Are the estimated betas significant (hint: t-test)? What do they imply? How do you interpret the meaning of the estimated coefficient for Fitness Center?

The row where three consecutive entries occur in the ratio 3:4:5 is row 7 in Pascal's Triangle.

To find the row in Pascal's Triangle where three consecutive entries occur in the ratio 3:4:5, we can use the property of Pascal's Triangle, where each entry is the sum of the two entries above it.
Let's denote the three consecutive entries in the ratio as 3x, 4x, and 5x. Since these are consecutive entries, we can use the following relationships from Pascal's Triangle:
1. 4x = C(n, k) = C(n-1, k-1) + C(n-1, k), where C(n, k) represents a binomial coefficient.
2. 3x = C(n-1, k-1) and 5x = C(n-1, k).
Now, we can write the equation:
4x = 3x + 5x => x = 3C(n-1, k-1) = 5C(n-1, k).
We can see that 3 divides C(n-1, k) and 5 divides C(n-1, k-1). Let's try different values of n until we find the smallest integer that fits this condition.
For n = 6:
C(5, 1) = 5, which is divisible by 5.
C(5, 2) = 10, which is not divisible by 3.
For n = 7:
C(6, 1) = 6, which is not divisible by 5.
C(6, 2) = 15, which is divisible by 3.

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The revolutions the wheel will have to make before the car comes to a complete stop are approximately 25.5 revolutions.

To find out how many revolutions the wheel will have to make before the car comes to a complete stop, we need to use the information provided about the distance and diameter of the wheel.

First, we need to convert the diameter from centimeters to meters: 61 centimeters = 0.61 meters.

Next, we can use the formula for the circumference of a circle: C = πd, where C is the circumference and d is the diameter.

So the circumference of the wheel is: C = π(0.61m) = 1.92m.

Now we can use the distance the car can stop in, 49 meters, to calculate the number of revolutions of the wheel:

49m ÷ 1.92m/rev ≈ 25.5 revolutions.

Therefore, the wheel will have to make approximately 25.5 revolutions before the car comes to a complete stop.

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The probability of both the socks and the t-shirt being white is 21/44.

The probability of selecting a white pair of socks from the drawer is 6/11. The probability of selecting a white t-shirt from the drawer is 7/8. To find the probability of both events occurring together, we multiply the two probabilities:
P(white socks and white t-shirt) = (6/11) * (7/8) = 0.4773
Therefore, the probability of randomly selecting one pair of white socks and one white t-shirt from the drawer is approximately 0.4773 or 47.73%.
Hi there! To find the probability that both the socks and the t-shirt you randomly select are white, you'll need to multiply the individual probabilities for each item being white.
For the socks, there are 6 white pairs out of a total of 11 pairs. So, the probability of selecting a white pair is 6/11.
For the t-shirts, there are 7 white ones out of a total of 8. So, the probability of selecting a white t-shirt is 7/8.
Now, multiply these probabilities together: (6/11) * (7/8) = 42/88. Simplify the fraction to get 21/44.
So, the probability of both the socks and the t-shirt being white is 21/44.

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The width of a confidence interval for the population mean depends on the sample size, standard deviation, and the desired level of confidence. Generally, for a greater confidence level, the width of the confidence interval will be wider.

This is because a higher confidence level means that we want to be more certain that the true population mean falls within the interval. To achieve this higher level of certainty, we need to widen the interval to include a larger range of possible values for the population mean.

However, it's important to note that the increase in width may not be proportional to the increase in confidence level. In fact, the width of the confidence interval increases at a decreasing rate as the confidence level increases.

This means that the increase in width from a 90% confidence interval to a 95% confidence interval will be less than the increase in width from an 80% confidence interval to a 85% confidence interval, even though both involve a 5% increase in the level of confidence.

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Note that where the above qualities of a right triangle are given the value of BC in it's simples radical is 11√2.

Here we simply applied the trigonometric rule.

