help ASAP Ill give you brainliest

The calculated value of the margin of error is 0.022

From the question, we have the following parameters that can be used in our computation:

Sample, n = 1400

The proportion is calculated as

p = 320/1400

So, we have

p = 0.2286

Next, we calculate the standard error using

E = √[(p * (1 - p)) / n]

So, we have

E = √[(0.2286 * (1 - 0.2286)) / 1400]

Evaluate

E = 0.0112

The margin of error is then calculated using

Margin of Error = z  * E

Using z at 95% CI, we have

M = 1.96 * 0.0112

Evaluate

M = 0.022

Hence, the margin of error is 0.022

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Answer:

FV= 676

Step-by-step explanation:

Giving the following formula:

Present value (PV)= 990 parents

Decrease rate (d)= 10% = 0.1 per year

Number of periods (n)= 4

To calculate the future value of votes, we need to use the following formula:

FV= PV / (1 + d)^n

FV= 990 / (1.1^4)

FV= 676

Answer:

$535

Step-by-step explanation:

First step is figure out what's 7% of 500, and then you can add the numbers together. To make it simpler, you can multiple 500 by 1.07, which would include the sales tax and the 500 altogether to get the answer.

Answer:

1 /1 ; 360°

Step-by-step explanation:

Start time = 2:30 pm

Stop time = 3:30 pm

Minute hand makes a complete revolution per hour ;

This means that the minutes hand revolves round the whole circle in one hour, hence fraction of the circle covered by the minute hand between 2:30 pm - 3:30 pm is 1/1 = 1

The angle turned by the minutes hand :

1 complete revolution = 360°

A circle covers 360°

1 /1 fraction of a circle = 1/1 * 360° = 360°

Hence, angle turned by the minute hand = 360°

Answer:

7: 15

Step-by-step explanation:

a) If Kristin has traveled 4 meters along the path of the Ferris wheel then the angle has swept out 0.5 radians.

b) If Kristin has traveled 45 meters along the path of the Ferris wheel then the angle has swept out 5.625 radians.

c) The formula that expresses the number of radians θ the angle has swept out in terms of the number of meters is θ = s / r.

a. To determine the angle in radians, we can use the arc length formula for a circle. The formula is given by θ = s / r, where θ is the angle in radians, s is the arc length, and r is the radius of the circle.

In this case, Kristin has traveled 4 meters along the path of the Ferris wheel, and the radius is 8 meters.

Thus, the angle swept out is

θ = 4 / 8 = 0.5 radians.

b. Following the same approach, if Kristin has traveled 45 meters along the path of the Ferris wheel, the angle swept out is

θ = 45 / 8 ≈ 5.625 radians.

c. The formula that expresses the number of radians θ the angle has swept out in terms of the number of meters Kristin has traveled since the ride started is given by

θ = s / r,

where θ is the angle in radians, s is the arc length traveled by Kristin, and r is the radius of the Ferris wheel.

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The return period of a hazardous wind can be calculated by finding the inverse of its cumulative distribution function (CDF) at a certain threshold value.

a) To determine the return period of a hazardous wind, we need to find the threshold wind speed that corresponds to a specific return period. Since the wind speed follows a lognormal distribution with a known median and coefficient of variation, we can calculate the corresponding quantile using the inverse of the lognormal CDF.

b) The probability of more than 3 hazardous events in the total happening within a year can be calculated using the Poisson distribution. We sum the probabilities of having 4, 5, 6, and so on hazardous events in a year.

c) The probability of no hazardous events happening within 5 years can also be calculated using the Poisson distribution. We calculate the probability of zero hazardous events in one year and then raise it to the power of 5.

d) To estimate the mean and standard deviation of expected annual monetary losses, we multiply the mean number of hazardous events for each type by the cost per event. Since the three hazardous events occur independently, we can sum the expected losses for each type.

The standard deviation of the expected losses can be calculated using the properties of independent random variables. By calculating the mean and standard deviation of expected annual monetary losses, the municipality can have an idea of the budget allocation required to mitigate the impact of natural hazards in Izmir.

