Answer:
This is false as you can have triangular sequences.
loftus (1974) gave subjects a description of an armed robbery. eighteen percent presented with only circumstantial evidence convicted the defendant. when an eyewitness' identification was provided in addition to the circumstantial evidence, 72% convicted the defendant. what happened when mock jurors were told that the eyewitness had poor eyesight and wasn't wearing his glasses?
The jurors may perceive the identification as less reliable, leading them to rely more on the circumstantial evidence and be less certain about convicting the defendant.
In Loftus' (1974) study on the effects of eyewitness testimony on jury decision-making, subjects were presented with a description of an armed robbery. When only circumstantial evidence was provided, 18% of the subjects convicted the defendant. However, when an eyewitness identification was added to the circumstantial evidence, the conviction rate increased to 72%.
When the mock jurors were told that the eyewitness had poor eyesight and wasn't wearing his glasses, it is likely that the conviction rate would decrease as this information weakens the credibility of the eyewitness testimony. The jurors may perceive the identification as less reliable, leading them to rely more on the circumstantial evidence and be less certain about convicting the defendant.
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A. B. C. D. pretty please help me. Also you get 100 points
Answer:
C
Step-by-step explanation:
7 + 45/5 = 16
Bisecting Bakery sells cylindrical round cakes. The most popular cake at the bakery is the red velvet cake. It has a radius of 15 centimeters and a height of 12 centimeters.
If everything but the circular bottom of the cake was iced, how many square centimeters of icing is needed for one cake? Use 3.14 for π and round to the nearest square centimeter.
810 cm2
585 cm2
2,543 cm2
1,837 cm2
Assuming that n,n2, find the sample sizes needed to estimate (P1-P2) for each of the following situations a.A margin of error equal to 0.11 with 99% confidence. Assume that p1 ~ 0.6 and p2 ~ 0.4. b.A 90% confidence interval of width 0.88. Assume that there is no prior information available to obtain approximate values of pl and p2 c.A margin of error equal to 0.08 with 90% confidence. Assume that p1 0.19 and p2 0.3. P2- a. What is the sample size needed under these conditions? (Round up to the nearest integer.)
The following parts can be answered by the concept from Standard deviation.
a. We need a sample size of at least 121 for each group.
b. We need a sample size of at least 78 for each group.
c. We need a sample size of at least 97.48 for each group.
To find the sample size needed to estimate (P1-P2) for each of the given situations, we can use the following formula:
n = (Zα/2)² × (p1 × q1 + p2 × q2) / (P1 - P2)²
where:
- Zα/2 is the critical value of the standard normal distribution at the desired confidence level
- p1 and p2 are the estimated proportions in the two populations
- q1 and q2 are the complements of p1 and p2, respectively (i.e., q1 = 1 - p1 and q2 = 1 - p2)
- (P1 - P2) is the desired margin of error
a. For a margin of error equal to 0.11 with 99% confidence, assuming p1 ~ 0.6 and p2 ~ 0.4, we have:
Zα/2 = 2.576 (from standard normal distribution table)
p1 = 0.6, q1 = 0.4
p2 = 0.4, q2 = 0.6
(P1 - P2) = 0.11
Plugging in the values, we get:
n = (2.576)² × (0.6 × 0.4 + 0.4 × 0.6) / (0.11)²
n ≈ 120.34
Therefore, we need a sample size of at least 121 for each group.
b. For a 90% confidence interval of width 0.88, assuming no prior information is available to obtain approximate values of p1 and p2, we have:
Zα/2 = 1.645 (from standard normal distribution table)
(P1 - P2) = 0.88
Since we have no information about p1 and p2, we can assume them to be 0.5 each (which maximizes the sample size and ensures a conservative estimate).
Plugging in the values, we get:
n = (1.645)² × (0.5 × 0.5 + 0.5 × 0.5) / (0.88)²
n ≈ 77.58
Therefore, we need a sample size of at least 78 for each group.
c. For a margin of error equal to 0.08 with 90% confidence, assuming p1 = 0.19 and p2 = 0.3, we have:
Zα/2 = 1.645 (from standard normal distribution table)
q1 = 0.81
q2 = 0.7
(P1 - P2) = 0.08
Plugging in the values, we get:
n = (1.645)² × (0.19 × 0.81 + 0.3 × 0.7) / (0.08)²
n ≈ 97.48
Therefore, we need a sample size of at least 98 for group 1. For group 2, we can use the same sample size as group 1, or we can adjust it based on the expected difference between p1 and p2 (which is not given in this case).