BC = a / Sin (Ф)

Where a = 11 and
Ф = 45

So

BC = 15.55635 = 11√2

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To find the 75th term of the sequence consisting of positive integers that can be expressed as a sum of distinct powers of 3. Thus, the 75th term of the sequence is $111$.

To find the 75th term of the sequence consisting of positive integers that can be expressed as a sum of distinct powers of 3, we can use the base-3 (ternary) numeral system. The 75th term can be represented as the 74th number in base-3 without a digit 2 (as it will require subtraction to form distinct powers of 3).

The 74th number in base-10 is represented as $74_{10}$, which when converted to base-3 is $2202_3$. Since we need to avoid the digit 2, we can carry out the operation similar to addition with carry-over: $2202_3 + 1111_3 = 10310_3$.

Now, we can convert $10310_3$ back to base-10: $(1 \times 3^4) + (0 \times 3^3) + (3 \times 3^2) + (1 \times 3^1) + (0 \times 3^0) = 81 + 0 + 27 + 3 + 0 = 111$.

Thus, the 75th term of the sequence is $111$.

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The measure of length of x from the similar triangles is x = 10

Given data ,

Let the first triangle be ΔABC

Let the second triangle be ΔACD

Now , AC is the common side of the triangle

And , they are similar triangles

So , the corresponding sides are in the same ratio

And , x / 5 = 20 / x

On cross multiplying , we get

x² = 100

Taking square roots on both sides , we get

x = 10

Hence , the length of side is x = 10

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The steps necessary to put he equation, x² - 3x + 27 = 8x - 3 in standard form is D. add 3 to both sides and subtract 8x from both sides

The standard form of quadratic equation is ax² + bx + c = 0, where 'a' is the leading coefficient and it is a non-zero real number.

Hence, let's represent x² - 3x + 27 = 8x - 3 in standard form as follows:

x² - 3x + 27 = 8x - 3

Therefore, the two steps that are necessary to make the quadratic equation in standard form is add 3 to both sides and subtract 8x from both sides

Hence,

x² - 3x - 8x + 27 + 3 = 8x - 8x - 3 + 3

x² - 11x + 30 = 0

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The  determinant of this matrix is -67/16.

To find the determinant of a matrix by row reduction to echelon form, we perform elementary row operations until the matrix is in echelon form, and then take the product of the diagonal entries. The determinant is the product of the pivots, with a factor of -1 for each row exchange.

Let's start with Exercise 5:

-1 -3  1
1  4  9
-1  0  5

We can start by adding the first row to the third row to eliminate the -1 in the (3,1) position:

-1 -3  1
1  4  9
0 -3  6

Next, we can multiply the third row by -1/3 to get a pivot in the (3,3) position:

-1 -3  1
1  4  9
0  1 -2

Then we add 3 times the second row to the third row to eliminate the 3 in the (3,2) position:

-1 -3  1
1  4  9
0  0  3

We now have an upper triangular matrix, which is in echelon form. The product of the diagonal entries is -1*4*3 = -12. Since we did not perform any row exchanges, there is no factor of -1. Therefore, the determinant of this matrix is -12.

Now let's move on to Exercise 6:

-1  0  5
3 -32  3
3  3  -1

We can start by adding 3 times the first row to the second row to eliminate the 3 in the (2,1) position:

-1  0   5
0 -32  18
3  3  -1

Then we can add the first row to the third row to eliminate the 3 in the (3,1) position:

-1  0   5
0 -32  18
0  3  4

Next, we can multiply the second row by -1/32 to get a pivot in the (2,2) position:

-1  0   5
0  1  -9/16
0  3   4

Then we add 9/16 times the second row to the third row to eliminate the -9/16 in the (3,2) position:

-1  0  5
0  1  -9/16
0  0  67/16

We now have an upper triangular matrix, which is in echelon form. The product of the diagonal entries is -1*1*67/16 = -67/16. Since we performed two row exchanges, there is a factor of (-1)^2 = 1. Therefore, the determinant of this matrix is -67/16.

