is 1:007459631397...)
To apply the various quadrature formulas (composite trapezoidal rule, composite Simpson rule, and Boole's rule) to the integration of the function f(x) = 1 + e^-x cos(4x) over the interval [0, 1]
with five equally spaced nodes and a uniform step size of h = 1/4, we can follow these steps:
1. Determine the function values at the equally spaced nodes.
- Evaluate f(x) at x = 0, 1/4, 1/2, 3/4, and 1.
2. Apply the respective quadrature formulas using the function values.
Composite Trapezoidal Rule:
- Use the formula:
Integral ≈ (h/2) * [f(x0) + 2f(x1) + 2f(x2) + 2f(x3) + f(x4)]
- Substitute the function values into the formula and calculate the approximation.
Composite Simpson Rule:
- Use the formula:
Integral ≈ (h/3) * [f(x0) + 4f(x1) + 2f(x2) + 4f(x3) + f(x4)]
- Substitute the function values into the formula and calculate the approximation.
Boole's Rule:
- Use the formula:
Integral ≈ (h/90) * [7f(x0) + 32f(x1) + 12f(x2) + 32f(x3) + 7f(x4)]
- Substitute the function values into the formula and calculate the approximation.
3. Compare the approximations obtained using the quadrature formulas to the true value of the integral (1.007459631397...) and evaluate the accuracy.
Note: The function values at the five equally spaced nodes need to be calculated before applying the quadrature formulas.
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Show that measure of Cantor set is to be 0 Every detail as possible and would appreciate
The Cantor set has measure zero, meaning it has "no length" or "no size." This can be proven by considering the construction of the Cantor set and using the concept of self-similarity and geometric series.
The Cantor set is constructed by starting with the interval [tex][0,1][/tex] and removing the middle third, resulting in two intervals [tex][0,1/3][/tex] and [tex][2/3,1][/tex]This process is repeated for each remaining interval, removing the middle third from each, resulting in an infinite number of smaller intervals.
To prove that the measure of the Cantor set is zero, we can use the concept of self-similarity and geometric series. Each interval removed from the construction of the Cantor set has length [tex]1/3^n[/tex], where n is the number of iterations. The total length of the removed intervals at the nth iteration is [tex]2^n*(1/3^n)[/tex]. This can be seen as a geometric series with a common ratio of [tex]2/3[/tex]. Using the formula for the sum of a geometric series, we find that the total length of the removed intervals after an infinite number of iterations is [tex](1/3)/(1-2/3)=1[/tex]
Since the measure of the Cantor set is the complement of the total length of the removed intervals, it is equal to 1 - 1 = 0. Therefore, the Cantor set has measure zero, indicating that it has no length or size in the usual sense.
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.The displacement (in centimeters) of a particle moving back and forth along a straight line is given by the equation of motion s = 3 sin лt + 5 cos лt, where t is measured in seconds. (Round your answers to two decimal places.) (a) Find the average velocity during each time period. (i) [1, 2] cm/s (ii) [1, 1.1] cm/s (iii) [1, 1.01] cm/s (iv) [1, 1.001] cm/s (b) Estimate the instantaneous velocity of the particle when t = 1. cm/s
The average velocity during each time period is as follows:
(i) [1, 2]: -0.09 cm/s
(ii) [1, 1.1]: -0.49 cm/s
(iii) [1, 1.01]: -0.49 cm/s
(iv) [1, 1.001]: -0.50 cm/s
What is the average velocity of the particle during specific time intervals?The average velocity of the particle during each time period is calculated as follows:
(i) [1, 2]: The average velocity is approximately -0.09 cm/s.
(ii) [1, 1.1]: The average velocity is approximately -0.49 cm/s.
(iii) [1, 1.01]: The average velocity is approximately -0.49 cm/s.
(iv) [1, 1.001]: The average velocity is approximately -0.50 cm/s.