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The following parts can be answered by the concept from Standard deviation.
a. We need a sample size of at least 121 for each group.
b. We need a sample size of at least 78 for each group.
c. We need a sample size of at least 97.48 for each group.
To find the sample size needed to estimate (P1-P2) for each of the given situations, we can use the following formula:
n = (Zα/2)² × (p1 × q1 + p2 × q2) / (P1 - P2)²
where:
- Zα/2 is the critical value of the standard normal distribution at the desired confidence level
- p1 and p2 are the estimated proportions in the two populations
- q1 and q2 are the complements of p1 and p2, respectively (i.e., q1 = 1 - p1 and q2 = 1 - p2)
- (P1 - P2) is the desired margin of error
a. For a margin of error equal to 0.11 with 99% confidence, assuming p1 ~ 0.6 and p2 ~ 0.4, we have:
Zα/2 = 2.576 (from standard normal distribution table)
p1 = 0.6, q1 = 0.4
p2 = 0.4, q2 = 0.6
(P1 - P2) = 0.11
Plugging in the values, we get:
n = (2.576)² × (0.6 × 0.4 + 0.4 × 0.6) / (0.11)²
n ≈ 120.34
Therefore, we need a sample size of at least 121 for each group.
b. For a 90% confidence interval of width 0.88, assuming no prior information is available to obtain approximate values of p1 and p2, we have:
Zα/2 = 1.645 (from standard normal distribution table)
(P1 - P2) = 0.88
Since we have no information about p1 and p2, we can assume them to be 0.5 each (which maximizes the sample size and ensures a conservative estimate).
Plugging in the values, we get:
n = (1.645)² × (0.5 × 0.5 + 0.5 × 0.5) / (0.88)²
n ≈ 77.58
Therefore, we need a sample size of at least 78 for each group.
c. For a margin of error equal to 0.08 with 90% confidence, assuming p1 = 0.19 and p2 = 0.3, we have:
Zα/2 = 1.645 (from standard normal distribution table)
q1 = 0.81
q2 = 0.7
(P1 - P2) = 0.08
Plugging in the values, we get:
n = (1.645)² × (0.19 × 0.81 + 0.3 × 0.7) / (0.08)²
n ≈ 97.48
Therefore, we need a sample size of at least 98 for group 1. For group 2, we can use the same sample size as group 1, or we can adjust it based on the expected difference between p1 and p2 (which is not given in this case).
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consider the parametric curve given by the equations x(t)=t2 13t−40 y(t)=t2 13t 1 how many units of distance are covered by the point p(t)=(x(t),y(t)) between t=0 and t=7 ?
Using a numerical integration method or a calculator, the value of the integral can be found to be approximately 62.7 units. So, point P(t) covers about 62.7 units of the distance between t = 0 and t = 7.
To find the distance covered by the point P(t) = (x(t), y(t)) between t = 0 and t = 7, we need to calculate the arc length of the parametric curve given by the equations x(t) = t^2 + 13t - 40 and y(t) = t^2 + 13t + 1.
Step 1: Find the derivatives of x(t) and y(t) with respect to t.
dx/dt = 2t + 13
dy/dt = 2t + 13
Step 2: Compute the square of the derivatives and add them together.
(dx/dt)^2 + (dy/dt)^2 = (2t + 13)^2 + (2t + 13)^2 = 2 * (2t + 13)^2
Step 3: Take the square root of the result obtained in step 2.
sqrt(2 * (2t + 13)^2)
Step 4: Integrate the result from step 3 with respect to t from 0 to 7.
Arc length = ∫[0,7] sqrt(2 * (2t + 13)^2) dt
Using a numerical integration method or a calculator, the value of the integral can be found to be approximately 62.7 units. So, the point P(t) covers about 62.7 units of distance between t = 0 and t = 7.
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The rear tire on a tractor has a radius of 8 feet. What is the area, in square feet, of the tire rounded to the nearest tenth?
The area of the rear tire of the tractor is A = 201.1 feet²
Given data ,
The area of a circle is given by the formula A = πr², where r is the radius of the circle.
