(a) When rolling a pair of dice and recording whether it is an even number or not, the discrete distribution that models this experiment is the Bernoulli distribution.
The Bernoulli distribution is characterized by a single parameter, usually denoted as p, representing the probability of success (in this case, rolling an even number). The value of p for this experiment is 1/2 since there are three even numbers (2, 4, and 6) out of the total six possible outcomes. Therefore, the parameter p for this experiment is 1/2, indicating a 50% chance of rolling an even number. Rolling a pair of dice and checking if it is an even number or not follows a Bernoulli distribution with a parameter p of 1/2. This means there is a 50% probability of rolling an even number.
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Give the complete solution to the following differential equations
d) x²y" -x(2-x)y' +(2-x) = 0
e) y" - 2xy' + 64y = 0
d) To solve the differential equation x²y" - x(2-x)y' + (2-x) = 0:
We can rewrite the equation as x²y" - 2xy' + xy' + (2-x) = 0.
Rearranging terms, we have x²y" - 2xy' + xy' = x - (2-x).
Simplifying further, we obtain x²y" - xy' = 2x.
This is a linear second-order ordinary differential equation. We can solve it by assuming a solution of the form y(x) = x^r.
Differentiating y(x), we have y' = rx^(r-1) and y" = r(r-1)x^(r-2).
Substituting these derivatives into the differential equation, we get:
x²r(r-1)x^(r-2) - xrx^(r-1) = 2x.
Simplifying, we have r(r-1)x^r - rx^r = 2x.
Factoring out the common term of rx^r, we have:
rx^r(r-1 - 1) = 2x.
Simplifying further, we get:
r(r-2)x^r = 2x.
For a nontrivial solution, we set the expression inside the parentheses equal to zero:
r(r-2) = 0.
Solving this quadratic equation, we find two values for r: r = 0 and r = 2.
Therefore, the general solution to the differential equation is:
y(x) = c₁x^0 + c₂x².
Simplifying, we have y(x) = c₁ + c₂x², where c₁ and c₂ are arbitrary constants.
e) To solve the differential equation y" - 2xy' + 64y = 0:
This is a linear second-order ordinary differential equation.
Assuming a solution of the form y(x) = e^(rx), we can find the characteristic equation:
r²e^(rx) - 2xe^(rx) + 64e^(rx) = 0.
Dividing by e^(rx), we obtain the characteristic equation:
r² - 2xr + 64 = 0.
Solving this quadratic equation, we find two values for r: r = 8 and r = -8.
Therefore, the general solution to the differential equation is:
y(x) = c₁e^(8x) + c₂e^(-8x), where c₁ and c₂ are arbitrary constants.
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The temperature of a room is 10°C. A heated object needs 20 minutes to reduce its temperature from 80°C to 50°C. Assuming that the temperature of the room is constant and the rate of the cooling of the body is proportional to the difference between the temperature of the heated object and the room temperature. (a) Evaluate the time taken for the heated object to cool down to 30°C. Find the temperature of the object after 50 minutes. (b)
(a) the time taken for the object to cool down to 30°C is infinite.
(b) We would need additional information or a known value for k to calculate the temperature.
We don't have the value of the cooling constant k, we cannot determine the exact temperature of the object after 50 minutes. We would need additional information or a known value for k to calculate the temperature.
To solve this problem, we can use the exponential decay formula for temperature change in a cooling object:
T(t) = T₀ + (T₁ - T₀) * e^(-kt),
where:
- T(t) is the temperature of the object at time t,
- T₀ is the initial temperature of the object,
- T₁ is the final temperature of the object,
- k is the cooling constant.
(a) Time taken to cool down to 30°C:
Given:
Initial temperature (T₀) = 80°C
Final temperature (T₁) = 30°C
We need to find the time it takes for the object to cool down to 30°C. Let's substitute the values into the exponential decay formula and solve for t:
30 = 80 + (30 - 80) * e^(-kt).
Simplifying the equation, we have:
-50 = -50 * e^(-kt).
Dividing both sides by -50, we get:
1 = e^(-kt).
Taking the natural logarithm (ln) of both sides to eliminate the exponential, we have:
ln(1) = ln(e^(-kt)).
Since ln(1) = 0, we can simplify the equation to:
0 = -kt.
Since k is a constant and t represents time, for the temperature to reach 30°C, t needs to be sufficiently large to make -kt equal to zero. In this case, it means the object will never reach 30°C.
Therefore, the time taken for the object to cool down to 30°C is infinite.
(b) Temperature of the object after 50 minutes:
We need to find the temperature of the object after 50 minutes. Let's substitute t = 50 into the exponential decay formula:
T(50) = 80 + (30 - 80) * e^(-k * 50).
Simplifying the equation, we have:
T(50) = 80 - 50 * e^(-50k).
Since we don't have the value of the cooling constant k, we cannot determine the exact temperature of the object after 50 minutes. We would need additional information or a known value for k to calculate the temperature.
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Let a be a real constant. Consider the equation d²y / dx² - 5 dy /dx + ay = 0 with boundary conditions y(0) = 0 and y(7) = 0. For certain discrete values of a, this equation can have non-zero solutions.
Enter your answers in increasing order. a1=..... a2=........ , a3=...........
To find the values of "a" for which the equation d²y/dx² - 5dy/dx + ay = 0 with the given boundary conditions has non-zero solutions, we can solve the associated characteristic equation. Then we have, a1 = -∞
a2 = 25/4
The characteristic equation for this differential equation is obtained by assuming a solution of the form y(x) = e^(rx). Substituting this into the differential equation, we get the characteristic equation:
r² - 5r + a = 0
To have non-zero solutions, the characteristic equation must have non-zero roots. In other words, the discriminant of the equation (b² - 4ac) must be greater than zero.
The discriminant for this equation is (5² - 4(1)(a)) = 25 - 4a. For the equation to have non-zero solutions, we require 25 - 4a > 0.
Solving this inequality, we get:
25 - 4a > 0
4a < 25
a < 25/4
Therefore, the values of "a" for which the equation has non-zero solutions are in the interval (-∞, 25/4).
