Please help me, GodBless.

Answer:

Add

Step-by-step explanation:

When MULTIPLY exponents with same base, you Keep the base and + ADD the exponents.

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Answer:

5

Step-by-step explanation:

Pythagorean Theorem. The 13-meter ladder is leaning against a wall, so it's the hypotenuse.

It reaches 12 meters up, so 12 is one leg.

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

[tex]a^{2}+12^{2}=13^{2}[/tex]

[tex]a^{2}+144=169[/tex]

[tex]a^{2}=25[/tex]

a = 5

(a) The measure of the radius, r, is 5√5. (b) The measure of angle θ is approximately -63.43 degrees or approximately 296.57 degrees.

(c) A positive angle coterminal with θ is approximately 656.57 degrees.

(d) A negative angle coterminal with θ is approximately -63.43 degrees.

(e) An angle with the same value of cos θ but not coterminal with θ can be found using arccos(cos θ) + 360 degrees.

(a) To find the measure of the radius (r), we can use the distance formula, which states that the distance between two points (x1, y1) and (x2, y2) is given by the formula [tex]\sqrt{((x2 - x1)^2 + (y2 - y1)^2)}[/tex]. In this case, the coordinates of the point P(-5, 10) represent the values (x1, y1), and the origin (0, 0) represents the values (x2, y2). Plugging in the values, we get [tex]\sqrt{((-5 - 0)^2 + (10 - 0)^2) }[/tex]= sqrt(25 + 100) = sqrt(125) = 5*sqrt(5). So, the measure of the radius is 5*√(5).

(b) To find the measure of angle 0, we can use inverse trigonometric functions. Since the coordinates of the point P(-5, 10) correspond to the values of x and y, we can use the arctan function to find the angle. The formula for finding the angle in standard position is given by arctan(y/x). Plugging in the values, we get arctan(10/-5) = arctan(-2). Using a calculator, we find that the measure of angle 0 is approximately -63.43 degrees or approximately 296.57 degrees (since the angle is in the second quadrant, we add 360 degrees to get a positive coterminal angle).

(c) To find a positive angle coterminal with 0, we can add multiples of 360 degrees to the angle. In this case, adding 360 degrees to the angle of approximately 296.57 degrees, we get a positive coterminal angle of approximately 656.57 degrees.

(d) To find a negative angle coterminal with 0, we can subtract multiples of 360 degrees from the angle. In this case, subtracting 360 degrees from the angle of approximately 296.57 degrees, we get a negative coterminal angle of approximately -63.43 degrees.

(e) To find an angle with the same value of cos 0 but not coterminal with 0, we can use the inverse cosine function. The formula for finding the angle is given by arccos(cos 0). Since cosine is a periodic function, angles with the same value of cosine repeat every 360 degrees. Therefore, we can find an angle by using arccos(cos 0) + 360 degrees.

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Answer:

Option 2, d; corresponding

Step-by-step explanation:

since 6 and 18 are on the same line (line d) and is on the same spot, they are considerd corresponding.

(a) The basis for the kernel of T is {(-1, 1, 1)}. (b) The basis for the range of T is {(2, 1, 0), (1, 1, 1)}. (c) The rank of T is 2. (d) The nullity of T is 1.

(a) To find the basis for the kernel of T, we need to solve the equation T(v) = 0. This is equivalent to finding the null space of the matrix A. By performing row reduction on A, we find that the basis for the kernel is {(-1, 1, 1)}.

(b) The range of T is the set of all possible outputs of T. To find the basis for the range, we can consider the columns of A that correspond to the pivot positions after row reduction. In this case, the columns {2, 1} and {1, 1} correspond to the pivot positions, so the basis for the range is {(2, 1, 0), (1, 1, 1)}.

(c) The rank of T is the dimension of the range, which is the number of linearly independent vectors in the basis for the range. In this case, the rank of T is 2.

(d) The nullity of T is the dimension of the kernel, which is the number of linearly independent vectors in the basis for the kernel. In this case, the nullity of T is 1.

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The most likely numeric measure to produce invalid statistical analysis would be  Pain rating as: none = 0; slight = 1; much = 2.

This is because assigning numerical values to categorical data in an arbitrary manner may not accurately represent the true nature of the variable. The assigned values of 0, 1, and 2 may not reflect the actual differences in pain intensity between the categories.

Statistical analysis requires meaningful and quantitative data, and converting qualitative variables into numerical values without a clear and consistent measurement scale can lead to misleading or invalid results. Therefore, option B) would be the most likely to produce invalid statistical analysis.

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Answer:

I think that is right

Step-by-step explanation:

I hope that is useful for you :)

Answer:

4 is 13.75 and 5 is 14.704

Step-by-step explanation:

Answer:

Similar!

Step-by-step explanation:

Hope this helps!

Answer:

E

Step-by-step explanation:

i just kinda figured it out

Answer:

1 [tex]\frac{2}{3}[/tex]

Step-by-step explanation:

Answer:

1 2/3

Step-by-step explanation:

First, you rewrite 5/8÷3/8 as a multiplication problem: 5/8*8/3. Now you simply multiply both numerators and denominators: 5x8/8x3 which equals 40/24. So your final answer will be 40/24 or 1 16/24 which equals 1 2/3.

