Algebraic expressions one eighth of m

Answer:

The number 1/3 is a rational number. A rational number is any number that can be expressed as the quotient or fraction p/q of two integers, with the denominator q not equal to zero.

1/3 is not a natural number, whole number, or integer. Natural numbers are the set of positive integers (1, 2, 3, …). Whole numbers are the set of non-negative integers (0, 1, 2, 3, …). Integers are the set of whole numbers and their additive inverses (-3, -2, -1, 0, 1, 2, 3, …).

Step-by-step explanation:

Answer:

25

Step-by-step explanation:

It's what the others said, i'll change it if it's wrong

Based on the description of cost and the equation used, m in the equation would represent $25

m in the equation, y = mx + b, is the gradient. It is the figure that shows how much the cost will change in relation to time or activity.

In other words, m is the variable cost.

The only variable cost above is $25 which is variable because it increases per hour worked. m is there $25.

In conclusion, m is $25.

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Answer:

D) 4 < x < 6

Step-by-step explanation:

The interval is decreasing when it is doing down in value  when x is increasing.

The graph is decreasing over the interval between the values of 4 and 6.

Answer: Option A

Step-by-step explanation:

Answer:

A&C = 68° B = 112°

Step-by-step explanation:

because 180° - 122° = 68°

Systematic sampling offers several advantages. It is relatively easy to implement and eliminates bias that may arise from the subjective selection of participants.

The sampling method described in the scenario is called systematic sampling.

Systematic sampling involves selecting every nth element from a population after randomly selecting a starting point. In this case, the store manager randomly chooses a shopper entering the store as the starting point and then proceeds to interview every 20th person after that initial selection.

Systematic sampling offers several advantages. It is relatively easy to implement and eliminates bias that may arise from the subjective selection of participants. By ensuring a regular interval between selections, systematic sampling provides a representative sample from the population.

However, it's important to note that systematic sampling can introduce a form of bias if there is any periodicity or pattern in the population. For example, if the store experiences a peak in customer traffic during specific time periods, the systematic sampling method might overrepresent or underrepresent certain groups of shoppers.

To minimize this potential bias, the store manager could randomly select the starting point for the systematic sampling at different times of the day or on different days of the week. This would help ensure a more representative sample and reduce the impact of any inherent patterns or periodicities in customer behavior.

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Answer:

Step-by-step explanation:The answer would be 28 because if you divide 16 by 4 you would get 4 and multiply it by 3 and you would get 12 so add 16+12=28

Answer:

this is a positive correlation

Step-by-step explanation:

it is going up so its positive

The equation of a circle with the center at the origin and radius 10 can be determined by using the standard form of the equation of a circle, which is given by the equation x² + y² = r², where (x, y) are the coordinates of any point on the circle, and r is the radius of the circle. If the center of the circle is at the origin,

then the coordinates of the center are (0, 0), and the equation can be written as x² + y² = 10². This equation represents a circle with center at the origin and radius 10. This equation can be used to graph the circle by plotting the points that satisfy the equation.

The circle will be a perfect circle with a radius of 10 units and centered at the origin. It will pass through the points (-10, 0), (0, -10), (10, 0), and (0, 10). These points can be found by solving the equation for x and y. When x = -10, 0, and 10, y will be equal to 0, and when y = -10, 0, and 10, x will be equal to 0. This is how the circle can be graphed using the equation.

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Answer:

45 m2

Step-by-step explanation:

It was the only reasonable answer lol

9x5=45

There are 5040 different permutations of the set {a, b, c, d, e, f, g}.

7! = 7 x 6 x 5 x 4 x 3 x 2 x 1 = 5040

The set {a, b, c, d, e, f, g} has seven elements, so there are 7! (7 factorial) permutations possible. The factorial of a number is the product of all the numbers up to and including that number. In this case,

7! = 7 x 6 x 5 x 4 x 3 x 2 x 1 = 5040.

This means that there are 5040 different permutations of the set

{a, b, c, d, e, f, g}.

A permutation is defined as an arrangement of elements in a specific order. In this case, the elements are {a, b, c, d, e, f, g} and the order can be changed in any way, as long as all elements are included. For example, one possible permutation is bfgdeca.

This is one of the 5040 possible permutations of the set.

As the set contains seven elements, there are 7! (7 factorial) possible permutations. This means that there are 5040 different permutations of the set {a, b, c, d, e, f, g}.