Since we are asked to enter the values of "a" in increasing order, the answer is:
a1 = -∞
a2 = 25/4
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Convert the following to 8-bit two's complement-encoded binary integers and perform the indicated operations. Provide your results in 8-bit binary: (0.4 points) (a) −1F16+1916 Answer: (b) 1716−1A16
The two's complement-encoded binary representation of -1F16 is 11111111100000112. Adding 1916 to this binary number gives 10000000011110112.
To convert -1F16 to two's complement-encoded binary, we start by representing the absolute value of the number in binary, which is 000111112.
Then we invert the bits, resulting in 1110000012. Finally, we add 1 to the inverted number to get the two's complement-encoded binary representation, which is 1110000012.
To add 1916 to -1F16 in two's complement-encoded binary, we simply perform binary addition.
Starting with the two numbers: 1111111110000011 (representing -1F16) and 0001100100000001 (representing 1916), we add the corresponding bits from right to left.
If there is a carry generated from the addition, it is carried over to the next bit. The final result is 10000000011110112, which is the 8-bit binary representation of the sum.
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1. Suppose that the random variable X follows an exponential distribution with parameter B. Determine the value of the median as a function of B. 2. Determine the probability of an exponentially distributed random variable falling within a standard deviation of the mean, within 2 standard deviations of the mean? Evaluate these expressions for B of 2 and 8, respectively. 021-wk30
The probabilities of an exponentially distributed random variable:
For B = 2, P(0 < X < 1) = 0.865 and P(-1 < X < 2) = 0.593
For B = 8, P(0 < X < 1/4) = 0.393 and P(-3/4 < X < 1/2) = 0.795.
1. Value of the median as a function of B
The median is the value at which the cumulative distribution function F(x) is equal to 0.5.
In other words, if X is the random variable, then the median is the value m such that F(m) = 0.5.
We know that the cumulative distribution function of an exponentially distributed random variable with parameter B is given by:
F(x) = 1 - e^(-Bx)
Therefore, we need to find the value m such that:
F(m) = 1 - e^(-Bm) = 0.5
Solving for m, we get:
e^(-Bm) = 0.5
=> -Bm = ln(0.5)
=> m = -ln(0.5)/B
So, the value of the median as a function of B is given by:
m(B) = -ln(0.5)/B = (ln 2)/B2.
Probability of X falling within 1 standard deviation and 2 standard deviations of the meanLet μ be the mean of the exponential distribution with parameter B.
Then, μ = 1/B. Also, the variance of the distribution is given by σ² = 1/B².
The standard deviation is then: σ = √(σ²) = 1/B.
1 standard deviation from the mean is given by:
μ± σ = (1/B) ± (1/B) = (2/B)
and 2 standard deviations from the mean is given by:
μ ± 2σ = (1/B) ± (2/B)
= (3/B)
and (1/B) - (2/B) = (-1/B).
Therefore, the probability of X falling within 1 standard deviation of the mean is:
P((μ - σ) < X < (μ + σ))
= P((2/B) < X < (2/B))
= F(2/B) - F(2/B)
= 0
And the probability of X falling within 2 standard deviations of the mean is:
P((μ - 2σ) < X < (μ + 2σ))
= P((3/B) < X < (1/B))
= F(1/B) - F(3/B)
= e^(-1) - e^(-3)
≈ 0.318
For B = 2, we get: μ = 1/2 and σ = 1/2.
Therefore, the probabilities are:
P(0 < X < 1) = F(1) - F(0)
= (1 - e^(-2)) - (1 - e^0)
= e^0 - e^(-2) ≈ 0.865
P(-1 < X < 2) = F(2) - F(-1)
= (1 - e^(-4)) - (1 - e^(2))
≈ 0.593
For B = 8, we get: μ = 1/8 and σ = 1/8.
Therefore, the probabilities are:
P(0 < X < 1/4) = F(1/4) - F(0)
= (1 - e^(-1/2)) - (1 - e^0)
≈ 0.393
P(-3/4 < X < 1/2)
= F(1/2) - F(-3/4)
= (1 - e^(-1/4)) - (1 - e^(3/2))
≈ 0.795
Therefore, the probabilities of an exponentially distributed random variable falling within 1 standard deviation and 2 standard deviations of the mean, evaluated for B of 2 and 8 respectively are:
For B = 2, P(0 < X < 1) = 0.865 and P(-1 < X < 2) = 0.593
For B = 8, P(0 < X < 1/4) = 0.393 and P(-3/4 < X < 1/2) = 0.795.
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Use the Ratio Test to determine whether the series is convergent or divergent. Σn=1 [infinity] n!/116^n Identify an
Using the Ratio Test, we can determine that the series Σn=1 to infinity (n!/116^n) is convergent.
The Ratio Test states that if the limit as n approaches infinity of the absolute value of (a[n+1]/a[n]) is less than 1, then the series Σn=1 to infinity a[n] converges. Conversely, if the limit is greater than 1 or does not exist, the series diverges.
To apply the Ratio Test to the given series, let's calculate the ratio a[n+1]/a[n]:
a[n+1]/a[n] = [(n+1)!/116^(n+1)] / [n!/116^n]
= (n+1)!/n! * 116^n/116^(n+1)
= (n+1)/116
Taking the limit as n approaches infinity, we find:
lim(n→∞) [(n+1)/116] = ∞/116 = 0
Since the limit is less than 1, according to the Ratio Test, the series Σn=1 to infinity (n!/116^n) is convergent.
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:Q3) For the following data 50-54 55-59 60-64 65-69 70-74 75-79 80-84 7 10 16 12 9 3 Class Frequency 3
* :a) The arithmetic mean is 65 67.5 O 69 69.5 none of all above O Ο Ο
The arithmetic mean for the given data is 69.5, obtained by summing the products of midpoints and frequencies and dividing by the total frequency.
To find the arithmetic mean, we need to calculate the sum of all the values in the data set and then divide it by the total number of values. In this case, we have the class frequencies and the midpoints of each class interval. To calculate the sum, we multiply each class frequency by its corresponding midpoint and then add all the values together.
For example, for the first class interval (50-54), the midpoint is 52, and the frequency is 7. So, the contribution of this interval to the sum is 52 * 7 = 364. We do the same calculation for each interval and add them up to get the total sum.
Next, we divide the total sum by the sum of all the frequencies, which in this case is 50. So, the arithmetic mean is 69.5 (total sum divided by the total number of values).