Given that the radius of the tractor tire is 8 feet, we can substitute this value into the formula to calculate the area:
A = π(8²)
Using the value of π as approximately 3.14159265359
A ≈ 3.14159265359 x (8²)
A = 3.14159265359 x 64
A ≈ 201.061929829746
Rounding to the nearest tenth, we get:
A ≈ 201.1 feet²
Hence , the area of the tractor tire is approximately 201.1 feet²
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The volume of a rectangular prism is given as 6x^(3)+96x^(2)+360x cubic inches. What is one possible expression for the height of the prism?
Answer:
6x(x+6)(x+10)
Step-by-step explanation:
6x^(3)+96x^(2)+360x
x6(x^2+16x+60)
6x(x+6((x+10)
for a second-order homogeneous linear ode, an initial value problem consists of an equation and two initial conditions. True False
The given statement "For a second-order homogeneous linear ordinary differential equation (ODE), an initial value problem (IVP) consists of an equation and two initial conditions" is True because A second-order homogeneous linear ODE is an equation of the form ay''(t) + by'(t) + cy(t) = 0, where y(t) is the dependent variable, t is the independent variable, and a, b, and c are constants.
The equation is homogeneous because the right-hand side is zero, and it is linear because y(t), y'(t), and y''(t) are not multiplied or divided by each other or their higher powers. An IVP for this type of equation requires two initial conditions because the second-order ODE has two linearly independent solutions.
These initial conditions are typically given in the form y(t0) = y0 and y'(t0) = y1, where t0 is the initial time, and y0 and y1 are the initial values of y(t) and y'(t), respectively.
The two initial conditions are necessary to determine a unique solution to the second-order ODE. Without them, there would be an infinite number of possible solutions. By providing the initial conditions, you establish constraints on the solutions, which allow for a unique solution that satisfies both the ODE and the initial conditions.
In summary, an IVP for a second-order homogeneous linear ODE consists of an equation and two initial conditions, ensuring a unique solution to the problem.
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How can we express (logₓy)², or log of y to the base x the whole squared? Is it the same as log²ₓy?
The equivalent expression of the logarithmic expression (logₓy)² is log²ₓy
Rewriting the logarithmic expressionFrom the question, we have the following parameters that can be used in our computation:
(logₓy)²
The above expression is pronounced
log y to the base of x all squared
When the expression is expanded, we have the following
(logₓy)² = (logₓy) * (logₓy)
Evaluating the expression, we have
(logₓy)² = log²ₓy
Hence, the equivalent expression of the expression (logₓy)² is log²ₓy
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The taylor series for f(x) = cos(x) centered at x = 0 is cos(x) = Sigma^infinity_k=0 (-1)^k 1/(2k)! X^2k = 1 - 1/2! x^2 + 1/4! X^4 -1/6! X^6 + ... Substitute t^3 for x to construct a power series expansion for cos (t^3). For full credit, your answer should use sigma notation. Integrate term-by-term your answer in part (a) to construct a power series expansion for integral cos(t^3) dt. Your final answer should include + C since this integral is indefinite. For full credit, your answer should use sigma notation.
The power series expansion for ∫cos(t^3) dt is:
∫cos(t^3) dt = Σ^∞_k=0 (-1)^k (1/(2k)!(6k+1)) t^(6k+1) + C
To construct a power series expansion for cos(t^3), we will substitute t^3 for x in the Taylor series of cos(x) centered at x = 0:
cos(t^3) = Σ^∞_k=0 (-1)^k 1/(2k)! (t^3)^(2k)
= Σ^∞_k=0 (-1)^k 1/(2k)! t^(6k)
Now, we will integrate term-by-term to find a power series expansion for ∫cos(t^3) dt:
∫cos(t^3) dt = ∫(Σ^∞_k=0 (-1)^k 1/(2k)! t^(6k)) dt
= Σ^∞_k=0 (-1)^k ∫(1/(2k)! t^(6k)) dt
Integrating term-by-term:
= Σ^∞_k=0 (-1)^k (1/(2k)!(6k+1)) t^(6k+1) + C
So, the power series expansion for ∫cos(t^3) dt is:
∫cos(t^3) dt = Σ^∞_k=0 (-1)^k (1/(2k)!(6k+1)) t^(6k+1) + C
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When finding a confidence interval for a population mean based on a sample of size 8, which assumption is made? O A The sampling distribution of z is normal. O B There is no special assumption made. O C The population standard deviation, σ is known. O D The sampled population is approximately normal
When finding a confidence interval for a population mean based on a sample of size 8, the assumption made is that the sampled population is approximately normal.