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To solve this problem, we can use the law of total probability and the definition of conditional probability. Let's start by calculating the probabilities of the first ball being red or green:

Pr(R1) = (31)/(31+16+12) = 31/59

Pr(G1) = (16+20+24)/(31+16+12) = 28/59

(a) Pr(R2) = Pr(R2|R1)Pr(R1) + Pr(R2|G1)Pr(G1)

To calculate the conditional probabilities, we need to consider two cases:

If the first ball is red (R1), we pick the second ball from box B, which has 12 red balls and 20 green balls:

Pr(R2|R1) = 12/32

Pr(G2|R1) = 20/32

If the first ball is green (G1), we pick the second ball from box C, which has 24 red balls and 16 green balls:

Pr(R2|G1) = 24/40

Pr(G2|G1) = 16/40

Plugging these values into the formula, we get:

Pr(R2) = (12/32)(31/59) + (24/40)(28/59) = 65957/173420

(b) Pr(G2) = 1 - Pr(R2) = 107463/173420

(c) Pr[R2|R1] = 12/32 (as calculated above)

(d) Pr[R2|G1] = 24/40 (as calculated above)

(e) Pr[G2|G1] = 16/40 (as calculated above)

(f) Pr[G2|R1] = 20/32 = 5/8 (complementary to Pr[R2|R1])

Therefore, the answers are:

(a) Pr(R2) = 65957/173420

(b) Pr(G2) = 107463/173420

(c) Pr[R2|R1] = 12/32

(d) Pr[R2|G1] = 24/40

(e) Pr[G2|G1] = 16/40

(f) Pr[G2|R1] = 5/8

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To determine if a series is convergent or divergent, we need to analyze the behavior of the sequence of its partial sums. If the sequence approaches a finite limit as we add more and more terms, then the series is convergent. Otherwise, if the sequence either grows without bound or oscillates, then the series is divergent.

Without any specific series to consider, it's hard to give a definitive answer. However, in general, there are various techniques and tests we can use to evaluate the convergence or divergence of a series. Some common ones include the comparison test, the ratio test, the root test, the integral test, and the alternating series test.

If the series is convergent, we can also try to find its sum by using formulas or manipulations that express the series in a simpler form. For example, if the series is a geometric series, then we can use the formula for its sum. If the series is a telescoping series, then we can use partial fraction decomposition or other algebraic tricks to cancel out most of the terms.

Overall, the analysis of series convergence and divergence is an important topic in calculus and mathematical analysis, with many applications in physics, engineering, finance, and other fields.

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In scientific notation, we write a number as a product of a number between 1 and 10 and a power of 10. The number before the multiplication sign is the significant figure, and the power of 10 indicates the magnitude of the number. To write a number to 3 significant figures, we only include one non-zero digit before the decimal point.

1. 2450: First, identify the non-zero digits (2, 4, and 5). Write the number as 2.45 and multiply it by 10 raised to the power of the number of places you moved the decimal point (3 in this case). So, the answer is 2.45 x 10^3.

2. 0.000326: Identify the non-zero digits (3, 2, and 6) and write the number as 3.26. Move the decimal point 4 places to the right, so multiply by 10 raised to the power of -4. The answer is 3.26 x 10^-4.

3. 0.000934: With non-zero digits 9, 3, and 4, write the number as 9.34. Move the decimal point 4 places to the right and multiply by 10^-4. The answer is 9.34 x 10^-4.

4. 685000: The non-zero digits are 6, 8, and 5, so write the number as 6.85. Move the decimal point 5 places to the left and multiply by 10^5. The answer is 6.85 x 10^5.

In summary:
2450 = 2.45 x 10^3
0.000326 = 3.26 x 10^-4
0.000934 = 9.34 x 10^-4
685000 = 6.85 x 10^5

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The probability of getting a multiple of 4 or a multiple of 7 is 0.267

There are three multiples of 4 (4, 8, 12) and two multiples of 7 (7, 14) on the spinner.

However, 8 is a common multiple of 4 and 7, so it is counted twice. Thus, there are 4 outcomes that are either a multiple of 4 or a multiple of 7: 4, 7, 8, and 12.