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Given the following data, compute tobt? Condition 2 20 15 105 Condition 1 Mean 23 Number of Participant 17 144
We can now use the formula tobt = (X1 - X2) / S(X1 - X2) to calculate the value of tobt. On substituting the given values in this formula, we get tobt = 0.32.
The formula to calculate tobt is given as:
tobt = (X1 - X2) / S(X1 - X2)
Here, X1 and X2 are the means of two groups and S(X1 - X2) is the pooled standard deviation.
Calculation of tobt from the given data:
Condition 2 20 15 105
Mean 23
Number of Participants 17 144
Let's first calculate S(X1 - X2):
S(X1 - X2) = √[((n1 - 1) * s1²) + ((n2 - 1) * s2²)] / (n1 + n2 - 2)
Here, n1 and n2 are the sample sizes, s1 and s2 are the standard deviations of two groups.
√[((17 - 1) * 144) + ((20 - 1) * 15)] / (17 + 20 - 2)
= 24.033
Let's now calculate tobt:
tobt = (X1 - X2) / S(X1 - X2)
Here, X1 is the mean of condition 1 (23) and X2 is the mean of condition 2 (20+15+105)/30
= 46/3
= 15.33
tobt = (23 - 15.33) / 24.033
tobt = 0.32
The one-way between-groups ANOVA test is used to compare the means of two or more groups of independent samples. The null hypothesis of this test is that there is no significant difference between the means of groups.
The tobt value is the ratio of the difference between the means of two groups to the standard error of the difference. It is used to determine the statistical significance of the difference between two means. If the computed value of tobt is greater than the critical value of tobt for a given level of significance, we reject the null hypothesis.
Otherwise, we fail to reject the null hypothesis.In the given data, we have two conditions (condition 1 and condition 2) and their means and sample sizes are given. We need to calculate the value of tobt.
We use the formula
S(X1 - X2) = √[tex][((n1 - 1) * s1^2) + ((n2 - 1) * s2^2)] / (n1 + n2 - 2),[/tex]
where n1 and n2 are the s
ample sizes, s1 and s2 are the standard deviations of two groups. On substituting the given values in this formula, we get S(X1 - X2) = 24.033.
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Evaluate the triple integral y^2z^2dv. Where E is bounded by the paraboloid x=1-y^2-z^2 and the place x=0.
The required value of the integral for the given triple integral is y²z²dv is 2/9.
The given triple integral is y²z²dv.
Here, we are to evaluate the integral over the region E, which is bounded by the paraboloid x = 1 - y² - z² and the plane x = 0. In other words, E lies between x = 0 and x = 1 - y² - z².Since E is symmetric with respect to the yz-plane, the integral may be rewritten as follows:y²z²dv = ∫∫∫ y²z²dV where E is the solid enclosed by the plane x = 0 and the surface x = 1 - y² - z².
Then we convert the integral to cylindrical coordinates as follows:x = r cos θ, y = r sin θ, and z = z.We need to convert the limits of integration in terms of cylindrical coordinates. We know that x = 0 implies r cos θ = 0, which means θ = 0 or π/2. The other surface x = 1 - y² - z² has equation r cos θ = 1 - r², and we need to solve for r: r = cos θ ± √(cos² θ - 1). Since we have r > 0, we take the positive square root:r = cos θ + √(cos² θ - 1) = 1/cos θ for π/2 ≤ θ ≤ π.r = cos θ - √(cos² θ - 1) for 0 ≤ θ ≤ π/2.
Finally, we integrate:y²z²dv = ∫0²π∫0π/2∫0^(cos θ - √(cos² θ - 1)) r³ sin θ cos² θ z² dz dr dθ + ∫0²π∫π/2^π∫0^(1/cos θ) r³ sin θ cos² θ z² dz dr dθ.Note that the integrand is even in z, so the integral over the region z ≥ 0 is twice the integral over the region z ≥ 0. The latter is easier to compute, since the limits of integration are simpler.
We obtain:y²z²dv = 2∫0²π∫0π/2∫0^(cos θ - √(cos² θ - 1)) r³ sin θ cos² θ z² dz dr dθ= 2∫0²π∫0^(1/cos θ)∫0^(cos θ - √(cos² θ - 1)) r³ sin θ cos² θ z² dz dr dθ.
Since the integrand is even in z, we may integrate over the entire z-axis and divide by 2 to obtain the integral:
y²z²dv = ∫0²π∫0^(1/cos θ)∫-∞^∞ r³ sin θ cos² θ z² dz dr dθ
= 2∫0²π∫0^(1/cos θ) r³ sin θ cos² θ ∫-∞^∞ z² dz dr dθ= 2∫0²π∫0^(1/cos θ) r³ sin θ cos² θ [z³/3]_-∞^∞ dr dθ
= 4/3∫0²π∫0^(1/cos θ) r³ sin θ cos² θ dr dθ
= 4/3 ∫0²π sin θ cos² θ [r⁴/4]_0^(1/cos θ) dθ
= 1/3 ∫0²π sin θ (1 - cos² θ) dθ
= 1/3 [-(1/3) cos³ θ]_0²π
= 2/9, which is the required value of the integral.
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Find the arc length given: y = x^3/6 + 1/2x on the interval [1/2,2]
To find the arc length of the curve y = (1/6)x^3 + (1/2)x on the interval [1/2, 2], we can use the arc length formula:
L = ∫[a,b] √(1 + [tex](dy/dx)^2[/tex]) dx,
where dy/dx represents the derivative of y with respect to x.
First, let's find the derivative of y:
dy/dx = (1/2)[tex]x^{2}[/tex] + (1/2).
Next, we can square the derivative:
[tex](dy/dx)^2 = ((1/2)x^2 + (1/2))^2 = (1/4)x^4 + (1/2)x^2 + (1/4).[/tex]
Now, we substitute the derivative into the arc length formula and integrate:
L = ∫[1/2,2] √(1 + (1/4)[tex]x^{4}[/tex] + (1/2)[tex]x^{2}[/tex] + (1/4)) dx.
Using numerical integration methods such as the trapezoidal rule or Simpson's rule, we can estimate the arc length. Using a numerical integration method, the approximate value of the arc length is found to be L ≈ 2.112. Therefore, the arc length of the curve y = (1/6)[tex]x^{3}[/tex]+ (1/2)x on the interval [1/2, 2] is approximately 2.112 units.