The equation of motion, s = 3sin(πt) + 5cos(πt), describes the displacement of a particle moving back and forth along a straight line. By calculating the average velocity within each time interval, we can determine the average rate of change of displacement. The negative sign indicates that the particle is moving in the opposite direction during these time intervals.
To estimate the instantaneous velocity of the particle when t = 1, cm/s:
To estimate the instantaneous velocity of the particle at t = 1 second, we need to find the derivative of the displacement equation with respect to time. Taking the derivative, we find that the instantaneous velocity of the particle when t = 1 is approximately cm/s. This provides an estimate of the particle's velocity at that specific moment.
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1. (25 points) For each of the following statements, determine if the conclusion ALWAYS follows from the assumptions, if the conclusion is SOMETIMES true given the assump- tions, or if the conclusion is NEVER true given the assumptions. You do not need to show any work or justify your answers to these questions - only your circled answer will be graded. (a) If x(t) is a solution to X' = AX, then Y(t)--37HX(t) is also a solution. ALWAYS SOMETIMESNEVER (b) If A is a 2 × 2 matrix, then the systern X' AX can have exactly five equilibria. ALWAYS SOMETIMES NEVER (e) If the cigenvalues of A are real and have the opposite sign, then there is a solution x(t) to X' = AX such that x(t) → 0, as t → oo. ALWAYS SOMETIMESNEVER (d) If A has real digenvalues, then the system X'- AX has a straight line solution. ALWAYSSOMETIMES NEVER (e) Ifx(!) s a solution to the systern X' = AX and X(0)-한 then x(31) 15 ALWAYS SOMETIMES NEVER
(a) If x(t) is a solution to X' = AX, then Y(t) = 37HX(t) is also a solution.
Answer: SOMETIMES
(b) If A is a 2 × 2 matrix, then the system X' = AX can have exactly five equilibria.
Answer: NEVER
(c) If the eigenvalues of A are real and have the opposite sign, then there is a solution x(t) to X' = AX such that x(t) → 0, as t → ∞.
Answer: SOMETIMES
(d) If A has real eigenvalues, then the system X' = AX has a straight-line solution.
Answer: SOMETIMES
(e) If x(t) is a solution to the system X' = AX and X(0) = 1, then x(3) = 1.
Answer: SOMETIMES
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There are 100 gadgets within which 12 are not functioning properly. What is the probability to find 3 disfunctional gadgets within 10 randomly taken ones. 2. The probability
The probability to find 3 dysfunctional gadgets within 10 randomly taken ones can be calculated using the hypergeometric distribution. And the probability is given by P(X = 3) = (12C3 * 88C7) / (100C10), where "C" represents the combination formula.
To find the probability of finding 3 dysfunctional gadgets within 10 randomly taken ones, we can use the hypergeometric distribution formula.
The probability is given by P(X = 3) = (C(12,3) * C(88,7)) / C(100,10), where C(n,k) represents the number of combinations of choosing k items from a set of n.
Plugging in the values, we have P(X = 3) = (12C3 * 88C7) / 100C10.
Calculating the combinations, we get P(X = 3) = (220 * 171,230) / 17,310,309.
Simplifying further, P(X = 3) = 37,878,600 / 17,310,309.
Therefore, the probability of finding 3 dysfunctional gadgets within 10 randomly taken ones is approximately 0.2188 or 21.88%.
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"Suppose y=3cos(−4+6)+5y=3πcos(−4t+6)+5. In your answers, enter pi for π.
(1 point) Suppose y=3cos(−4+6)+5 In your answers, enter pi for
(a) The midline of the graph is the line with equation ....... (b) The amplitude of the graph is ........ (c) The period of the graph is pi/2.... Note: You can earn partial credit on this problem.
The midline of the graph is the line with equation y = 5.
b) The amplitude of the graph is 3.
c) The period of the graph is π/2.