When finding a confidence interval for a population mean based on a sample of size 8, the assumption made is that the sampled population is approximately normal. This assumption is crucial because it ensures that the sampling distribution of the sample mean is normal or nearly normal, allowing for accurate confidence interval calculations.
This assumption allows us to use the central limit theorem, which states that the distribution of sample means will approach a normal distribution as the sample size increases. This in turn allows us to use a t-distribution to calculate the confidence interval.
Option A is incorrect because the sampling distribution of z is used when the population standard deviation is known, which is not the case in this scenario. Option B is also incorrect because assumptions are made in statistical inference. Option C is incorrect because it assumes that the population standard deviation is known, which is not always the case.
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find the area of the figure below
The area of the figure in this problem is given as follows:
140 yd².
How to obtain the area of the figure?The figure in the context of this problem is a composite figure, hence the area is the sum of the areas of all the parts that compose the figure.
The figure in this problem is composed as follows:
Square of side length 10 yd.Right triangle of dimensions 8 yd and 10 yd.The area of each part of the figure is given as follows:
Square: 10² = 100 yd².Right triangle: 0.5 x 8 x 10 = 40 yd².Hence the total area of the figure is given as follows:
100 + 40 = 140 yd².
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A new car is purchased for 16600 dollars. The value of the car depreciates at 9.75% per year. What will the value of the car be, to the nearest cent, after 8 years?
please show work
Answer:
7306.1
Step-by-step explanation:
The value of the car is $7306.10 after 8 years.
Given
A new car is purchased for 16600 dollars.
The value of the car depreciates at 9.75% per year.
What is depreciation?
Depreciation denotes an accounting method to decrease the cost of an asset.
To get the depreciation of a partial year, you need to calculate the depreciation a full year first.
The formula to calculate depreciation is given by;
V= P( 1-r )^t
Where V represents the depreciation r is the rate of interest and t is the time.
Hence, the value of the car is $7306.10 after 8 years.
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A blueprint for a cottage has a scale of 1:40 one room measures 3.4 m by 4.8 . calculate the dimensions of the room on the blueprint.
I need students to solve it, with operations
The actual dimension of the room on the blueprint is 136 meters by 192 meters
From the question, we have the following parameters that can be used in our computation:
Scale ratio = 1 : 40
This means that the ratio of the scale to the actual is 1:40
Also, from the question. we have
One room measures 3.4 m by 4.8 .
This means that
Actual length = 40 * 3.4 meters
Actual width = 40 * 4.8 meters
Using the above as a guide, we have the following:
We need to evaluate the products to determine the actual dimensions
So, we have
Actual length = 136 meters
Actual width = 192 meters
Hence, the actual dimension is 136 meters by 192 meters
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PLEASE HELP!!!
The side lengths and areas of some regular polygons are shown in the table below which expressions can be used to find the area in square units of a similar polygon with a side length of N units?
n^2
all the numbers on the right are squares of the numbers on the left
squares means the number times the same number
Answer:
Number 2, [tex]n^{2}[/tex]
Step-by-step explanation:
The table shows at the top of the screen has a very specific pattern, when comparing side length and area.
When the side length is 4 the area is 16
When the side length is 5 the area is 25
What is happening?
They are being squared(Multipled by itself).
See here:
4*4 = 16
5*5 = 25
Understand how the table is working?
The table is a side to area comparision of a polygon.
The question asks to find the area of a similar polygon, if a side length is n.
Because we are squaring the side length, the answer is:
[tex]n^{2}[/tex]
12. Find the rate of change for the linear function represented in the table.
Time (hr) Cost ($)
x y
1 55.00
1.5 73.50
2 92.00
2.5 110.50
A student uses Square G and Square F, shown below, in an attempt to prove the Pythagorean theorem. Square G and Square F both have side lengths equal to (a + b).
The student's work is shown in the photo attached.
What error did the student make?
A. In Step 1, the areas of the squares are different because the squares are partitioned into different shapes.
B. In Step 2, the area of Square G should be equal to a? + 2ab + b2 because there are 2 rectangles with sides lengths a and b.
C. In Step 3, the area of Square F should be equal to a? + ab + b? because there are 2 right triangles with sides lengths a and b.
D. In Step 5, ab should be subtracted from the left side of the equation and 2ab should be subtracted from the right side.
Answer:
the answer is b
Step-by-step explanation:
Due to the presence of two rectangles with sides of lengths a and b, Square G's area in Step 2 should equal [tex]a^2+2ab+b^2[/tex].