The total number of possible outcomes is 15, since there are 15 sectors on the spinner.

Therefore, the probability of getting a multiple of 4 or a multiple of 7 is:

P(multiple of 4 or multiple of 7) = number of favorable outcomes / total number of possible outcomes

= 4 / 15

≈ 0.267

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Answer:

the answer is 1/3

To find P(AC), we need to remember that the probability of an event and its complement always adds up to 1. So, P(AC) = 1 - P(A) = 1 - 0.7 = 0.3.

Probability is simply how likely something is to happen. Whenever we're unsure about the outcome of an event, we can talk about the probabilities of certain outcomes—how likely they are. The analysis of events governed by probability is called statistics.

P(A or AC) is the probability that either event A occurs or its complement occurs. Since these two events are mutually exclusive (they cannot both happen at the same time), we can use the addition rule of probability to find P(A or AC) = P(A) + P(AC) = 0.7 + 0.3 = 1.

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To find the time required for more than 200 cars to have entered the parking lot with a probability of 0.9, we need to use the properties of the Poisson distribution and its cumulative distribution function (CDF).

Given:

- Poisson distribution rate (λ) = 100 cars per hour

- Desired probability (P(X > 200)) = 0.9

The Poisson distribution probability mass function (PMF) is given by:

P(X = k) = (e^(-λ) * λ^k) / k!

To find the time required, we need to determine the value of λt (λ multiplied by time) that corresponds to the desired probability.

Using the CDF of the Poisson distribution, we can express the desired probability as:

P(X > 200) = 1 - P(X ≤ 200)

Since the CDF is a cumulative probability, we want to find the time (t) at which P(X ≤ 200) is less than or equal to 0.1. We can incrementally increase t until we reach the desired probability.

Step 1: Calculate the rate parameter for the desired time:

λt = λ * t

100 * t = λt

Step 2: Calculate the cumulative probability P(X ≤ 200) using the Poisson CDF:

P(X ≤ 200) = ∑[k=0 to 200] (e^(-λt) * (λt)^k) / k!

Step 3: Incrementally increase t until P(X ≤ 200) ≤ 0.1:

Start with t = 0, and increase it until P(X ≤ 200) ≤ 0.1 is achieved. This can be done using numerical methods or a Poisson distribution calculator.

The specific value of time required can vary based on the precise probability calculation and numerical approximation used. To obtain an accurate and precise result, it is recommended to use specialized software, statistical calculators, or programming languages with built-in functions for Poisson distributions.

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The correct option is b. judgmental sampling; convenience sampling.  

Judgmental sampling was used in Mexico to ensure a representative sample of target respondents, while convenience sampling with the snowball procedure was employed in Saudi Arabia due to the absence of sampling frames and social customs prohibiting personal interviews.

The question is about the different sampling techniques used for the same consumer research study in Mexico and Saudi Arabia. In Mexico, judgmental sampling was used by having experts identify neighborhoods where the target respondents lived; homes were then randomly selected for interviews.

In Saudi Arabia, convenience sampling employing the snowball procedure was used because there were no lists from which sampling frames could be drawn and social customs prohibited spontaneous personal interviews.

Judgmental sampling, also known as expert sampling or purposive sampling, is a non-probability sampling technique where the researcher selects participants based on their expertise or knowledge about the population being studied.

In the case of Mexico, experts identified neighborhoods where target respondents lived, and homes were randomly selected for interviews. This technique helped ensure that the sample was representative of the target population.

On the other hand, convenience sampling is another non-probability sampling technique where participants are selected based on their availability and ease of access.

In Saudi Arabia, due to the absence of lists for sampling frames and social customs prohibiting spontaneous personal interviews, the snowball procedure was used. Snowball sampling is a type of convenience sampling where existing participants recruit additional participants from their network. This process continues until the desired sample size is achieved.

Therefore, the correct answer is b. judgmental sampling; convenience sampling.

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Strengths Finder 2.0 is a valuable tool that can help individuals identify and develop their unique strengths. By leveraging these strengths, individuals can achieve greater success in their personal and professional lives, and organizations can create a more positive and productive work environment.