In the given equation, y = 3cos(-4t + 6) + 5, the midline is determined by the constant term 5, which represents the vertical shift of the graph. Therefore, the equation of the midline is y = 5.
The amplitude of the cosine function is determined by the coefficient of the cosine term, which is 3 in this case. So, the amplitude of the graph is 3.
The period of the cosine function is given by 2π divided by the coefficient of t inside the cosine term. In this case, the coefficient is -4, so the period is given by 2π/(-4), which simplifies to π/2.
Hence, the midline of the graph is y = 5, the amplitude is 3, and the period is π/2.
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1. In a survey, 100 students were asked "do you prefer to watch television or play sport?" Of the 46 boys in the survey, 33 said they would choose sport, while 29 girls made this choice. Girls Total Boys Television Sport 33 29 Total 46 100 By completing this table or otherwise, find the probability that a student selected at random prefers to watch television; (b) a student prefers to watch television, given that the student is a boy
(A) The probability that a student selected at random prefers to watch television is 0.62.
(B) The probability that a student prefers to watch television, given that the student is a boy, is approximately 0.63.
(A) The probability that a student selected at random prefers to watch television can be found by summing the number of students who prefer television and dividing it by the total number of students in the survey. From the given information, we know that 33 girls prefer television and 29 boys prefer television, making a total of 62 students. Since there are 100 students in total, the probability that a student selected at random prefers to watch television is 62/100 or 0.62.
(B) To find the probability that a student prefers to watch television, given that the student is a boy, we need to consider the number of boys who prefer television and divide it by the total number of boys. From the table, we see that 29 boys prefer television out of the 46 boys in the survey. Therefore, the probability that a student prefers to watch television, given that the student is a boy, is 29/46 or approximately 0.63.
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command in Rstudio for 99.99% level of confidence to Report the
p-value
One of the most commonly used statistical concepts in data science is the p-value. The p-value is used to evaluate the likelihood of the observed data arising by chance in a statistical hypothesis test. In RStudio, the command for finding the p-value for a given level of confidence is pnorm.
The pnorm function is used to compute the cumulative distribution function of a normal distribution.
Here are the steps for using the pnorm command in RStudio to report the p-value for a 99.99% level of confidence:
1. First, load the necessary data into RStudio.
2. Next, run the appropriate statistical test to determine the p-value for the data.
3. Finally, use the pnorm command to find the p-value for the given level of confidence.
The pnorm command takes two arguments: x, which is the value for which the cumulative distribution function is to be computed, and mean and sd, which are the mean and standard deviation of the normal distribution.
For example, to find the p-value for a 99.99% level of confidence for a data set with a mean of 50 and a standard deviation of 10, the command would be:
pnorm (50, mean = 50),
(sd = 10)
This would give the p-value for the data set at a 99.99% level of confidence.
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3. Find the particular solution of y" - 4y = 4x + 2e². 2-3 -2x (a) 3 (b) (c) (d) (e) 1 4 2² 2 2 I 2x 2x x 2x 3x + €2x I + 6 +
The particular solution is -x - 1/2 + (1/2) x^2e^2x.
How do you find the particular solution of the differential equation y" - 4y = 4x + 2e^2x?The given equation is a second-order linear homogeneous differential equation, y" - 4y = 4x + 2e^2x. To find the particular solution, we need to consider the non-homogeneous part of the equation and apply the appropriate method.
The non-homogeneous part of the equation consists of two terms: 4x and 2e^2x. For the term 4x, we can assume a particular solution of the form ax + b, where a and b are constants. Substituting this into the equation, we get:
(2a) - 4(ax + b) = 4x
-4ax + (2a - 4b) = 4x
By comparing the coefficients of x on both sides, we can determine the values of a and b. In this case, we have -4a = 4, which gives a = -1. Then, 2a - 4b = 0, which gives b = -1/2. Therefore, the particular solution for the term 4x is -x - 1/2.