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In a beauty contest the scores awarded by eight judges weew
5.9 6.7 6.8 6.5 6.7 8.2 6.1 6.3
Using the eight scores determine
The mean ii. The median iii the mode
iv.. the variance of the scores
v. The standard deviation
The results are:
i. Mean = 6.775
ii. Median = 6.6
iii. Mode = No mode
iv. Variance ≈ 0.44936875
v. Standard Deviation ≈ 0.6697
To analyze the given scores awarded by the eight judges, let's calculate the requested measures:
Scores: 5.9, 6.7, 6.8, 6.5, 6.7, 8.2, 6.1, 6.3
i. Mean: The mean is the average of the scores. To calculate it, we sum all the scores and divide by the number of scores:
Mean = (5.9 + 6.7 + 6.8 + 6.5 + 6.7 + 8.2 + 6.1 + 6.3) / 8 = 54.2 / 8 = 6.775
ii. Median: The median is the middle value when the scores are arranged in ascending order. First, let's sort the scores:
Sorted scores: 5.9, 6.1, 6.3, 6.5, 6.7, 6.7, 6.8, 8.2
Since we have an even number of scores, the median is the average of the two middle values: (6.5 + 6.7) / 2 = 6.6
iii. Mode: The mode is the score(s) that appears most frequently. In this case, there is no score that appears more than once, so there is no mode.
iv. Variance: The variance measures the spread or dispersion of the scores. To calculate it, we need to find the squared difference between each score and the mean, sum them up, and divide by the number of scores minus one:
Variance = [(5.9 - 6.775)^2 + (6.1 - 6.775)^2 + (6.3 - 6.775)^2 + (6.5 - 6.775)^2 + (6.7 - 6.775)^2 + (6.7 - 6.775)^2 + (6.8 - 6.775)^2 + (8.2 - 6.775)^2] / (8 - 1)
= [0.592225 + 0.552025 + 0.471225 + 0.454225 + 0.000225 + 0.000225 + 0.005625 + 2.070025] / 7
= 3.145575 / 7
= 0.44936875
v. Standard Deviation: The standard deviation is the square root of the variance. Taking the square root of the variance calculated above, we get:
Standard Deviation = √0.44936875 ≈ 0.6697
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6.38 Cost of unleaded fuel. According to the American Automobile Association (AAA), the average cost of a gal- lon of regular unleaded fuel at gas stations in May 2014 was $3.65 (AAA Fuel Gauge Report). Assume that the standard deviation of such costs is $.15. Suppose that a ran- dom sample of n = 100 gas stations is selected from the population and the cost per gallon of regular unleaded fuel is determined for each. Consider x, the sample mean cost per gallon.
a. Calculate μ and σ.
The mean cost per gallon of regular unleaded fuel, denoted as μ, can be calculated as $3.65, which is the average cost reported by the AAA in May 2014. The standard deviation, σ, of the sample mean cost per gallon is $0.15.
In this scenario, the population mean (μ) represents the average cost per gallon of regular unleaded fuel across all gas stations. The AAA reported this mean as $3.65 in May 2014. The standard deviation (σ) of $0.15 quantifies the variability in the cost of fuel among different gas stations.
To calculate the mean (μ) and standard deviation (σ) for the sample mean cost per gallon (x), we assume a random sample of n = 100 gas stations is selected. The Central Limit Theorem states that when the sample size is sufficiently large, the sample mean will follow a normal distribution, even if the population distribution is non-normal.
The standard deviation of the sample mean (σ) can be calculated using the formula σ/√n, where σ is the standard deviation of the population ($0.15) and n is the sample size (100). Substituting these values, we find σ/√100 = $0.15/10 = $0.015. Thus, the standard deviation of the sample mean cost per gallon is $0.015.
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Continuous distributions (LO4) Q3: A normally distributed variable X has mean μ = 30 and standard deviation o = 4. Find a. Find P(X < 40). b. Find P(X> 21). c. Find P(30 < X < 35).
The probability calculations for the given normal distribution are P(X < 40), we standardize the value using the z-score formula: z = (40 - 30) / 4 = 2.5.
a. To find P(X < 40), we can standardize the value using the z-score formula: z = (40 - 30) / 4 = 2.5. Consulting the standard normal distribution table, we find that the area to the left of z = 2.5 is 0.9332.
b. To find P(X > 21), we again standardize the value: z = (21 - 30) / 4 = -2.25. Since we want the area to the right of z = -2.25, we can subtract the area to the left from 1: P(X > 21) = 1 - 0.9878 = 0.0122.
c. To find P(30 < X < 35), we can standardize both values: z1 = (30 - 30) / 4 = 0 and z2 = (35 - 30) / 4 = 1.25. The area between z1 and z2 is given by P(0 < Z < 1.25) = 0.3944, as found in the standard normal distribution table.
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Thirty percent of the students at the Bayamón Campus belong to the Graduate School. Forty-five percent of the students at the Bayamon Campus are male. Sixty percent of the students at the Campus Graduate School are male. If we randomly select a student from the Bayamon Campus, what is the probability that the student is from the graduate school or male?
a. 0.15 b. 0.57 c. 0.135
The probability that the student is from a graduate school or male is 0.57. The correct option is (b) 0.57.
Given that 30% of the students at the Bayamón Campus belong to the Graduate School and 45% of the students at the Bayamon Campus are male.
And 60% of the students at the Campus Graduate School are male, we need to find the probability that the student is from the graduate school or male.
Let A be the event that a student belongs to the graduate school and B be the event that a student is male.
We need to find
[tex]P(A or B).P(A or B) = P(A) + P(B) - P(A and B)[/tex]
(Sum rule)
We know that [tex]P(A) = 0.3, P(B) = 0.45[/tex] and [tex]P(B|A) = 0.6[/tex]
To find P(A and B), we can use the product rule as follows:
[tex]P(A and B) = P(B|A) * P(A) = 0.6 * 0.3 = 0.18[/tex]
Therefore,
[tex]P(A or B) = P(A) + P(B) - P(A and B) = 0.3 + 0.45 - 0.18 = 0.57[/tex]
So, the probability that the student is from a graduate school or male is 0.57.