Strengths Finder 2.0 is a popular survey tool that helps individuals identify their unique strengths and talents. The survey has been completed by 10 million people to date and has been adopted by many universities and organizations to assist individuals in identifying their strengths.

The survey consists of a series of questions designed to assess an individual's natural talents and abilities. The results are then used to provide personalized feedback and coaching on how to leverage those strengths in their personal and professional lives.

The use of Strengths Finder 2.0 has become increasingly popular in recent years as individuals and organizations recognize the importance of focusing on strengths rather than weaknesses. By identifying and developing their strengths, individuals can improve their performance, increase their engagement and job satisfaction, and achieve greater success in their careers.

Organizations that use Strengths Finder 2.0 have reported increased productivity, employee engagement, and retention rates. By providing employees with the tools and resources to develop their strengths, organizations can create a more positive and fulfilling work environment.

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The probability of choosing 6 people at random from the group and having all of them be left-handed is approximately 0.00002599 or 0.0026%.

We can approach this problem using the binomial distribution, which models the probability of a certain number of successes (in this case, choosing left-handed people) in a fixed number of trials (choosing 6 people).

Let p be the probability of choosing a left-handed person, which is given as 15% or 0.15. Then, the probability of choosing all 6 people to be left-handed can be calculated as:

P(6 left-handed) = (0.15[tex])^6[/tex] * (1 - 0.15)[tex]^(6 - 6) * C(6, 6)[/tex]

where C(6, 6) represents the number of ways to choose 6 items from a set of 6, which is equal to 1.

Plugging in the values, we get:

P(6 left-handed) = (0.15[tex])^6[/tex] * (0.85)^0 * 1

= 0.00002599

Therefore, the probability of choosing 6 people at random from the group and having all of them be left-handed is approximately 0.00002599 or 0.0026%.

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The equation to represent the relationship is x - 3y + 9 = 0.

We have the table

Input (x)     Output (y)

      3              4

      6              5

      9              6

     12              7

     15              8

So, the equation can be formed as

(y - 4) = (5-4)/ (6-3) (x-3)

y - 4 = 1/3 (x -3)

3y - 12 = x - 3

x - 3y - 3 + 12 =0

x - 3y + 9 = 0

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Answer: the answer is 2 I believe

Step-by-step explanation:as you look at “stem” and go down to the number 4. You count below that. So 8, and 6. That’s 2 numbers :) hope this helps!

The stem and leaf plot shows the ages of people at the library. 2 people are under the age of 40.

The duration of a being's or thing's existence; the length of its existence or life up until the moment being discussed or alluded to age. A time frame for humans that begins at birth and is measured in years.

This time frame is typically characterised by a specific stage or level of physical or mental development as well as the potential for legal responsibility. The stem and leaf plot shows the ages of people at the library. 2 people are under the age of 40.

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Therefore, there were 75 downloads of the standard version with total size downloaded is 75 MB + 3(25 MB) = 150 MB.

To solve this problem, we can use a system of equations. Let x be the number of downloads for the standard version and y be the number of downloads for the high-quality version.

From the problem, we know that:
- The size of the standard version is x MB
- The size of the high-quality version is 3y MB
- The total size downloaded for the two versions was x + 3y MB

Putting these equations together, we get:

x + 3y = 150

We also know that the size of the standard version is smaller than the high-quality version, so we can assume that the standard version was downloaded more times than the high-quality version:

x > y

Now we have two equations and two unknowns. We can solve for x and y by substitution or elimination.

Let's use substitution:

From the second equation, we can isolate y:

y = x/3

Substitute this into the first equation:

x + 3(x/3) = 150

Simplify:

x + x = 150

2x = 150

x = 75

So there were 75 downloads of the standard version.

To check our answer, we can find the number of downloads for the high-quality version:

y = x/3 = 75/3 = 25

And verify that the total size downloaded is 75 MB + 3(25 MB) = 150 MB.

Therefore, there were 75 downloads of the standard version.

