X is the midpoint of AB. B has coordinates (12, -7), and X has coordinates
Y
(3,-1). Identify the coorditates of A.
O (21,-13)
O (7.5,-4)
O (-4, 7.5)
O (-6, 5)

Answer:700

Step-by-step explanation:

The resulting matrix using the specified row transformation to change the matrix; - 4 times row 1 added to row 2 is 0 -8

To apply the specified row transformation, we need to subtract 4 times the first row from the second row.

So the resulting matrix will be:

[  2              3

8 - 4 ( 2 )   4 - 4 ( 3 ) ]

which simplifies to:

[ 2   3

0   -8 ]

Therefore the resulting matrix for the specified row transformation is 0 and - 8.

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Answer:

The answer is 0.

Step-by-step explanation:

[tex] log_{2}(32) = 5[/tex]

[tex] log_{5}(5) = 1[/tex]

[tex] log_{3}(1) = 0[/tex]

The probability of winning the minimum award is 1/16,448.

To calculate this probability, follow these steps:

1. Find the total number of ways to pick two white balls from 58: C(58,2) = 58!/(2!(58-2)!) = 1,653.

2. Find the total number of ways to pick one gold ball from 44: C(44,1) = 44!/(1!(44-1)!) = 44.

3. Multiply the number of ways to pick two white balls and one gold ball: 1,653 * 44 = 72,732.

4. Calculate the total number of possible combinations: 58 * 57 * 56 * 55 * 44 = 1,195,084,680.

5. Divide the number of successful combinations by the total number of combinations: 72,732 / 1,195,084,680 = 1/16,448.

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The given values modulo 45 are 192 (mod 45) = 12, 194 (mod 45) = 14, 198 (mod 45) = 18, and 1916 (mod 45) = 1.

To find the value of modulo of 192 (mod 45),

we can divide 192 by 45 and take the remainder

192 = 4 (45) + 12

So, 192 (mod 45) = 12.

To find 194 (mod 45),

we can divide 194 by 45 and take the remainder

194 = 4 (45) + 14

So, 194 (mod 45) = 14.

To find 198 (mod 45),

we can divide 198 by 45 and take the remainder

198 = 4 (45) + 18

So, 198 (mod 45) = 18.

To find 1916 (mod 45),

we can first reduce 1916 by reducing each digit

1916 = 1 (mod 45)

Therefore, 1916 (mod 45) = 1.

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s = −81/4,t = −34 so its

Step-by-step explanation:

Change in concentration = c(5/6) - c(2/3). To estimate the change in concentration (C) in mg/ml of a certain drug in a person's bloodstream when t changes from 40 to 50 minutes,

we will use the given model: c(t) = 2t / (3 + e^(-0.01t)).

First, let's convert the time from minutes to hours since the model uses hours:
40 minutes = 40/60 = 2/3 hours
50 minutes = 50/60 = 5/6 hours
Next, we will calculate the concentration at these times using the model:
1. For t = 2/3 hours:
c(2/3) = 2(2/3) / (3 + e^(-0.01(2/3)))

2. For t = 5/6 hours:
c(5/6) = 2(5/6) / (3 + e^(-0.01(5/6)))
Now, estimate the change in concentration by subtracting the concentrations at these two times:
Change in concentration = c(5/6) - c(2/3)

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Given:

AE = AC + CE = 4 + 12 = 16

BE = BD + DE = 4⅔ + 14 = 14/3 + 14 = 56/3

To Prove:

AB || CD

Now,

By converse of ∆ proportionality theorem

EC/CA = ED/DB

12/4 = 14/4⅔

3 = 14 ÷ 14/3

3 = 14 × 3/14

3 = 3

L H S = R H S

HENCE PROVED!

(a) The number of binary strings of length 10 with at least one 1 is 1023.

(b) The number of binary strings of length 10 with at least one 1 and at least one 0 is 2045.

(a) To count the number of binary strings of length 10 with at least one 1, we can subtract the number of strings with all 0's from the total number of binary strings of length 10.

The total number of binary strings of length 10 is 2^10 = 1024, and the number of strings with all 0's is 1 (namely, 0000000000). Therefore, the number of binary strings of length 10 with at least one 1 is:

1024 - 1 = 1023

(b) To count the number of binary strings of length 10 with at least one 1 and at least one 0, we can use the principle of inclusion-exclusion.