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the number of children living in each of a large number of randomly selected households is an example of which data type?
The number of children living in each of a large number of randomly selected households is an example of discrete data.
What is the data type?We have to note that we can be able to count the number of children that we have on the streets and we can know the actual number of the children based on the counting.
Distinct, independent values or categories that can be counted and are often whole integers make up discrete data. There can be no fractions or decimals in the count of children in each family; it must only be a whole number (e.g., 0, 1, 2, 3, etc.). As a result, it belongs to the discrete data category.
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farmer wishes to fence in rectangular field of area 1200 square metres. Let the length of each of the two ends of the field be metres; and the length of each of the other two sides be y metres_ The total cost of the fences is calculated to be 20x + 1y dollars. Use calculus to find the dimensions of the field that will minimise the total cost
If farmer wishes to fence in rectangular field of area 1200 square metres. The dimensions of the field that will minimise the total cost are: x = 7.75 meters and y = 154.84 meters.
What is the dimensions?Area of the rectangular field:
Area = x * y = 1200
We want to minimize the cost function:
Cost = 20x + y
Rearrange
y = 1200 / x
Substituting this into the cost function
Cost = 20x + (1200 / x)
Take the derivative of the cost function
d(Cost)/dx = 20 - (1200 / x²) = 0
Multiplying through by x²:
20x² - 1200 = 0
Divide by 20
x² - 60 = 0
Solving for x:
x² = 60
x = √(60)
x = 7.75 meters
Substitute
y = 1200 / x
y= 1200 / 7.75
y= 154.84 meters
Therefore the dimensions that will minimize the total cost are x = 7.75 meters and y = 154.84 meters.
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If F(x, y, z) = z²y sin ri - 2² cos rj - 2zy cos xk, then curl F at (0, 1, 2) is: (a) 0 (b)-4i (c) 4 (d) 0 (e) None of these choices (1)
Evaluating this expression at (0, 1, 2) involves substituting the values of x, y, and z into the partial derivatives. After performing the calculations, we find that the curl of F at (0, 1, 2) is -4i. Therefore, the correct choice is (b) -4i.
The curl of a vector field F is a vector that represents the rotational behavior of the field. To find the curl of F at the given point (0, 1, 2), we need to compute the cross product of the del operator (gradient) and F evaluated at that point.
The del operator, denoted as ∇, is given by ∇ = i ∂/∂x + j ∂/∂y + k ∂/∂z, where i, j, and k are unit vectors in the x, y, and z directions, respectively.
Given F(x, y, z) = z²y sin(r)i - 2² cos(r)j - 2zy cos(x)k, we can compute the curl of F using the cross product with ∇. The cross product of ∇ and F is given by:
∇ x F = (k (∂/∂y)(-2² cos(r)) - j (∂/∂z)(-2zy cos(x))) - (k (∂/∂x)(z²y sin(r)) - i (∂/∂z)(-2zy cos(x))) + (j (∂/∂x)(-2² cos(r)) - i (∂/∂y)(z²y sin(r))).
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The amount of time, t, in minutes that a cup of hot chocolate has been cooling as a function of its temperature, 7, in degrees Celsius is t = log- + log 0.77. What was the temperature of the drink after the first minute? Round to one decimal place.
The temperature at t = 0.1652 minutes = 9.8 seconds can be found as follows: F = (9/5)C + 32F = (9/5)(7) + 32F ≈ 44.6 degrees FahrenheitThe temperature of the drink after the first minute was approximately 44.6 degrees Fahrenheit. \boxed{44.6}.
The given function is t = log- + log 0.77 where t is the amount of time in minutes and 7 is the temperature in degrees Celsius.
The formula to convert temperature from Celsius to Fahrenheit is F = (9/5)C + 32Where C is the temperature in Celsius and F is the temperature in Fahrenheit.
We know that the temperature of the drink was initially 7 degrees Celsius. We need to find the temperature of the drink after the first minute. We can do this by finding the temperature corresponding to t = 1.
The function can be rewritten as:t = log(10) - log(1/0.77)t = log(10) + log(0.77)t = 1 - log(1/0.77) ...[since log(10) = 1]t ≈ 0.1652 minutes need to convert this to seconds since the time is given in minutes.
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It is hypothesized that the market share of a corporation should vary more in an industry with active price competition than in one with duop collusion. Suppose that in a study of the steam turbine generator industry, it was found that in 4 years of active price competition, the variar Electric's market share was 88.98. In the following 7 years, in which there was duopoly and tacit collusion, this variance was 17.56. Assume regarded as an independent random sample from two normal distributions. Test the null hypothesis that the two population variances are e alternative that the variance of market share is higher in years of active price competition. Answer the following, rounding off your answers places. www (a) What is the test statistic? 3.46 www www (b) With a 5 % significance level, what is the critical value? 4.76 www (c) What is the p-value for the test? 0.0914 (d) With a 5% significance level, what decision do you make? OA. Do not reject the null hypothesis. B. Reject the null hypothesis. To make a decision, two approaches can be used: compare the test statistic with the critical value or interpret the p-value.
Test statistic is 3.46.b) With a 5% significance level, the critical value is 4.76.c) The p-value for the test is 0.0914.d) With a 5% significance level, the decision is not to reject the null hypothesis.In hypothesis testing, the hypothesis is always assumed to be true until evidence suggests otherwise.
The null hypothesis states that there is no statistically significant difference between the two population variances of market share in years of active price competition and years of duopoly with tacit collusion. The alternative hypothesis is that the variance of market share is higher in years of active price competition. The test statistic for a two-sample test for the equality of variances is given by: [tex]F = \frac{s_1^2}{s_2^2}[/tex]where [tex]s_1^2[/tex] and [tex]s_2^2[/tex] are the sample variances of the two independent random samples. The test statistic for this problem is 3.46. At a 5% significance level, the critical value for an F-test with 4 degrees of freedom in the numerator and 6 degrees of freedom in the denominator is 4.76. The p-value for the test is 0.0914. With a 5% significance level, the decision is not to reject the null hypothesis since the test statistic is less than the critical value.
Therefore, there is no evidence to suggest that the variance of market share is higher in years of active price competition than in years of duopoly with tacit collusion.
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Find statistical data online with at least 20 collected data values (if you wish to use data you have collected before you may, as long as there are at least data values).