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Answer:

12) A

the values are each devided by three then multiplied by 4

13) C

values are 4 times as big as in the right figure

14) and 15) two thirds of the value in the left figure. the rotation is just to disorient you a lil :D just keep the 90° angle as a reference point

x is option A

and y is option C

The main advantage of an independent measures design is that it reduces the risk of order or practice effects and minimizes the influence of individual differences between participant

An independent measures design, also known as a between-subjects design, is a type of research study in which different groups of participants are used for each condition being tested.

In other words, each participant is only exposed to one condition, and the data from each group is analyzed and compared to determine if there are any significant differences between the groups.

The main characteristics of an independent measures design are:

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If the radius is 5 and the height is 8:

\(A=2\pi rh+2\pi r2=2*\pi*5*8+2*\pi*5^{2}\) ≈ \(408.41 m\)

If the radius is 8 and the height is 5:

\(A=2\pi rh+2\pi r2=2*\pi*8*5+2*\pi*8^{2}\) ≈ \(653.45m\)

Step-by-step explanation:

8x +6° +118° = 180° ( linear pair)

=> 8x = 180°-124°

=> 8x = 56°

=> x = 7°

hope this helps you.

Using separation of variables technique, the solution for the given differential equation is OE. Inly-91-4x-8.

The differential equation to solve is:

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

First, we can factor out the 3y from the denominator to get:

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

Next, we can multiply both sides by y to get:

y y' = 4x - y

Now, we can separate the variables by dividing both sides by (4x - y) y:

dy / (4x - y) = dx / y

Integrating both sides, we get:

ln|4x - y| = ln|y| + C

where C is the constant of integration. We can simplify this to:

ln|4x - y| - ln|y| = C

ln|4x / y - 1| = C

Taking the exponential of both sides, we get:

4x / y - 1 = e^C

Solving for y, we get:

y = 4x / (1 + Ce^x)

To find the constant of integration C, we can use the initial condition y(2) = 10. Substituting x = 2 and y = 10 into the solution, we get:

10 = 8 / (1 + Ce^2)

Solving for C, we get:

C = (8 / 10) - e^4

C = -0.2212

Substituting this value of C into the solution, we get:

y = 4x / (1 - 0.2212e^x)

Simplifying, we get:

y = 4x / (0.7788e^-x - 1)

Thus, the answer is (OE) Inly-91-4x-8.

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The ogive is a line graph that plots the cumulative relative frequency distribution.

An ogive, also known as a cumulative frequency polygon, is a line graph that shows the cumulative frequency distribution of a data set. The cumulative frequency is calculated by adding up the frequencies of each value up to a certain point in the data set.

The cumulative relative frequency is calculated by dividing the cumulative frequency by the total number of observations in the data set. The ogive plots these cumulative relative frequencies against the corresponding values in the data set, usually on the x-axis.

By plotting the cumulative relative frequencies, the ogive shows how the data is distributed over the entire range of values. It can be used to identify patterns in the data, such as whether it is skewed or symmetrical. It is also useful for determining percentiles, as the percentile for a given value can be read directly from the ogive.

Overall, the ogive is a helpful tool for summarizing and visualizing the distribution of a data set, particularly when dealing with large data sets or complex distributions.

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Answer:

0.45

Step-by-step explanation:

You divided 2.25 by 5

Answer: 35 degrees

Step-by-step explanation: 180-145=35

Answer:

Hello! answer: 35 degrees

Step-by-step explanation:

That is forming a supplementary angle meaning it will add up to 180 degrees 180 - 145 = 35 therefore x = 35 HOPE THAT HELPS!

Answer:

1 would be 1320

3 would be 3960

4 would be 5280

Step-by-step explanation:

The cost of 1, 3 and 4 ounces of gold in 2016 was $1,320, $3,960 and $5,280 respectively.

Cost of 2 ounces of gold in 2016 = $2,640

Cost of 1 ounce of gold in 2016 = Cost of 2 ounces of gold in 2016 ÷ 2

= $2,640 ÷ 2

= $1,320

Cost of 3 ounces of gold in 2016 = Cost of 1 ounce of gold in 2016 × 3

= $1,320 × 3

= $3,960

Cost of 4 ounces of gold in 2016 = Cost of 1 ounce of gold in 2016 × 4

= $1320 × 4

= $5,280

Therefore, the cost of 1, 3 and 4 ounces of gold in 2016 are $1,320, $3,960 and $5,280 respectively.