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Answer:

c) 33

Step-by-step explanation:

We can calculate supplementary angles by subtracting the given angle from 180°. To find the other angle (in your case, ∠e), use the ∠y = 180° – ∠x where ∠x is the given angle.

Answer:

c)33

Step-by-step explanation:

Using the z-distribution, as we have the population standard deviation, it is found that a sample of 83 people must be taken.

Given,

Estimation of number of minutes per day a person spends on the internet .

Margin of error in Z distribution,

M = z σ/[tex]\sqrt{n}[/tex]

In which:

z is the critical value.

σ is the population standard deviation.

n is the sample size.

Here,

We have 90% confidence level ,

Thus ,

[tex]\alpha[/tex] = 0.9

z is the value of Z that has a p-value

(1+0.9) / 2

= 0.95

so the critical value is z = 2.575

Also we have

standard deviation = 46 minutes

Population mean = 13 minutes

To find minimum sample size solve for n

M = z σ/[tex]\sqrt{n}[/tex]

13 = 2.575 (46/[tex]\sqrt{n}[/tex])

n = 83 .30

Rounding up, a sample of 83 people must be taken.

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Answer:

C

Step-by-step explanation:

Answer:

F= 1 /4 y+ 9 /4

Step-by-step explanation:

brainliest?

Answer:

divide 7/100 which is 0.07

multiply that by 13.75, and you get 0.96

13.75+0.96= $13.20

(this is including sales tax)

Answer:

$12.78

Step-by-step explanation:

I THINK you are supposed to multiply the original price (13.75) by the sales tax as a decimal (0.07) and then subtract that answer from, the original, amount.

Answer: $8 bowl, noodles, bean sprouts, beef

Step-by-step explanation:

Answer:

A) 36 inches

36 Incheon is the correct answer

Answer:

D.) 64pi in.³

Step-by-step explanation:

I got it right in quiz, trust me.

I hope this helps! ^^

The preparation workshop’s impact on first-time composite scores can be assessed by evaluating the scores of a group of 30 high school seniors who retake the Miller Analogies Test (MAT) after attending the workshop.

The MAT is taken twice by each student: once before the workshop and once after it. The scores are reported on a ratio scale.
To check if there has been a significant change in scores, the following steps can be followed:

Step 1: To determine the change in scores, subtract the scores obtained before the workshop from the scores obtained after the workshop.

Step 2: Calculate the average score change for the group of 30 students by dividing the sum of score changes by 30.

Step 3: Calculate the standard deviation of the score change by using the following formula:
SD = √[∑ (Xi - X)2 / (n - 1)]
where Xi is the individual score change, X is the average score change, and n is the number of students.

Step 4: Use a t-test to determine if the change in scores is statistically significant. If the t-value is greater than the critical value (using a 5% significance level and 29 degrees of freedom), then the change in scores is significant.
Thus, by following these steps, the impact of the preparation workshop on first-time composite scores of the MAT can be assessed.

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The paired t-test is the appropriate statistical analysis to use for this type of data.

The first step to check for a significant change over first-time composite scores when a group of 30 high school seniors retake the Miller Analogies Test (MAT) after completing a Test Preparation Workshop, note that each student will have taken the MAT twice, once before and once following the workshop, and the scores are on a ratio scale is to compute the ratio of the scores before and after the workshop for each student.

Then, calculate the mean and standard deviation of the ratios.

Finally, conduct a paired t-test to determine if the mean ratio is significantly different from 1 at the 0.05 level of significance.

The paired t-test is the appropriate statistical analysis to use for this type of data.

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The square root of 8 - 2i, with the real part of the answer being positive, is approximately 2.34 + 0.52i.

To find the square root of 8 - 2i, we can represent the complex number in its polar form and then apply the square root operation.