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To determine the probabilities, we need to use the standard normal distribution table or a calculator that has this function. The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1.

(a) P(−0.79 ≤ z ≤ −0.57) = We need to find the area under the standard normal distribution curve between z = -0.79 and z = -0.57. Using a standard normal distribution table or calculator, we find this probability to be 0.0767.
(b) P(z > 1) = We need to find the area under the standard normal distribution curve to the right of z = 1. Using a standard normal distribution table or calculator, we find this probability to be 0.1587.

(c) P(z ≥ −3.36) = We need to find the area under the standard normal distribution curve to the right of z = -3.36 (or the area to the left of z = 3.36, which is the same thing since the standard normal distribution is symmetrical). Using a standard normal distribution table or calculator, we find this probability to be 1.

(d) P(z < 4.96) = We need to find the area under the standard normal distribution curve to the left of z = 4.96. Since this value is greater than any z-score on the standard normal distribution table, we can say that this probability is extremely close to 1 (or practically 1).


To find the probabilities for a standard normal distribution, you can use a z-table or an online calculator based on the given intervals, rounding to four decimal places:

(a) P(-0.79 ≤ z ≤ -0.57) = P(z ≤ -0.57) - P(z ≤ -0.79) = 0.2843 - 0.2148 = 0.0695
(b) P(z > 1) = 1 - P(z ≤ 1) = 1 - 0.8413 = 0.1587
(c) P(z ≥ -3.36) = 1 - P(z < -3.36) = 1 - 0.0004 = 0.9996
(d) P(z < 4.96) = 0.9999 (since the probability of z > 4.96 is extremely small)

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The null and alternative hypotheses are H₀ = μ ≥ 6 and H₁ = μ < 6.

Given that, the mean GPA of students in colleges is different from 2.0 (out of 4.0).

H₀: μ = 2.0 and H₁: μ ≠ 2.0

So,

We test the likelihood of the statement being true in order to decide whether to accept or reject our alternative hypothesis. Since, the question wants to test if the college student take less than six years to graduate on average, then we take, H₀ = μ ≥ 6.

And,

WE determine whether to accept or reject based on the likelihood of the null hypotheses being true, so we then take H₁ = μ < 6.

Hence, the null and alternative hypotheses are H₀ = μ ≥ 6 and H₁ = μ < 6.

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The complex number (cos π/4 + i sin π/4)³ can be written in a trigonometric form as (cos π³/64 + i sin π³/64).

We have,

De Moivre's theorem states that for any non-zero complex number

z = r(cosθ + i sinθ) and any positive integer n.

z^n = r^n (cos nθ + i sin nθ)

In this case,

We have z = cos π/4 + i sin π/4 and n = 3.

So we can apply de Moivre's theorem as follows:

z³ = (cos π/4 + i sin π/4)³

= cos³ π/4 + 3i cos² π/4 sin π/4 - 3 cos π/4 sin² π/4 - i sin³ π/4

= (cos³ π/4 - 3 cos π/4 sin² π/4) + i (3 cos² π/4 sin π/4 - sin³ π/4)

We can simplify the real and imaginary parts using the trigonometric identities:

cos³ θ - 3 cos θ sin² θ = cos 3θ

3 cos² θ sin θ - sin³ θ = sin 3θ

So we get:

z³ = cos 3π/4 + i sin 3π/4

= cos π³/4 + i sin π³/4

Therefore,

The complex number (cos π/4 + i sin π/4)³ can be written in a trigonometric form as (cos π³/64 + i sin π³/64).

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The complete question:

Use de Moivre's theorem to write the complex number in trigonometric form (cos π/4 + i sin π/4)³

(cos π³/64 + i sin π³/64)

The sum of all the perfect squares between $15$ and $25$, inclusive, minus the sum of all the other integers between $15$ and $25$, inclusive, is [tex]$-164$[/tex].

To find the sum of all the perfect squares between $15$ and $25$, we need to list them out: $16$, $25$. The sum of these perfect squares is $16+25=41$.