The number of strings with at least one 1 is 1023 (as we calculated in part (a)), and the number of strings with at least one 0 is also 1023 (since the complement of a string with at least one 0 is a string with all 1's, and we calculated the number of strings with all 0's in part (a)).

However, some strings have both no 0's and no 1's, so we need to subtract those from the total count. There is only one such string, namely 1111111111. Therefore, the number of binary strings of length 10 with at least one 1 and at least one 0 is:

1023 + 1023 - 1 = 2045.

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Answer:

11 tables - $145

t tables - 35 + 10t

Step-by-step explanation:

11 tables: $35 + 10*11 tables = 145

Answer:

total earning with 11 tables: $145

Step-by-step explanation:

if he gets a $10 tip per table you would do 10×11=110

and since he gets a guaranteed $35 a day you would do 35+110=145

The probability of selecting a college with in-state tuition less than $5,000 is 10%.

To calculate the probability that a randomly selected college will have an in-state tuition of less than $5,000, we first need to gather data on the number of colleges with in-state tuition less than $5,000 and the total number of colleges.

Let's assume that there are 500 colleges in the dataset, out of which 50 have in-state tuition less than $5,000.

So, the probability of selecting a college with in-state tuition less than $5,000 can be calculated as:

P(In-state tuition < $5,000) = Number of colleges with In-state tuition < $5,000 / Total number of colleges

P(In-state tuition < $5,000) = 50 / 500

P(In-state tuition < $5,000) = 0.1 or 10%

Therefore, the probability of selecting a college with in-state tuition less than $5,000 is 10%.

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The solution of the given initial value problem for r as a vector function of t is [tex]r(t) = 3(t + 1)^{(3/2)} i + (-6 e^{-t} + 6) j + (ln(t + 1) + 1) k[/tex].

A differential equation is an equation that contains one or more terms and the derivatives of one variable (i.e., dependent variable) with respect to the other variable (i.e., independent variable).

To solve the given differential equation, we will integrate each component of the differential equation and apply the initial condition.

Differential Equation: dr/dt = [tex]9/2 (t + 1)^{1/2} i + 6 e^{-t} j + 1/(t + 1) k[/tex]
Initial condition: r(0) = k

Step 1: Integrate each component of the differential equation with respect to t:
[tex]r(t) = \int(9/2 (t + 1)^{1/2}) dt \ i + \int(6 e^{-t}) dt \ j + \int(1/(t + 1)) dt \ k[/tex]

Step 2: Solve the integrals:
[tex]r(t) = [3(t + 1)^{(3/2)}] i - [6 e^{-t}] j + [ln(t + 1)] k + C[/tex]

Step 3: Apply the initial condition r(0) = k:
[tex]k = [3(0 + 1)^{(3/2)}] i - [6 e^0] j + [ln(0 + 1)] k + C[/tex]
k = 0 i - 6 j + 0 k + C
C = 6j + k

Step 4: Substitute C back into the expression for r(t):
[tex]r(t) = [3(t + 1)^{(3/2)}] i - [6 e^{-t}] j + [ln(t + 1)] k + (6j + k)[/tex]

So, the vector function r(t) is:
[tex]r(t) = 3(t + 1)^{(3/2)} i + (-6 e^{-t} + 6) j + (ln(t + 1) + 1) k[/tex].

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You should originally invest $148.

To solve this problem, we need to use the formula for present value of a bond:

[tex]PV = C/(1+r)^t[/tex]

where PV is the present value, C is the annual coupon payment, r is the annual interest rate, and t is the time to maturity in years.

We know that the General Electric bonds had a time to maturity of 87 years and an annual rate of 5.25%. We also know that they paid a total of $6,630 at maturity. Let's call the original investment amount X.

Using the formula, we can set up the following equation:

[tex]6,630 = X/(1+0.0525)^{87[/tex]

Simplifying this equation, we get:

[tex]X = 6,630 * (1+0.0525)^{-87[/tex]

Using a calculator, we get:

X = $147.91

Rounding this to the nearest dollar, the answer is:

$148

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The correct statement when using the Excel Regression tool is:

d. Checking the option Constant is Zero forces the intercept to zero.