First, we calculate the magnitude (r) and argument (θ) of the complex number 8 - 2i:

Magnitude: |8 - 2i| = √([tex]8^2[/tex] + (-2[tex])^2[/tex]) = √(64 + 4) = √68 = 2√17

Argument: θ = arctan(-2/8) = arctan(-1/4) ≈ -0.24498 radians

Next, we express the complex number in polar form:

8 - 2i = 2√17 * (cos(-0.24498) + isin(-0.24498))

To find the square root, we take the square root of the magnitude and divide the argument by 2:

√(8 - 2i) ≈ √(2√17) * (cos(-0.24498/2) + isin(-0.24498/2))

Simplifying the expression:

√(8 - 2i) ≈ √(2√17) * (cos(-0.12249) + isin(-0.12249))

≈ 2.34 + 0.52i

Therefore, the square root of 8 - 2i, with the real part of the answer being positive, is approximately 2.34 + 0.52i.

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Given two predictor variables with a correlation of 0.32879, we should expect there to be multicollinearity between them.

In a data set with a, b, c, d, e, and f numeric variables, given there is a strong correlation of these pairs (f, a), (f, c), (d, e), (a, d), we can set up a regression model as

Of-a + c Of-a + b + c + d + e Of-a + C + d + e Of-a + C + e.

Given two predictor variables with a correlation of 0.32879, we should expect there is multicollinearity between them.

The statement that is true regarding the given two predictor variables with a correlation of 0.32879 is:

we should expect there to be multicollinearity between them.

Multicollinearity is a situation in which two or more predictor variables in a multiple regression model are highly correlated with one another. Multicollinearity complicates the understanding of which predictor variables are significant in the regression model's estimation.

Therefore, given two predictor variables with a correlation of 0.32879, we should expect there to be multicollinearity between them.

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Answer:

1.41 kilograms

Step-by-step explanation:

Given data

290-gram bag of gummy worms

450-gram bag of sour keys

670-gram bag of chocolate-covered almonds

In all, she bought

=290+450+670

=1410grams of candy

Now let us convert from grams to kilograms

1000grams is equal to 1 kilogram

hence 1410 grams  will be x

cross multiply

1000x= 1410

x= 1410/1000

x= 1.41 kilograms

Let's denote the lengths of the legs of the right triangle as a and b, and the length of the hypotenuse as c. We are given that the altitude perpendicular to the hypotenuse is 12 cm.

Using the Pythagorean theorem, we have:

[tex]a^2 + b^2 = c^2[/tex]

The perimeter of the right triangle is given by:

Perimeter = a + b + c

We want to express the length of the hypotenuse (c) as a function of the perimeter.

Rearranging the equation for the perimeter, we have:

c = Perimeter - (a + b)

Substituting the equation for c into the Pythagorean theorem equation, we get:

[tex]a^2 + b^2[/tex] = (Perimeter - [tex](a + b))^2[/tex]

Expanding and simplifying, we have:

[tex]a^2 + b^2[/tex]= [tex]Perimeter^2[/tex] - 2Perimeter(a + b) +[tex](a + b)^2[/tex]

Simplifying further:

[tex]a^2 + b^2[/tex]= [tex]Perimeter^2[/tex]- 2Perimeter(a + b) + a^2 + 2ab + b^2

The terms with [tex]a^2[/tex] and [tex]b^2[/tex]cancel out, giving:

[tex]2ab = Perimeter^2 - 2Perimeter(a + b)[/tex]

Dividing both sides by 2, we have:

[tex]ab = (Perimeter^2 - 2Perimeter(a + b))/2[/tex]

[tex]ab = (Perimeter^2 - 2Perimeter(a + b))/2[/tex]

Now, since we are given that the altitude perpendicular to the hypotenuse is 12 cm, we know that:

ab = [tex]12^2 = 144[/tex]

We can solve this equation for either a or b, and then substitute the value into the expression for the hypotenuse (c):

For example, let's solve for a:

a = 144/b

Substituting this into the expression for c

c = Perimeter - (a + b)

c = Perimeter - (144/b + b)

Therefore, the length of the hypotenuse (c) can be expressed as a function of the perimeter.

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Answer: i dont know

Step-by-step explanation:

The slope of the line joining the given pair of points is 4/3.

The slope of the line joining the points (4, 6) and (1, 2) can be found using the formula:

slope = (y2 - y1) / (x2 - x1).