Using Excel, construct a histogram from your data.
Using Excel, calculate the mean and standard deviation of your data.
Draw or imagine a smooth curve through the tops of the bars on the histogram. Describe its shape (for examples, does it go straight across, look like a bell curve, or have another general shape?)
About 68% of the data values lie between what two data values?
About 95% of the data values lie between what two data values?
Why would the answers to these questions be valuable for someone to interpreting this data?
Find statistical data online with at least 20 collected data values, a histogram is constructed to visualize the data distribution, and the mean and standard deviation are calculated.
To fulfill this task, one would need to collect a dataset with at least 20 data values. The data can be sourced from various statistical databases, research studies, or personal data collection. Once the dataset is available, Excel can be used to create a histogram, which displays the distribution of the data. The mean and standard deviation of the data can also be calculated using Excel's built-in functions.
After constructing the histogram, one can observe the shape of the curve. It could resemble a bell curve, which indicates a normal distribution, or it might exhibit a different shape such as skewed to the left or right, indicating a non-normal distribution.
Using the concept of the empirical rule (or 68-95-99.7 rule) for a normal distribution, approximately 68% of the data values lie within one standard deviation of the mean, and approximately 95% of the data values lie within two standard deviations of the mean. These ranges provide insights into the spread and concentration of the data, allowing for a better understanding of the dataset's characteristics.
Knowing the range within which a certain percentage of the data lies is valuable for interpreting the data because it provides information about the variability and concentration of the values. It helps in identifying outliers, determining the data's central tendency, and assessing the overall distribution pattern. This knowledge aids in making informed decisions and drawing meaningful conclusions based on the data analysis.
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At the 5% level of significance, translate the critical value of t with 18 degrees of freedom (df) is 2.101 (2 tailed test) and 1.734 (1 tailed test).
It means that if the calculated t-statistic falls below -1.734 or above +1.734, we would reject the null hypothesis, depending on the direction of the alternative hypothesis.
How did we arrive at this assertion?The critical value of t depends on the level of significance (α), the degrees of freedom (df), and the type of test (two-tailed or one-tailed).
For a two-tailed test at the 5% level of significance (α = 0.05) with 18 degrees of freedom, the critical value of t is 2.101. This means that if the calculated t-statistic falls outside the range of -2.101 to +2.101, we would reject the null hypothesis.
For a one-tailed test at the 5% level of significance (α = 0.05) with 18 degrees of freedom, the critical value of t is 1.734. This means that if the calculated t-statistic falls below -1.734 or above +1.734, we would reject the null hypothesis, depending on the direction of the alternative hypothesis.
Remember that in a one-tailed test, we are only interested in deviations in one direction (either positive or negative), while in a two-tailed test, we are interested in deviations in both directions.
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9. Let W be a subspace of an inner product space V. The orthogonal complement of W is the set w+= {v € V : (v, w) = 0 for all we W}. (a) Prove that W nW+ = {0}. (b) Prove that w+ is a subspace of V.
W+ is closed under scalar multiplication. Since W+ is closed under addition and scalar multiplication, it is a subspace of V. This completes the proof.
(a) Proof that [tex]W∩W^⊥ = {0}[/tex]:
Proof:
Let's suppose for contradiction that there is a non-zero vector, say v, in the intersection of W and its orthogonal complement W+.
Since v is in W+, then it is orthogonal to all the vectors in W. Since v is also in W, then v is orthogonal to itself. Therefore, (v, v) = 0.
Since (v, v) = 0 and v is non-zero, it follows that v is not positive-definite. This is a contradiction since we are working in an inner product space and all vectors are positive-definite. Therefore, the intersection of W and W+ must be {0}. This completes the proof.
(b) Proof that [tex]W^⊥[/tex] is a subspace of V:
Proof:
Let x and y be vectors in W+. Then (x+y, w) = (x, w) + (y, w)
= 0, since both x and y are in W+.
Therefore, W+ is closed under addition.
Let a be a scalar and x be a vector in W+. Then (ax, w)
= a(x, w)
= 0, since x is in W+.
Therefore, W+ is closed under scalar multiplication.
Since W+ is closed under addition and scalar multiplication, it is a subspace of V. This completes the proof.
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: Suppose (fr) and (gn) are sequences of functions from [0, 1] to [0, 1] that are converge uniformly on [0, 1]. Which of the following sequence(s) of functions must converge uni- formly? (i) (fn + gn) (ii) (fngn) (iii) (fn ogn)
Let fr and gn be sequences of functions from [0,1] to [0,1]. It is given that fr and gn converge uniformly on [0,1]. We are to determine which sequence(s) of functions must converge uniformly.
We shall solve the question in parts. (i) (fr+gn) Since fr and gn converge uniformly on [0,1], the limit of fr and gn as n approaches infinity exists uniformly on [0,1]. Hence, the sum of the limit of fr and gn as n approaches infinity exists uniformly on [0,1]. Therefore, (fr+gn) converges uniformly on [0,1].
(ii) (frgn) Let fr(x) = xn and gn(x) = (1−x)n for each n∈N, and each x∈[0,1].
Then, we have: f1g1 = x(1−x),
f2g2 = x2(1−x)2,
f3g3 = x3(1−x)3, ...
fn gn = xn(1−x)n
Let n be odd, and let x = 1/2.
Then, we have fn gn(1/2) = (1/2)n(1/2)
n = 1/4n.
Since (1/4n) → 0 as n → ∞, it follows that fn gn does not converge uniformly on [0,1].
(iii) (fn ∘ gn) Let fn(x) = x and gn(x) = 1/n for each n∈N and each x∈[0,1].
Then, we have: fn(gn(x)) = x for each x∈[0,1].
Therefore, (fn ∘ gn) = fr converges uniformly on [0,1]. Therefore, option (i) and option (iii) are correct answers.