What is Pythagorean theorem?According to the Pythagorean Theorem, the squares on the hypotenuse of a right triangle, or, in conventional algebraic notation, [tex]a^2+b^2[/tex], are equal to the squares on the legs. The Pythagorean Theorem states that the square on a right-angled triangle's hypotenuse is equal to the total number of the squares on its other two sides.
The Pythagoras theorem, often known as the Pythagorean theorem, explains the relationship between each of the sides of a shape with a right angle. According to the Pythagorean theorem, the square root of a triangle's the hypotenuse is equal to the sum of the squares of its other two sides.
Area of square [tex]G=a^2+2ab+b^2[/tex]
[tex]a^2+2ab+b^2=c^2+2ab\\\\a^2+2ab-2ab+b^2=c^2+2ab-2ab\\\\a^2+b^2=c^2[/tex]
[ The Pythagorean theorem]
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determine whether the geometric series is convergent or divergent. (4 − 7 49 4 − 343 16 )
The common ratio 'r' is not constant, meaning that the series is not geometric.
Define the term geometric series?Each term in a geometric series is created by multiplying the previous term by a fixed constant known as the common ratio.
To determine if the geometric series (4, -7, 49, -343, 16) is convergent or divergent, we need to find the common ratio 'r' of the series.
r = (next term) / (current term)
r = (-7) / 4 = -1.75
r = 49 / (-7) = -7
r = (-343) / 49 = -7
r = 16 / (-343) = -0.0466...
We can see that the common ratio 'r' is not constant, meaning that the series is not geometric, and therefore we cannot determine if it is convergent or divergent.
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45.1 devided by 1,000
Points p q and r lie on the circumference of a circle centre o angle pqr is 29 work out the size of the reflex angle por
The size of the reflex angle POR is 302 degrees.
Since the angle PQR is given as 29 degrees and it lies on the circumference of the circle, we know that it is an inscribed angle that intercepts the arc PR. The measure of an inscribed angle is half the measure of the intercepted arc. Therefore, we can find the measure of the arc PR as:
Arc PR = 2 × Angle PQR = 2 × 29 = 58 degrees
Since angle POR is a reflex angle that contains the inscribed angle PQR and the arc PR, we can find its measure by subtracting the measure of angle PQR from 360 degrees:
Angle POR = 360 - Arc PR = 360 - 58 = 302 degrees
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The sum of two integers is -1500 one of the number is 599. Find the other numbers.
Answer:
∴ The other integer is -2099.
Step-by-step explanation:
Let the unknown number be x,
599+x=(-1500)
x=(-1500)-599
x=(-2099)
Determine your Type I error about the 1968 minimum wage, if your null hypothesis, H0, is p≤$10.86.Select the correct answer below:You think the 1968 minimum wage was at most $10.86 when, in fact, it was.You think the 1968 minimum wage was at most $10.86 when, in fact, it was not.You think the 1968 minimum wage was not at most $10.86 when, in fact, it was.You think the 1968 minimum wage was not at most $10.86 when, in fact, it was not.
The correct answer to the question is "You think the 1968 minimum wage was at most $10.86 when, in fact, it was not."
Explanation: -
In statistical hypothesis testing, a Type I error is the rejection of a null hypothesis when it is actually true.
In this scenario, the null hypothesis is that the 1968 minimum wage is p≤$10.86. If a researcher thinks that the 1968 minimum wage was at most $10.86, but in reality, it was not, this would be a Type I error. In other words, the researcher rejected the null hypothesis (that the minimum wage was $10.86 or less) when it was actually true.
To determine the probability of making a Type I error, we use the significance level, denoted by α. The significance level is the probability of rejecting the null hypothesis when it is actually true. If we set α=0.05, this means that there is a 5% chance of making a Type I error. So, if we reject the null hypothesis that the 1968 minimum wage is $10.86 or less, when in fact, it is true, we are making a Type I error with a probability of 0.05 or 5%.
Therefore, the correct answer to the question is "You think the 1968 minimum wage was at most $10.86 when, in fact, it was not."
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In a random sample of 80 bicycle wheels, 37 were found to have critical flaws that would result in damage being done to the bicycle. Determine the lower bound of a two-sided 95% confidence interval for p, the population proportion of bicycle wheels that contain critical flaws. Round your answer to four decimal places.