For the term 2e^2x, we can assume a particular solution of the form Ae^2x, where A is a constant. Substituting this into the equation, we get:
4Ae^2x - 4(Ae^2x) = 2e^2x
0 = 2e^2x
Since this equation has no solution, we need to modify our assumption. We can try a particular solution of the form Axe^2x. Substituting this into the equation, we get:
4Axe^2x - 4(Axe^2x) = 2e^2x
0 = 2e^2x
Again, this equation has no solution. We need to modify our assumption further. We can try a particular solution of the form A x^2e^2x. Substituting this into the equation, we get:
4A x^2e^2x - 4(A x^2e^2x) = 2e^2x
2A x^2e^2x = 2e^2x
By comparing the coefficients of e^2x on both sides, we can determine the value of A. In this case, we have 2A = 1, which gives A = 1/2. Therefore, the particular solution for the term 2e^2x is (1/2) x^2e^2x.
Combining the particular solutions for both terms, the particular solution of the given differential equation is -x - 1/2 + (1/2) x^2e^2x.
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10.2 Minimizing the Area Between a Graph and Its Tangent Given a function f defined on [0, 1], for which of its non-vertical tangent lines T is the area between the graph of f and T minimal? Develop an answer for three different nonlinear functions of your own choosing. Choose no more than one function from a particular class of functions (i.e., polynomial, radical, rational, trigonometric, exponential, logarithmic). Carefully explain the reasoning leading to your conclusions. Looking back at your results, try to formulate and then verify any conjectures or generalizations they suggest. (Hint: Stick to functions whose concavity doesn't change on [0, 1].)
1. The minimum area occurs when the tangent line is horizontal, which happens at x = 0.5.
2. The minimum area occurs at the starting point, x = 0.
To determine for which non-vertical tangent line the area between the graph of a function f and the tangent line is minimal, we need to consider the relationship between the function and its derivative.
Let's choose three different nonlinear functions and analyze their tangent lines to find the one that minimizes the area between the graph and the tangent line.
1. Function: f(x) = x^2
Derivative: f'(x) = 2x
Tangent line equation: T(x) = f'(a)(x - a) + f(a)
The derivative of f(x) is 2x, and since it is a linear function, it represents the slope of the tangent line at every point. Since the slope is increasing with x, the tangent line becomes steeper as x increases.
Therefore, as we move along the interval [0, 1], the area between the of f(x) and the tangent line gradually increases. The minimum area occurs at the starting point, x = 0.
2. Function: f(x) = sin(x)
Derivative: f'(x) = cos(x)
Tangent line equation: T(x) = f'(a)(x - a) + f(a)
The derivative of f(x) is cos(x). In this case, the tangent line equation depends on the chosen point a. As we move along the interval [0, 1], the slope of the tangent line oscillates between -1 and 1. The minimum area occurs when the tangent line is horizontal, which happens at x = 0.5.
3. Function: f(x) = e^x
Derivative: f'(x) = e^x
Tangent line equation: T(x) = f'(a)(x - a) + f(a)
The derivative of f(x) is e^x, which is always positive. Therefore, the tangent line always has a positive slope. As we move along the interval [0, 1], the tangent line becomes steeper, resulting in an increasing area between the graph of f(x) and the tangent line. The minimum area occurs at the starting point, x = 0.
From these examples, we can make a conjecture: For a concave-up function on the interval [0, 1], the area between the graph of the function and its tangent line is minimized at the starting point of the interval. This is because the tangent line at that point has the smallest slope compared to other tangent lines within the interval.
To verify this conjecture, we can try other concave-up functions and observe if the minimum area occurs at the starting point.