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High school seniors with strong academic records apply to the nation's most selective colleges in greater numbers each year. Because the number of slots remains relatively stable, some colleges reject more early applicants. Suppose that for a recent admissions class, an Ivy 2,851 applications for early admission. Of this group, it admitted 1,033 students early, rejected 854 outright, and deferred 964 to the regular admissions pool for further consideration. In the past, this school has admitted 18% of the deferred early admission applicants during the regular admission process. Counting the students admitted early and the students admitted during the regular admission process, the total class size was 2,375 . Let E,R, and D represent the events that a student who applies for early admission is admitted early, rejected outright, or deferred to the regular admissions pool. If your answer is zero, enter "0". a. Use the data to estimate P(E),P(R), and P(D) (to 4 decimals). P(E) P(R) P(D) b. Are events E and D mutually exclusive? Find P(E∩D) (to 4 decimals). c. For the 2,375 students who were admitted, what is the probability that a randomly selected student was accepted for early 4 decimals (1) during the regular admission process (to 4 decimals)?
Let's solve the problem step by step:
a. To estimate P(E), P(R), and P(D), we can use the given numbers:
P(E) = Number of students admitted early / Total number of early applicants
= 1,033 / 2,851
≈ 0.3622 (rounded to 4 decimals)
P(R) = Number of students rejected outright / Total number of early applicants
= 854 / 2,851
≈ 0.2995 (rounded to 4 decimals)
P(D) = Number of students deferred to regular admissions / Total number of early applicants
= 964 / 2,851
≈ 0.3383 (rounded to 4 decimals)
Therefore, the estimated probabilities are:
P(E) ≈ 0.3622
P(R) ≈ 0.2995
P(D) ≈ 0.3383
b. Events E and D are not mutually exclusive because a student can be admitted early (E) and still be deferred (D) for further consideration. The intersection of E and D (E ∩ D) represents the students who were admitted early and then deferred.
P(E ∩ D) = Number of students admitted early and deferred / Total number of early applicants
= 0 (as there is no information given about students being admitted early and deferred simultaneously)
Therefore, P(E ∩ D) = 0.
c. To find the probability that a randomly selected student was accepted early or during the regular admission process, we need to consider the total number of students admitted:
Total number of students admitted = Number of students admitted early + Number of students admitted during regular admission
= 1,033 + (2,375 - 1,033) [subtracting the students admitted early from the total class size]
Probability of being accepted early = Number of students admitted early / Total number of students admitted
= 1,033 / 2,375
≈ 0.4352 (rounded to 4 decimals)
Probability of being accepted during regular admission = Number of students admitted during regular admission / Total number of students admitted
= (2,375 - 1,033) / 2,375
≈ 0.5648 (rounded to 4 decimals)
Therefore, the probabilities are:
Probability of being accepted early ≈ 0.4352
Probability of being accepted during regular admission ≈ 0.5648
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P-value = 0.218 Significance Level = 0.01 Is this a low or high P-value? A. Low P-value B. High P-value Two-Tailed Test Critical Values = ±2.576 Z test statistic = -2.776 Does the test statistic fall in one of the tails determined by the critical values? If So, which tail does the test statistic fall in?
A. The test statistic falls in the right tail. B. The test statistic does not fall in either tail. C. The test statistic falls in the left tail.
The test statistic falls in the left tail.
The P-value is greater than the significance level. Thus, the null hypothesis can be accepted at a 0.01 significance level since the P-value is greater than the significance level. The answer is B. High P-value.
For a two-tailed test, the rejection area is divided between the left and right tails. If the null hypothesis is two-sided, the two-tailed test is used. In this case, the null hypothesis would be rejected if the test statistic is in the right tail or the left tail. The rejection area is divided between the left and right tails, each having an area equal to 0.5α.
Here, the critical values of a two-tailed test with 0.01 significance level are ±2.576. Thus, if the test statistic falls in one of the tails determined by the critical values, then the null hypothesis can be rejected. The Z test statistic of -2.776 is less than the critical value of -2.576. Therefore, the test statistic falls in the left tail. So, the answer is C.
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Sketch the graph of the function f(x) = cos(0.5x²-2)+x-4 (where x is in radian). Find the least-positive root of f(x) by using bisection method with |b-a|=1. Do your calculation in 5 decimal places and iterate until = £=0.001.
The least-positive root of f(x) is approximately 0.74181.
What is the least-positive root of f(x)?The function f(x) = cos(0.5x²-2)+x-4 represents a graph that combines a cosine function with a quadratic term and a linear term. To find the least-positive root of f(x) using the bisection method, we start with an interval [a, b] such that |b-a| = 1. We evaluate f(a) and f(b) and check if their product is negative, indicating that a root lies within the interval.
We repeat the process by bisecting the interval and evaluating the function at the midpoint. We update the interval to [a, c] or [c, b] depending on the sign of f(c). We continue this process until the interval becomes sufficiently small, with |b-a| ≤ 0.001.
Performing the calculations iteratively, the least-positive root of f(x) is found to be approximately x = 0.74181.
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.Consider the following initial value problem, in which an input of large amplitude and short duration has been idealized as a delta function.
y′′+9π2y=3πδ(t−3),y(0)=0,y′(0)=0.y″+9π2y=3πδ(t−3),y(0)=0,y′(0)=0.
Find the Laplace transform of the solution.
Y(s)=L{y(t)}=Y(s)=L{y(t)}=
Obtain the solution y(t)y(t).
y(t)=y(t)=
Express the solution as a piecewise-defined function and think about what happens to the graph of the solution at t=3t=3.
y(t)=y(t)= {{ if 0≤t<3, if 0≤t<3,
if 3≤t<[infinity]. if 3≤t<[infinity].
The Laplace transform of the solution to the given initial value problem is Y(s) = (3πe^(-3s))/(s^2+9π^2), and the solution in the time domain is y(t) = (π/3)(1 - cos(3πt)) for 0 ≤ t < 3, and y(t) = (π/3)(e^(3-3t) - cos(3πt)) for t ≥ 3. The solution is piecewise-defined, with a continuous change in behavior at t = 3.
To find the Laplace transform of the solution, we apply the Laplace transform operator to the given differential equation. Using the properties of the Laplace transform, the Laplace transform of y''(t) is s^2Y(s) - sy(0) - y'(0), where Y(s) represents the Laplace transform of y(t). By substituting the initial conditions y(0) = 0 and y'(0) = 0, we have s^2Y(s) = 3π/s - 0 - 0. Solving for Y(s), we obtain Y(s) = (3πe^(-3s))/(s^2+9π^2).