Explanation: The Excel Regression tool is used to perform linear regression analysis on a set of data. The independent variable values are specified in the Input X Range, while the dependent variable values are specified in the Input Y Range. The Regression tool can be found in the Data Analysis tab under the Analysis group.

When performing linear regression analysis, the intercept term represents the value of the dependent variable when the independent variable is equal to zero. Checking the option Constant is Zero in the Regression tool forces the intercept term to be zero, which can be useful in certain cases. However, it may also reduce the analysis' fit to the data and should be used with caution.

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Answer:6.9 and 8.5

Step-by-step explanation: 7.7-0.8=6.9 hours

7.7+0.8=8.5 hours

since it starts at 135 and doubles every week f(n)=135*2^n-1

so for example after 4 weeks it would be f(4)=135*2^4-1=135*2^3=135*2*2*2=1080

The greatest common divisor of the pair of integers 19 and 1919 is 19.

the greatest common divisor (GCD) of the pair of integers you provided. The pair of integers in question is 19 and 1919.

To find the GCD, you can use the Euclidean algorithm:

1. Divide the larger integer (1919) by the smaller integer (19) and find the remainder.
  1919 ÷ 19 = 101 with a remainder of 0.

2. Since there is no remainder, the smaller integer (19) is the greatest common divisor.

So, the greatest common divisor of the pair of integers 19 and 1919 is 19.

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a. The null hypothesis for this statement would be that the number of children the younger sister has is not dependent on the number of children the older sister has.

b. The null hypothesis for this statement would be that the distribution of family sizes for older and younger sisters is the same.

For a, The alternative hypothesis would be that there is a dependency between the two variables. This hypothesis can be tested using a chi-squared test for independence.

For b,The alternative hypothesis would be that the distributions are different. This hypothesis can be tested using a two-sample t-test for comparing means or a chi-squared test for comparing proportions.

Both hypotheses can be true or false independently. It is possible that the number of children the younger sister has is independent of the number of children the older sister has, but the distribution of family sizes could be different for older and younger sisters. Conversely, it is also possible that the number of children the younger sister has is dependent on the number of children the older sister has, but the distribution of family sizes is the same for both.

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Complete Question:  

A sociologist is studying influences on family size. He finds pairs of sisters, both of whom are married, and determines for each sister whether she has 0, 1, or 2 or more children. He wants to compare older and younger sisters. Explain what the following hypotheses mean and how to test them.

   a. The number of children the younger sister has is independent of the number of children the older sister has.

     b. The distribution of family sizes is the same for older and younger sisters. Could one hypothesis be true and the other false? Explain.

To determine if the normal approximation to the binomial is appropriate, we need to check if both np and n(1-p) are greater than or equal to 10.

(a) For n = 500 and p = 0.33, np = 165 and n(1-p) = 335, both of which are greater than 10. Therefore, the normal approximation to the binomial is appropriate.

(b) For n = 400 and p = 0.01, np = 4 and n(1-p) = 396, which are not both greater than 10. Therefore, the normal approximation to the binomial is not appropriate.

(c) For n = 100 and p = 0.61, np = 61 and n(1-p) = 39, both of which are greater than 10. Therefore, the normal approximation to the binomial is appropriate.
To determine if the normal approximation to the binomial is appropriate in each situation, we can use the following rule of thumb: the normal approximation is suitable when both np and n(1-p) are greater than or equal to 10.
A binomial is a polynomial that is the sum of two terms, each of which is a monomial .It is the simplest kind of a sparse polynomial after the monomials.

(a) n = 500, p = 0.33
np = 500 * 0.33 = 165
n(1-p) = 500 * (1 - 0.33) = 500 * 0.67 = 335
Since both values are greater than 10, the normal approximation is appropriate.
Normal distributions are important in statistics and are often used in the natural to represent real-valued random variables whose distributions are not known. Their importance is partly due to the central limit theorem.

(b) n = 400, p = 0.01
np = 400 * 0.01 = 4
n(1-p) = 400 * (1 - 0.01) = 400 * 0.99 = 396
Since np is less than 10, the normal approximation is not appropriate.

(c) n = 100, p = 0.61
np = 100 * 0.61 = 61
n(1-p) = 100 * (1 - 0.61) = 100 * 0.39 = 39
Since both values are greater than 10, the normal approximation is appropriate.