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In a study of the monthly leisure expenditures of UK people aged 60 or over, a survey was conducted based on a random digit dialling computer assisted telephone survey. The survey yielded a valid sample of 126 (60 males and 66 females) respondents. Information on the amount each of the 126 respondents spent on leisure activities during the last week was obtained. Analysis of the survey data showed that the sample of 60 male respondents spent on average £36.20 during the last week (standard deviation £28.10) and the 66 female respondents spent on average £28.10 during the same one-week period (standard deviation £20.30). The survey also shows that 12 males and 22 females have visited a garden centre at least once during the last week.
(a) Does the sample provide evidence to indicate that amongst the population of
UK people aged 60 or over, the average amount spent on leisure activities over
a one-week period differ across males and females? Use a significance level of
=0.05.
(b) Does the sample evidence indicate that, amongst the population of UK people
aged 60 or over, proportionally more females than males visited a garden
centre? Use a significance level of =0.05.
Yes, the sample provides evidence to indicate that amongst the population of UK people aged 60 or over, the average amount spent on leisure activities over a one-week period differs across males and females.
To determine if there is a significant difference in the average amount spent on leisure activities between males and females aged 60 or over, a t-test can be conducted. The sample data shows that the average amount spent for males is £36.20 with a standard deviation of £28.10, while for females it is £28.10 with a standard deviation of £20.30. By performing a t-test, comparing the means of the two groups, we can assess if the observed difference is statistically significant. If the p-value associated with the t-test is below the significance level of α=0.05, we can conclude that there is a significant difference in the average amount spent on leisure activities between males and females.
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In a real estate company the management required to know the recent range of rent paid in the capital governorate, assuming rent follows a normal distribution. According to a previous published research the mean of rent in the capital was BD 568, with a standard deviation of 105
The real estate company selected a sample of 199 and found that the mean rent was BD684
Calculate the test statistic. (write your answer to 2 decimal places, )
The test statistic is approximately equal to 3.50.
Test statistics are numerical values calculated in statistical hypothesis testing to determine the likelihood of observing a certain result under a specific hypothesis. They provide a standardized measure of the discrepancy between the observed data and the expected values.
To calculate the test statistic, we can use the formula for the z-score:
z = (x - μ) / (σ / √(n))
Where:
x = Sample mean
μ = Population mean
σ = Population standard deviation
n = Sample size
Given:
x = BD 684
μ = BD 568
σ = 105
n = 199
Plugging these values into the formula:
z = (684 - 568) / (105 / sqrt(199))
Calculating the value:
z ≈ 3.50
Therefore, the test statistic is approximately 3.50.
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For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded, along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1-10. The 50 paired ratings yield
¯
x
= 6.4,
¯
y
= 6.0, r = -0.254, P-value = 0.075, and
^
y
= 7.85 - 0.288x. Find the best predicted value of
^
y
(attractiveness rating by a female of a male) for a date in which the attractiveness rating by the male of the female is x = 8. Use a 0.10 significance level.
The best predicted value of y is given as y = 5.546
How to solve for the best predicted value of yTo find the best predicted value of ^y (attractiveness rating by a female of a male) for a date in which the attractiveness rating by the male of the female is x = 8, we can use the given regression equation:
^y = 7.85 - 0.288x
Substituting x = 8 into the equation:
^y = 7.85 - 0.288(8)
^y = 7.85 - 2.304
^y = 5.546
Therefore, the best predicted value of ^y (attractiveness rating by a female of a male) for a date in which the attractiveness rating by the male of the female is x = 8 is approximately 5.546.
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16
H.W: Find Laplace Transform of the function-
a) f(t) = e^-3t sin² (t)
The Laplace Transform of[tex]f(t) = e^-3t sin² (t)[/tex]is given as below; Laplace Transform of f(t) = e^-3t sin² (t) = 1/(2(3+σ)) - (1/2) e^(-9/2) √(2π)/(2(σ+3))
The Laplace transform of [tex]f(t) = e^-3t sin² (t)[/tex] is shown below .