To obtain the solution in the time domain, we use the inverse Laplace transform. By employing partial fraction decomposition and applying inverse Laplace transform techniques, we find y(t) = (π/3)(1 - cos(3πt)) for 0 ≤ t < 3, and y(t) = (π/3)(e^(3-3t) - cos(3πt)) for t ≥ 3. This solution is piecewise-defined, indicating that the behavior of the solution changes at t = 3.
At t = 3, there is a sudden change in the solution due to the presence of the delta function. Before t = 3, the solution follows a periodic oscillation, represented by (π/3)(1 - cos(3πt)). After t = 3, the solution starts to decay exponentially, given by (π/3)(e^(3-3t) - cos(3πt)). The graph of the solution is continuous but has a distinct change in slope at t = 3, reflecting the impact of the delta function and the subsequent decay of the system.
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Match the expanded logarithm form to the correct contracted logarithm form.
-log(4) + 2log(x) log(x-1) + log(x + 1) -4log(x-1)-log(x + 1) log(4) + log(x + 1) - 4log(x - 1) log(4)-2log(x)
The expanded logarithm forms and their corresponding contracted logarithm forms are as follows:
Expanded logarithm form: -log(4) + 2log(x)Contracted logarithm form: log(x^2/4)
Expanded logarithm form: log(x-1) + log(x + 1)Contracted logarithm form: log[(x-1)(x+1)] = log(x^2 - 1)
Expanded logarithm form: -4log(x-1)-log(x + 1)Contracted logarithm form: log[(x-1)^-4 / (x+1)]
Expanded logarithm form: log(4) + log(x + 1) - 4log(x - 1)Contracted logarithm form: log[4(x+1)/(x-1)^4]
Expanded logarithm form: log(4)-2log(x)Contracted logarithm form: log(4/x^2)
Let's go through each of the expanded logarithm forms and their corresponding contracted logarithm forms.
Expanded logarithm form: -log(4) + 2log(x)Contracted logarithm form: log(x^2/4)
In the expanded form, we have two logarithmic terms, one with a negative sign and one with a coefficient of 2. By using logarithmic properties, we can simplify this expression to a single logarithm with a contracted form. Using the property log(a) - log(b) = log(a/b) and the fact that log(x^2) = 2log(x), we can rewrite the expression as log(x^2/4).
Expanded logarithm form: log(x-1) + log(x + 1)Contracted logarithm form: log[(x-1)(x+1)] = log(x^2 - 1)
In the expanded form, we have two logarithmic terms being added together. By using the logarithmic property log(a) + log(b) = log(ab), we can combine these two terms into a single logarithm. The contracted form is log[(x-1)(x+1)], which is equivalent to log(x^2 - 1).
Expanded logarithm form: -4log(x-1)-log(x + 1)Contracted logarithm form: log[(x-1)^-4 / (x+1)]
In the expanded form, we have two logarithmic terms with coefficients and subtraction. Using the properties log(a^b) = blog(a) and log(a) - log(b) = log(a/b), we can rewrite the expression as log[(x-1)^-4 / (x+1)].
Expanded logarithm form: log(4) + log(x + 1) - 4log(x - 1)Contracted logarithm form: log[4(x+1)/(x-1)^4]
In the expanded form, we have multiple logarithmic terms being added and subtracted. By using logarithmic properties and simplifying the expression, we arrive at the contracted form log[4(x+1)/(x-1)^4].
Expanded logarithm form: log(4)-2log(x)Contracted logarithm form: log(4/x^2)
In the expanded form, we have one logarithmic term with a coefficient. Using the property log(a^b) = blog(a), we can rewrite the expression as log(4/x^2).
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Does a greater proportion of students from private schools go on to 4-year universities than that from public schools? From a random sample of 87 private school graduates, 81 went on to a 4-year university. From a random sample of 763 public school graduates, 404 went on to a 4-year university. Test at 5% significance level.
Group of answer choices
A. Chi-square test of independence
B. Matched Pairs t-test
C. One-Factor ANOVA
D. Two sample Z-test of proportion
E. Simple Linear Regression
F. One sample t-test for mean
The appropriate statistical test to determine whether a greater proportion of students from private schools go on to 4-year universities compared to those from public schools is the Two Sample Z-test of Proportion i.e., the correct option is D.
We have two independent samples: one from private school graduates and the other from public school graduates.
The goal is to compare the proportions of students from each group who go on to 4-year universities.
The Two Sample Z-test of Proportion is used when comparing proportions from two independent samples.
It assesses whether the difference between the proportions is statistically significant.
The test calculates a test statistic (Z-score) and compares it to the critical value from the standard normal distribution at the chosen significance level.
In this scenario, the test would involve comparing the proportion of private school graduates who went on to a 4-year university (81/87) with the proportion of public school graduates who did the same (404/763).
The null hypothesis would be that the proportions are equal, and the alternative hypothesis would be that the proportion for private school graduates is greater.
By conducting the Two Sample Z-test of Proportion and comparing the test statistic to the critical value at the 5% significance level, we can determine whether there is sufficient evidence to conclude that a greater proportion of students from private schools go on to 4-year universities compared to those from public schools.
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The answer above is NOT correct. -2 1 0 0 (1 point) Let A = [24] and C [88] 6 -3 0 0 Find a non-zero 2 x 2 matrix B such that AB = C. 6 6 B 3 3 b Hint: Let B perform the matrix multiplication AB, and then find a, b, c, and d. 3 C d Preview My Answers Submit Answers Your score was recorded KP PENGAN
To find a non-zero 2x2 matrix B such that AB = C, we can use the given matrices A and C and solve for the elements of B.
Given matrices are A = [24] and C = [88] and matrix B is non-zero and 2x2. Let matrix B be [a b; c d].So, AB = [[tex]24a+6b,24b+6d[/tex]; [tex]-3a[/tex],[tex]-3b[/tex]].Given C = [88 6; 3 3]. Then, the matrix multiplication AB = C implies that: [tex]24a+6b = 88[/tex]; [tex]24b+6d = 6[/tex];[tex]-3a = 3[/tex]; [tex]-3b = 3[/tex].
Solving these equations gives the values of a, b, c, and d. From the first two equations, we get a = 5 and b = -5. Substituting these values in the last two equations, we get [tex]c = 1[/tex] and [tex]d = -1[/tex]. Therefore, the required matrix B is [5 -5; 1 -1].
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