The Confidence interval for the population proportion p is approximately 0.4832
How to determine the lower bound of a confidence interval for the population proportion?To determine the lower bound of a two-sided 95% confidence interval for the population proportion p, we can use the formula for the confidence interval of a proportion.
The formula for the confidence interval of a proportion is given by:
CI = p ± zsqrt((p(1-p))/n)
where:
CI = confidence interval
p = sample proportion
z = z-score corresponding to the desired confidence level
n = sample size
Given:
Sample proportion (p) = 37/80 = 0.4625 (since 37 out of 80 bicycle wheels were found to have critical flaws)
Sample size (n) = 80
Desired confidence level = 95%
We need to find the z-score corresponding to a 95% confidence level. For a two-sided confidence interval, we divide the desired confidence level by 2 and find the z-score corresponding to that area in the standard normal distribution table.
For a 95% confidence level, the area in each tail is (1 - 0.95)/2 = 0.025. Using a standard normal distribution table or a z-score calculator, we can find that the z-score corresponding to an area of 0.025 is approximately -1.96.
Now we can plug in the values into the formula and solve for the lower bound of the confidence interval:
CI = 0.4625 ± (-1.96)sqrt((0.4625(1-0.4625))/80)
Calculating the expression inside the square root first:
(0.4625*(1-0.4625)) = 0.2497215625
Taking the square root of that:
sqrt(0.2497215625) ≈ 0.4997215107
Substituting back into the formula:
CI = 0.4625 ± (-1.96)*0.4997215107
Now we can calculate the lower bound of the confidence interval:
Lower bound = 0.4625 - (-1.96)*0.4997215107 ≈ 0.4625 + 0.979347415 ≈ 1.4418 (rounded to four decimal places)
Therefore, the lower bound of the two-sided 95% confidence interval for the population proportion p is approximately 0.4418 (rounded to four decimal places).
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could either approach still function with a load factor greater than 1?
It is generally recommended to keep the load factor below 0.75 for hash tables using either linear probing or chaining.
Explain the answer more in detail below?No, neither linear probing nor chaining can function properly with a load factor greater than 1.
When the load factor exceeds 1, it means that the number of items in the hash table exceeds the number of available buckets, and collisions become unavoidable.
In linear probing, this results in an endless loop of searching for an empty bucket, making it impossible to insert new items or retrieve existing ones.
In chaining, a high load factor can cause the chains to become very long, slowing down retrieval operations significantly.
In extreme cases, the chains can become so long that the hash table degenerates into a linked list, rendering the hash table useless.
Therefore, it is generally recommended to keep the load factor below 0.75 for hash tables using either linear probing or chaining.
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we were told the results are based on a random sample of ann arbor teens. is the following statement about the remaining assumption correct or not correct?we need to have a simple size n that is large enough, namely that the sample size n is at least 25.O CorrectO Incorrect
Correct. The assumption that the sample size should be at least 25 is correct. This is because, for a sample to be representative of the population, it should have enough observations to provide a reasonable estimate of the population parameters.
A sample size of at least 25 is generally considered the minimum requirement for statistical analysis. The statement about the remaining assumption is correct. In order to make valid inferences from a random sample, it is important to have a large enough sample size (n). A common rule of thumb is that the sample size should be at least 25. This helps to ensure that the sample is representative of the population and increases the accuracy of the results.
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(1 point) let b be the basis of r2 consisting of the vectors {[42],[−15]}, and let c be the basis consisting of {[−23],[1−2]}. find the change of coordinates matrix p from the basis b to the basis c.
The change of coordinates matrix P from the basis B to the basis C is given by P = [[-23/42, -15/42], [-46/42, 30/42]], which simplifies to P = [[-23/42, -5/14], [-23/21, 5/7]].
To find the change of coordinates matrix P from basis B to basis C, follow these steps:
1. Write the basis vectors of B and C as column vectors: B = [[42], [-15]] and C = [[-23], [1-2]].
2. Find the inverse of the matrix formed by basis B, B_inv = (1/determinant(B)) * adjugate(B). The determinant of B is -630, so B_inv = (1/-630) * [[-15, 15], [-42, 42]] = [[15/630, -15/630], [42/630, -42/630]] = [[1/42, -1/42], [2/30, -2/30]].
3. Multiply the matrix B_inv with matrix C to obtain the change of coordinates matrix P: P = B_inv * C = [[1/42, -1/42], [2/30, -2/30]] * [[-23], [1-2]] = [[-23/42, -15/42], [-46/42, 30/42]] = [[-23/42, -5/14], [-23/21, 5/7]].