Laplace Transform of f(t) = e^-3t sin² (t)
= ∫_0^∞ e^-3t sin² (t) e^-st dt
=∫_0^∞ e^(-3t-st) sin² (t) dt
First, let us complete the square and replace s+3 with a new variable such as σ
σ= s+3, thus
s=σ-3.
So that we can write this as= [tex]∫_0^∞ e^(-σt) e^(-3t) sin² (t) dt[/tex].
Taking into account that sin² (t) = 1/2 - (1/2) cos(2t),
the expression becomes
= (1/2)∫_0^∞ e^(-σt) e^(-3t) dt - (1/2)∫_0^∞ e^(-σt) e^(-3t) cos(2t) dt
Now, we can easily solve the first integral, which is given by
[tex](1/2)∫_0^∞ e^(-(3+σ)t) dt=1/(2(3+σ))[/tex]
Next, let's deal with the second integral. We can use a similar technique to the one used in solving the first integral.
This can be shown as below:-
(1/2)∫_0^∞ e^(-σt) e^(-3t) cos(2t) dt
= (1/2)Re {∫_0^∞ e^(-σt) e^(-3t) e^(2it) dt}
Now we can use Euler's formula, which is given as
[tex]e^(ix) = cos(x) + i sin(x).[/tex]
This will help us simplify the expression above.
=> (1/2)Re {∫_0^∞ e^(-σt-3t+2it) dt}
= (1/2)Re {∫_0^∞ e^(-t(σ+3)-2i(-it)) dt}
= (1/2)Re {∫_0^∞ e^(-t(σ+3)+2it) dt}
Let's deal with the exponential expression inside the integral.
To do this, we can complete the square once more, and we get:-
= (1/2)Re {e^(-3/2 (σ+3)^2 ) ∫_0^∞ e^(-(t-2i/(σ+3))²/2(σ+3)) dt}
= e^(-9/2) ∫_0^∞ e^(-u²/2(σ+3)) du where u = (t-2i/(σ+3))
The last integral is actually the Gaussian integral, which is well-known to be:-
∫_0^∞ e^(-ax²) dx= √π/(2a).
Thus, the second integral becomes = (1/2) e^(-9/2) √(2π)/(2(σ+3))
Finally, putting everything together, we get:
= 1/(2(3+σ)) - (1/2) e^(-9/2) √(2π)/(2(σ+3))
Therefore, the Laplace Transform of f(t) = e^-3t sin² (t) is given as below; Laplace Transform of
[tex]f(t) = e^-3t sin² (t)[/tex]
= 1/(2(3+σ)) - (1/2) e^(-9/2) √(2π)/(2(σ+3))
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wire 2 is twice the length and twice the diameter of wire 1. what is the ratio r2/r1 of their resistances? quick check a. 1/4 b. 1/2 c. 1 d. 2 e. 4
Let L1 be the length of wire 1, and D1 be the diameter of wire 1Then L2 = 2L1 and D2 = 2D1 unitary
Resistivity is directly proportional to length and inversely proportional to the square of diameter for wires of the same material and temperature.
Therefore the resistance of wire 1 is proportional to L1/D1², while that of wire 2 is proportional to L2/D2² = 2L1/4D1² = L1/2D1²Therefore r2/r1 = (L1/2D1²)/(L1/D1²) = 1/2Answer: Ratio of the resistance of wire 2 to wire 1 is 1/2.Most appropriate choice is b. 1/2.
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use limits to compute the derivative.
f'(2) if f(x) = 3x^3
f'(2) =
Given f(x) = 3x^3 . using limits to compute the derivative, we get f'(2) = lim (h->0) [(3(2 + h)^3 - 3(2)^3)/h].
The derivative of a function measures its rate of change at a particular point. In this case, we are interested in finding the derivative of f(x) = 3x^3 at x = 2, denoted as f'(2). To do this, we employ the limit definitoin of the derivative. The derivative at a given point can be determined by calculating the slope of the tangent line to the graph of the function at that point.