Answer:

8 or 9

Step-by-step explanation:

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Answer:

sorry men this is not the answer

Step-by-step explanation

The expected frequency for the fourth category is 8.

To calculate the expected frequency for a particular category, we multiply the total number of observations by the expected proportion for that category. In this case, we have the observed frequencies for all four categories, but we need to determine the total number of observations.

To find the total number of observations, we sum up the observed frequencies for all categories:

Total number of observations = observed frequency of category 1 + observed frequency of category 2 + observed frequency of category 3 + observed frequency of category 4

In your case, the observed frequencies are as follows:

Observed frequency of category 1 = 23

Observed frequency of category 2 = 12

Observed frequency of category 3 = 34

Observed frequency of category 4 = 11

Substituting these values into the equation, we get:

Total number of observations = 23 + 12 + 34 + 11 = 80

Now that we know the total number of observations is 80, we can calculate the expected frequency for the fourth category using the null hypothesis proportions.

Expected frequency for category 4 = Total number of observations * Expected proportion for category 4

Expected proportion for category 4 = 10% = 0.10 (based on the null hypothesis)

Substituting the values into the equation, we have:

Expected frequency for category 4 = 80 * 0.10 = 8

Therefore, the expected frequency for the fourth category, according to the null hypothesis, is 8.

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Complete Question:

The table below lists the observed frequencies for all four categories for an experiment.

Category         Observed Frequency

1                                   23

2                                  12

3                                  34

4                                  11

The null hypothesis for the goodness-of-fit test is that 40% of all elements of the population belong to the first category, 30% belong to the second category, 20% belong to the third category, and 10% belong to the fourth category.

What is the expected frequency for the fourth category?

Answer:

with what??????????????

To guarantee a maximum error of e = 0.01 using the Bisection Method on the interval [-1, 7], approximately 8 iterations are required.

The Bisection Method is an iterative numerical method used to find the root of a continuous function within a given interval. It repeatedly bisects the interval and determines in which subinterval the root lies, based on the sign change of the function. The process continues until the desired accuracy is achieved.

In this case, the interval is [-1, 7] and the maximum error allowed is e = 0.01. The number of iterations required can be determined by finding the number of times the interval can be halved until its length becomes less than or equal to the maximum error.

Initially, the length of the interval is 7 - (-1) = 8. To achieve an error of 0.01, the interval needs to be halved 3 times. After each halving, the length of the interval is reduced by a factor of 1/2. Thus, after 3 iterations, the length becomes 8 * (1/2)^3 = 1.

Since the length of the interval is now less than the maximum error, we can conclude that approximately 8 iterations are required to guarantee a maximum error of 0.01 using the Bisection Method on the interval [-1, 7].

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Answer:

cosine of angle a = 8/17

Step-by-step explanation:

Hello there!

Remember these are the trigonometric ratios

SOC CAH TOA

Sine = Opposite over Hypotenuse (SOH)

Cosine = Adjacent over Hypotenuse (CAH)

Tangent = Opposite over Adjacent (TOA)

And we are asked to find the Cosine of angle A

Remember cosine is adjacent over hypotenuse

Hypotenuse - The longest side

Adjacent - the side that's not the hypotenuse nor the opposite

The adjacent side length of angle A is equal to 8 and the hypotenuse is equal to 17

so the cosine of angle a = 8/17

Answer:

0.95, 2.15

Step-by-step explanation:

cookie-x

ice bar-y

7x+2y=10.95 (*3)

4x+3y=10.25 (*2)

21x+6y=32.85

8x+6y=20.5

21x-8x=32.85-20.5=12.35

13x=12.35

x=0.95

2y=10.95-7*0.95=4.3

y=2.15

Answer C

Step-by-step explanation:

In line 1, the position vector is (3, 2, 4), and the direction vector is (1, 1, 1). By varying the parameter t, we can obtain different points on the line.

In line 2, the position vector is (2, 3, 1), and the direction vector is (4, 4, 1). By varying the parameter s, we can obtain different points on this line.

The vector form and parametric form of the equations for lines 1 and 2 are as follows:

Vector form of line 1:

r = (3, 2, 4) + t(1, 1, 1)

Parametric form of line 1:

x = 3 + t

y = 2 + t

z = 4 + t

Vector form of line 2:

r = (2, 3, 1) + s(4, 4, 1)

Parametric form of line 2:

x = 2 + 4s

y = 3 + 4s

z = 1 + s

The vector form of a line represents the line in terms of a position vector r and a parameter t or s. The position vector r gives a point on the line, and the parameter t or s determines the location of other points on the line.

In line 1, the position vector is (3, 2, 4), and the direction vector is (1, 1, 1). By varying the parameter t, we can obtain different points on the line.

Similarly, in line 2, the position vector is (2, 3, 1), and the direction vector is (4, 4, 1). By varying the parameter s, we can obtain different points on this line.

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Answer:

1.5% of 4000 or 60

Step-by-step explanation:

Answer:

cgal to the store with me for the wounds on the number and the kids to today because I'm so 4

Answer:

the answer is

Step-by-step explanation:

8.0208333333