To find the sum of all the other integers between $15$ and $25$, we can use the formula for the sum of an arithmetic series. The sum of an arithmetic series is equal to the average of the first and last term, multiplied by the number of terms. In this case, the first term is $16$ and the last term is $25$, so there are $10$ terms. The average of the first and last term is [tex]$\frac{16+25}{2}=20.5$[/tex]. Therefore, the sum of all the other integers between $15$ and $25$ is $20.5\times 10 = 205$.

Now we can subtract the sum of all the other integers from the sum of the perfect squares to get our final answer: $41-205 = -164$.

Therefore, the sum of all the perfect squares between $15$ and $25$, inclusive, minus the sum of all the other integers between $15$ and $25$, inclusive, is $-164$.

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The probability that in a randomly selected hour, the number of calls is 2 is approximately 0.133 or 13.3%.

The number of calls received by a car towing service follows a Poisson distribution with an average of 18 calls per day (per 24-hour period). To find the mean number of calls per hour, divide the daily average by the number of hours in a day: 18 calls/day ÷ 24 hours/day = 0.75 calls/hour.

Now, to calculate the probability that in a randomly selected hour, the number of calls is 2, we can use the formula for the Poisson distribution:

P(X=k) = (e^(-λ) * λ^k) / k!

where P(X=k) is the probability of having k calls, λ is the mean number of calls per hour (0.75 in this case), k is the desired number of calls (2), e is the base of the natural logarithm (approximately 2.718), and k! is the factorial of k.

Plugging in the values, we get:

P(X=2) = (e^(-0.75) * 0.75^2) / 2!

P(X=2) ≈ (0.472 * 0.5625) / 2 ≈ 0.133

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A planning phase for an engineering component generated 80 engineering drawings. The QA team randomly selected 8 drawings for inspection. This exercise can BEST be described as example of random sampling.

The exercise can be described as an example of random sampling, which is a statistical technique used to select a subset of individuals or items from a larger population, in a way that each member of the population has an equal chance of being selected. In this case, the 80 engineering drawings represent the population, and the QA team randomly selecting 8 of them for inspection is a form of random sampling.

By selecting the drawings randomly, the QA team can get an unbiased representation of the population and make inferences about the quality of the engineering component as a whole based on the inspection results of the selected subset.

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The educational researcher will need a sample size of at least 385 community college students to estimate the mean score on the math part of the SAT with a margin of error of 10 and 95% confidence.

To calculate the sample size required to estimate the mean score on the math part of the SAT of all community college students in the state, we can use the following formula:

n = (Zα/2 × σ / E) ^ 2

where:

n = sample size

Zα/2 = the z-score corresponding to the desired level of confidence (in this case, 95% confidence corresponds to a z-score of 1.96)

σ = the standard deviation of the population (given as 100)

E = the desired margin of error (given as 10)

Substituting the given values into the formula, we get:

n = (1.96 × 100 / 10) ^ 2

n = 384.16

Rounding up to the nearest integer, we get a sample size of 385. Therefore, the educational researcher will need a sample size of at least 385 community college students to estimate the mean score on the math part of the SAT with a margin of error of 10 and 95% confidence.

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Each team member should run 9073.6 miles in the race on Course B.

Let's break down the problem step by step:

1. First, we need to find the length of Course B. We know that Course B is 212 times as long as Course A, and Course A is 214 miles. So, to find the length of Course B, we multiply:
  Course B length = 212 × 214 miles

2. Calculate the length of Course B:
  Course B length = 45368 miles

3. Now, we need to determine the distance each team member should run. There are 5 members on the team, and they need to run an equal distance on Course B. To find the distance for each member, we divide the total length of Course B by the number of team members:
  Distance per member = Course B length / number of members

4. Calculate the distance per team member:
  Distance per member = 45368 miles / 5

5. Finally, we find the distance each team member should run:
  Distance per member = 9073.6 miles

So, each team member should run 9073.6 miles in the race on Course B.

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Answer: 9.01 is the answer

Step-by-step explanation: Because when you add the number in the square you can split the number you add to the nearest sum to the number you get in the outcum.