Substituting the coordinates of the two points into the formula:

slope = (2 - 6) / (1 - 4)

Calculating this expression:

slope = -4 / -3

Simplifying the fraction:

slope = 4/3

Therefore, the slope of the line joining the points (4, 6) and (1, 2) is 4/3.

To evaluate the slope of a line joining two points, we use the formula (y2 - y1) / (x2 - x1), where (x1, y1) and (x2, y2) are the coordinates of the two points. In this case, we substitute the coordinates (4, 6) and (1, 2) into the formula and calculate the expression.

Simplifying the fraction, we find that the slope of the line is 4/3. This means that for every 3 units of horizontal change (x-axis), the line rises by 4 units (y-axis).

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Answer:

x ≈ 9.6

Step-by-step explanation:

Using Pythagoras' identity in the right triangle, that is

x² + 14² = 17²

x² + 196 = 289 ( subtract 196 from both sides )

x² = 93 ( take the square root of both sides )

x = [tex]\sqrt{93}[/tex] ≈ 9.6 (to the nearest tenth )

(a) The transmitted codeword vector when 0100110 is received is 0100110.

To determine the transmitted codeword vector, we need to find the syndrome of the received vector and check if it corresponds to any error patterns. If the syndrome is zero, it means no error occurred during transmission.

Let's calculate the syndrome for the received vector 0100110 using the parity check matrix:

Received vector: r = 0 1 0 0 1 1 0

Parity check matrix: H = 0 0 0 1 1 1 1

                           0 1 0 1 0 1 0

                           1 0 1 0 1 0 1

To calculate the syndrome, we multiply the received vector by the transpose of the parity check matrix:

Syndrome = r * H^T

         = 0 1 0 0 1 1 0 * 0 0 1

                                0 1 0

                                1 0 1

                                1 0 1

                                0 1 0

                                1 0 1

                                0 1 0

         = 0 1 0 * 0 1 0

                  1 0 1

                  0 1 0

                  1 0 1

                  0 1 0

                  1 0 1

                  0 1 0

         = 0 0 0

The resulting syndrome is 0 0 0, which indicates that no error occurred during transmission. Therefore, the transmitted codeword vector is the same as the received vector: 0100110.

(b) The transmitted codeword vector when 0001111 is received is 1001111.

Following the same process as in part (a), let's calculate the syndrome for the received vector 0001111 using the parity check matrix:

Received vector: r = 0 0 0 1 1 1 1

Parity check matrix: H = 0 0 0 1 1 1 1

                           0 1 0 1 0 1 0

                           1 0 1 0 1 0 1

Syndrome = r * H^T

         = 0 0 0 1 1 1 1 * 0 0 1

                                0 1 0

                                1 0 1

                                1 0 1

                                0 1 0

                                1 0 1

                                0 1 0

         = 0 1 1 * 0 1 0

                  1 0 1

                  1 0 1

                  0 1 0

                  1 0 1

                  0 1 0

                  1 0 1

         = 0 1 1

The resulting syndrome is 0 1 1, which indicates an error occurred during transmission. To correct the error, we need to locate the error bit. The syndrome corresponds to the position of the error bit in the received vector.

The error bit is in position 3, so we flip the value of the bit in position 3 in the received vector:

Received vector (after error correction): 1001111

Since we assumed that no more than one error occurred during transmission, we can conclude that the transmitted cod

eword vector is 1001111.

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Answer:

do i need to answer them for me or just basically?

1. This is NOT a statistical question since you don't need data or mathematical data, or collection of nothing to come to a conclusion because it's a question for any person in the world and we know it's Donald Trump; we don't need math, collection of data or analysis to know this.

2. This is a statistical question because you need to use math to know this; you need to collect a lot of cupcakes, describe their types and size, you need to analyze and count how many you can eat, and see the results or side effects,  you might even have to do this more than one so you can gather all your quantitative to come to a conclusion.

3. This is NOT a statistical question. This is a yes or no question where you can ask anyone in your family if they speak another language, this doesn't require math or gathered data to come to a conclusion; the question would be statistical if it was, "How many people in your family speak another language COMPARED to the other people in your family? This would be an example of a statistical question given this scenario.