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Okay, here are the steps:

* Hassam buys 2 adult tickets and 2 child tickets

* Let's assume:

** Adult ticket price = $50

** Child ticket price = $25

* So total ticket price = 2 * $50 + 2 * $25 = $200

* The booking fee is 5% of the total cost

* 5% of $200 is $10

* So total payment = $200 + $10 = $210

Therefore, the total Hassam pays altogether is $210

The value of dot product (6+8)⋅(−10) is -140.

The value of (6u+v)⋅(u−10v) can be found using the distributive property and the dot product formula, which is (6u⋅u)+(v⋅u)-(60v⋅v). Substituting the given values, we get (6(6)²)+(8(6))-(60(4)²) = 92.

In the given problem, we are given the values of dot product, norms of two vectors u and v. We need to find the value of (6+8)⋅(−10) and (6u+v)⋅(u−10v). Using the formula for dot product, we get the value of the first expression as -140. For the second expression, we use the distributive property and the formula for dot product.

After substituting the given values, we simplify the expression to get the answer 92. The dot product is a useful tool in linear algebra and can be used to find angles between vectors, projections of vectors, and more.

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The repeated measures test, also known as a within-subjects or paired design, decreases the influence of individual differences compared to an independent t-test. The correct answer is c. paired/independent.

A repeated measures test decreases variability between subjects because it is a within-subjects design, meaning that each participant is measured multiple times under different conditions. This reduces the variability between participants and increases the power of the test. In contrast, an independent t-test is a between-subjects design and compares the means of two independent groups, resulting in more variability between subjects. The type of test statistic used depends on the design of the study - a within design uses a paired test statistic, while a between design uses an independent test statistic. Therefore, the answer is c. paired/independent.

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We can start by simplifying each factor separately and then combine them.

(a + b)/(a^2 + b^2) can be simplified by multiplying both the numerator and denominator by (a - b):

(a + b)/(a^2 + b^2) * (a - b)/(a - b) = (a^2 - b^2)/(a^3 - b^3)

Next, we simplify a/(a - b) by multiplying both the numerator and denominator by (a + b):

a/(a - b) * (a + b)/(a + b) = a(a + b)/(a^2 - b^2)

Lastly, we simplify (a^4 - b^4)/(a + b)^2 by factoring the numerator and expanding the denominator:

(a^4 - b^4)/(a + b)^2 = [(a^2)^2 - (b^2)^2]/(a + b)^2 = [(a^2 + b^2)(a^2 - b^2)]/(a + b)^2

Now we can combine all three simplified factors:

(a + b)/(a^2 + b^2) * a/(a - b) * (a^4 - b^4)/(a + b)^2 = [(a^2 - b^2)/(a^3 - b^3)] * [a(a + b)/(a^2 - b^2)] * [(a^2 + b^2)(a^2 - b^2)]/(a + b)^2

Simplifying further, we can cancel out the (a^2 - b^2) terms and the (a + b) terms:

= [a(a + b)/(a^3 - b^3)] * [(a^2 + b^2)/(a + b)]

= a(a + b)(a^2 + b^2)/(a + b)(a^3 - b^3)

= a(a^2 + b^2)/(a^3 - b^3)

Therefore, the simplified expression is a(a^2 + b^2)/(a^3 - b^3)

The terms of the sequence continue to increase without bound, we can say that the sequence is not bounded.

To determine whether the sequence is increasing or decreasing, we need to compare consecutive terms of the sequence.

For n = 1, a1 = 6(1) + 2 = 8

For n = 2, a2 = 6(2) + 2 = 14

For n = 3, a3 = 6(3) + 2 = 20

Since each term of the sequence is greater than the previous one, we can say that the sequence is increasing.

To determine if the sequence is bounded, we need to check if it approaches infinity or if it has a finite upper and lower bound. Since the terms of the sequence continue to increase without bound, we can say that the sequence is not bounded.

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To use the Chi Squared test on the resulting data we can use the following statements in order:

D. He takes a random sample of balloons.

B. He samples 36 balloons at most.

C. He expects each color to appear at least 5 times.

A statistical hypothesis test used to examine if a variable is likely to come from a specific distribution is the Chi-square goodness of fit test. To ascertain if sample data is representative of the total population, it is widely utilised.