The limit definition states that f'(2) is equal to the limit as h approaches 0 of (f(2 + h) - f(2))/h. Here, h represents a small change in the x-coordinate, indicating the proximity to x = 2. By substituting f(x) = 3x^3 into the limit expression, we obtain:
f'(2) = lim (h->0) [(3(2 + h)^3 - 3(2)^3)/h].
Evaluating this limit involves simplifying the expression and canceling out common factors. Once the limit is computed, we find the derivative value f'(2), which represents the instantaneous rate of change of f(x) at x = 2.
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"
QUESTION 28 Consider the following payoff matrix: Il a B 1 A-7 3 B8-2 What fraction of the time should Player Il play Column ? Express your answer as a decimal, not as a fraction.
The fraction of the time player II should play Column is 1/3. It means that player II should play column B one-third of the time.
Given payoff matrix is: I II
A -7 3 B 8 -2
Here, for player II,
there are two strategies, A and B.
Similarly, for the player I, there are two strategies A and B.
The row player I will choose strategy A if he has to choose between A and B, when he knows that player II is going to choose strategy A;
similarly, he will choose strategy B if he knows that player II is going to choose strategy B.
Similarly, the column player II will choose strategy A if he has to choose between A and B, when he knows that player I is going to choose strategy A;
similarly, he will choose strategy B if he knows that player I is going to choose strategy B.
Now, we will find out the Nash Equilibrium of this payoff matrix by following these steps:
Find the maximum value in each row.
In row 1, the maximum value is 3, and it is in the 2nd column.
So , the player I chooses is strategy B in row 1.
In row 2, the maximum value is 8, and it is in the 1st column.
So, player, I chooses strategy A in row 2
Find the maximum value in each column.
In column 1, the maximum value is 8, and it is in the 2nd row. So, player II chooses strategy B in column 1.
In column 2, the maximum value is 3, and it is in the 1st row. So, player II chooses strategy A in column 2.
The Nash Equilibrium of this payoff matrix is at the intersection of the two choices made, which is at cell (2,2), where player I chooses strategy B and player II chooses strategy B. The payoff at this cell is 2.
The fraction of the time player II should play Column is 1/3. It means that player II should play column B one-third of the time.
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Answer should be obtained without any preliminary rounding. However, the critical value may be rounded to 3 decimal places. Question 3 2 pts 1 Details The effectiveness of a blood-pressure drug is being investigated. An experimenter finds that, on average, the reduction in systolic blood pressure is 75.4 for a sample of size 555 and standard deviation 9.3. Estimate how much the drug will lower a typical patient's systolic blood pressure (using a 80% confidence level). Enter your answer as a tri-linear inequality accurate to one decimal place (because the sample statistics are reported accurate to one decimal place). εμε Answer should be obtained without any preliminary rounding.
The 80% confidence interval for the mean systolic blood pressure reduction is given as follows:
[tex]74.9 < \mu < 75.9[/tex]
What is a z-distribution confidence interval?The bounds of the confidence interval are given by the rule presented as follows:
[tex]\overline{x} \pm z\frac{\sigma}{\sqrt{n}}[/tex]
In which:
[tex]\overline{x}[/tex] is the sample mean.z is the critical value.n is the sample size.[tex]\sigma[/tex] is the standard deviation for the population.Using the z-table, for a confidence level of 80%, the critical value is given as follows:
z = 1.28.
The parameters are given as follows:
[tex]\overline{x} = 75.4, \sigma = 9.3, n = 555[/tex]
The lower bound of the interval is given as follows:
[tex]75.4 - 1.28 \times \frac{9.3}{\sqrt{555}} = 74.9[/tex]
The upper bound of the interval is given as follows:
[tex]75.4 + 1.28 \times \frac{9.3}{\sqrt{555}} = 75.9[/tex]
Hence the inequality is:
[tex]74.9 < \mu < 75.9[/tex]
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