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(1 point) consider the basis b of r2 consisting of vectors [−4−5] and [12]. find x⃗ in r2 whose coordinate vector relative to the basis b is [x⃗ ]b=[2−4].
X in r2 whose coordinate vector relative to the basis b is [1/5 2/15].
To find x⃗ in r2 whose coordinate vector relative to the basis b is [2 -4], we first need to express the basis vectors as a matrix.
The matrix for the basis b is:
[ -4 12
-5 0 ]
To find x⃗, we can use the formula:
x⃗ = [x⃗ ]b * [B]^-1
where [B]^-1 is the inverse of the matrix for the basis b.
To find the inverse of the matrix for the basis b, we can use the formula:
[B]^-1 = (1/60) * [0 12
5 -4 ]
Plugging in the values, we get:
x⃗ = [2 -4] * (1/60) * [0 12
5 -4 ]
= (1/60) * [(-8)+(20) (24)+(-16)]
= (1/60) * [12 8]
= [1/5 2/15]
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let be a random variable with f(x)=kx^4 pdf find e(x) .
The expected value of X is then calculated as E(X) = ∫x f(x) dx from 0 to 1, which simplifies to E(X) = k∫x⁵ dx from 0 to 1. Evaluating this integral gives us the expected value of X, which is equal to 5/6.
The expected value of the random variable X with a probability density function (pdf) of f(x) = kx⁴ is calculated as E(X) = ∫x f(x) dx from negative infinity to positive infinity.
Integrating f(x) from negative infinity to positive infinity gives us the normalizing constant k, which is equal to 1/∫x⁴ dx from 0 to 1. Simplifying this gives us k = 5.
The expected value of X is then calculated as E(X) = ∫x f(x) dx from 0 to 1, which simplifies to E(X) = k∫x⁵ dx from 0 to 1. Evaluating this integral gives us E(X) = k/6, which is equal to 5/6. Therefore, the expected value of X with f(x) = kx⁴ pdf is 5/6.
In summary, the expected value of a random variable X with a probability density function (pdf) of f(x) = kx⁴ is calculated by integrating x f(x) from negative infinity to positive infinity. Integrating f(x) from negative infinity to positive infinity gives us the normalizing constant k, which is equal to 1/∫x⁴ dx from 0 to 1.
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Which graph represents the function f(x) = -3 -2?
The fourth graph represents the functions f(x)=-3ˣ-2
We can plug in the y intercept to find which graph has the correct one.
x = 0 is y intercept
Thus function f(0)=-3⁰-2
f(0)=-1-2
f(0)=-3
At this point we known the y intercept is -3 so both graph in the left is considerable.
Notice that the base is the negative, thus the graph would goes down. Therefore the bottom right would be correct.
Hence, the fourth graph represents the functions f(x)=-3ˣ-2
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Pleaseee help
Lisa has collected data to find that the number of pages per book on a book shelf has a normal distribution. What is the probability that a randomly selected book has fewer than 170 pages if the mean (k) is 195 pages and the standard deviation (o) is 25 pages? Use the empirical rule. Enter your answer as a percent rounded to two decimal places if necessary.
Answer:
Approximately 16%
Step-by-step explanation:
To solve this problem using the empirical rule, we need to first standardize the value of 170 pages using the mean and standard deviation provided:
z = (x - k) / o
where x is the value we want to find the probability for (170 pages), k is the mean (195 pages), and o is the standard deviation (25 pages).
So,
z = (170 - 195) / 25 = -1
Now, we can use the empirical rule, which states that for a normal distribution:
- About 68% of the data falls within 1 standard deviation of the mean
- About 95% of the data falls within 2 standard deviations of the mean
- About 99.7% of the data falls within 3 standard deviations of the mean
Since we know that the distribution is normal, and we want to find the probability that a randomly selected book has fewer than 170 pages (which is one standard deviation below the mean), we can use the empirical rule to estimate this probability as follows:
- From the empirical rule, we know that about 68% of the data falls within 1 standard deviation of the mean.
- Since the value of 170 pages is one standard deviation below the mean, we can estimate that the probability of randomly selecting a book with fewer than 170 pages is approximately 16% (which is half of the remaining 32% outside of one standard deviation below the mean).
Therefore, the probability that a randomly selected book has fewer than 170 pages is approximately 16%.