To let you know if there is a correlation, the Chi-Square test provides a P-value. An assumption is being considered, which we can test later, that a specific condition or statement may be true. Consider this: The data collected and expected match each other quite closely, according to a very tiny Chi-Square test statistic. The data do not match very well, according to a very significant Chi-Square test statistic. The null hypothesis is disproved if the chi-square score is high.

Here in the question,

To use the Chi Squared test on the resulting data we can use the following statements in order:

D. He takes a random sample of balloons.

B. He samples 36 balloons at most.

C. He expects each color to appear at least 5 times.

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The complete question is:

Peter bought a big pack of

360

360360 party balloons. The balloons come in

6

66 different colors which are supposed to be distributed evenly in the pack.

Peter wants to test whether the distribution is indeed even, but he doesn't want to go over the entire pack. So, he plans to take a sample and carry out a

χ

2

χ

2

\chi, squared goodness-of-fit test on the resulting data.

Which of these are conditions for carrying out this test? Choose 3 options.

A. He observes each color at least 5 times.

B. He samples 36 balloons at most.

C. He expects each color to appear at least 5 times.

D. He takes a random sample of balloons.

Answer: the answer is A B D

Step-by-step explanation:

Answer:

8) The distance the jet traveled is the area under the graph.

9) (1/2)(600)(20 + 25) = 13,500 miles

10) (1/2)(600)(5) = 1,500 miles

The probabilities for:

a. P(48 <X <66) = 0.978.

b. P(X> 69) = 0.0618.

c. P(X <= 65)  = 0.8051

d. P(X < 60) = 0.5

a. P(48 < X < 66) can be approximated using the normal distribution as follows:

mean, μ = np = 150 × 0.4 = 60

standard deviation, σ = [tex]\sqrt{(np(1-p)) }[/tex]= [tex]\sqrt{(150 * 0.4 * 0.6)[/tex] = 5.81

We can standardize using the formula z = (x - μ) / σ to find the area under the standard normal distribution between the z-scores corresponding to x = 48 and x = 66:

z1 = (48 - 60) / 5.81 = -2.06

z2 = (66 - 60) / 5.81 = 1.03

Using a standard normal distribution table, we find the area between these z-scores to be approximately 0.978. Therefore, P(48 < X < 66) ≈ 0.978.

b. P(X > 69) can be approximated using the normal distribution as follows:

mean, μ = np = 150 × 0.4 = 60

standard deviation, σ = [tex]\sqrt{(np(1-p)) }[/tex]= [tex]\sqrt{(150 * 0.4 * 0.6)[/tex] = 5.81

We can standardize using the formula z = (x - μ) / σ to find the area under the standard normal distribution to the right of the z-score corresponding to x = 69:

z = (69 - 60) / 5.81 = 1.55

Using a standard normal distribution table, we find the area to the right of this z-score to be approximately 0.0618. Therefore, P(X > 69) ≈ 0.0618.

c. P(X <= 65) can be approximated using the normal distribution as follows:

mean, μ = np = 150 × 0.4 = 60

standard deviation,  σ = [tex]\sqrt{(np(1-p)) }[/tex]= [tex]\sqrt{(150 * 0.4 * 0.6)[/tex]= 5.81

We can standardize using the formula z = (x - μ) / σ to find the area under the standard normal distribution to the left of the z-score corresponding to x = 65:

z = (65 - 60) / 5.81 = 0.86

Using a standard normal distribution table, we find the area to the left of this z-score to be approximately 0.8051. Therefore, P(X <= 65) ≈ 0.8051.

d. P(X < 60) can be approximated using the normal distribution as follows:

mean, μ = np = 150 × 0.4 = 60

standard deviation, σ = sqrt(np(1-p)) = sqrt(150 × 0.4 × 0.6) = 5.81

We can standardize using the formula z = (x - μ) / σ to find the area under the standard normal distribution to the left of the z-score corresponding to x = 60:

z = (60 - 60) / 5.81 = 0

Using a standard normal distribution table, we find the area to the left of this z-score to be 0.5. Therefore, P(X < 60) ≈ 0.5.

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Answer:

Tooo mny

Step-by-step explanation:

I think, you need to add al the sides then subtract by 180