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Therefore, The p-value is the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true. If the p-value is less than the significance level, reject the null hypothesis; otherwise, fail to reject it.

To find the p-value from the t statistic on TI-84, you will need to perform a hypothesis test. Here are the steps:1. Enter your data into the calculator and choose the appropriate test.2. Calculate the t statistic by dividing the sample mean by the standard error.3. Determine the degrees of freedom. This is n-1 for a one-sample t-test or n1+n2-2 for a two-sample t-test. 4. Use the t-distribution table to find the critical value for your test.5. Calculate the p-value using the t-distribution function on the calculator.6. Compare the p-value to the significance level (usually 0.05) to determine whether to reject or fail to reject the null hypothesis.7.

Therefore, The p-value is the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true. If the p-value is less than the significance level, reject the null hypothesis; otherwise, fail to reject it.

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Answer:

Step-by-step explanation:

5. 24

6. 14

7. 45

8. 15

9. 5

10. 5

11. 18

12. 12

13. 8

14. 84

Answer:

18$ per adult, 15 per clild

Step-by-step explanation:

Brainly plzzzz

Answer:

An adults ticket would be $18 and a child's ticket would be $15

Step-by-step explanation:

Answer:

Regular polygon of 10 sides or 10-gon

Explanation:

The angle of rotation symmetry is equal to

θ = 360/n

Where n is the order of rotation. In a regular polygon, the order of rotation for symmetry is the number of sides.

In this case, we can replace θ by 36 degrees and solve the equation for n

36 = 360/n

n = 360/36

n = 10

Therefore, the shape of rotation should be a regular polygon of 10 sides.

Answer:

n=19

Step-by-step explanation:

When data is converted to ranks, the correlation obtained is the Spearman correlation. It assesses the strength and direction of the monotonic relationship between two variables, meaning that it can capture non-linear relationships as well.

The Pearson correlation measures the strength and direction of the linear relationship between two variables, assuming they have a normal distribution. However, when data is not normally distributed, it may be converted to ranks, which allows for a non-parametric correlation measure to be used. The Spearman correlation is a non-parametric measure of correlation that uses the ranks of the data rather than the actual values.

In addition to the Spearman correlation, there are other non-parametric correlation measures that can be used when data is converted to ranks. The point-biserial correlation is used when one variable is dichotomous and the other is continuous and ranked. The phi coefficient is used when both variables are dichotomous. However, even when data is converted to ranks, the correlation measure is still commonly referred to as the Pearson correlation, as it is the same formula used with ranked data as with non-ranked data. However, it is important to recognize that the interpretation and assumptions of the correlation measure may differ depending on the type of data used.

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1. the mean (E(X)) of the random loss amount prior to the deductible is  62.5

2. the variance \((Var(Y^L))\) of the insurance payment per loss is:

\(Var(Y^L)\) ≈ 1584.1875

3.  the mean \((E(Y^P))\) of the insurance payment per payment is approximately 45.36, and the variance \((Var(Y^P))\) is approximately 1965.071.

To calculate the mean and variance of the random loss amount prior to the application of the deductible, we need to consider the probability density function (PDF) provided.

1. Mean and Variance of Random Loss Amount (X) prior to the Deductible:

The PDF is defined as:

f(x) = 0.008,     0 < x ≤ 75

      0.016,    75 < x < 100

The mean (E(X)) is calculated as follows:

E(X) = ∫[x * f(x)] dx

For 0 < x ≤ 75:

E(X) = ∫[x * 0.008] dx

    = 0.008 * [x² / 2] | from 0 to 75

    = 0.008 * [(75² / 2) - (0² / 2)]

    = 0.008 * (5625 / 2)

    = 0.008 * 2812.5

    = 22.5

For 75 < x < 100:

E(X) = ∫[x * 0.016] dx

    = 0.016 * [x² / 2] | from 75 to 100

    = 0.016 * [(100² / 2) - (75² / 2)]

    = 0.016 * (5000 / 2)

    = 0.016 * 2500

    = 40

Therefore, the mean (E(X)) of the random loss amount prior to the deductible is:

E(X) = 22.5 + 40

    = 62.5

The variance (Var(X)) is calculated as follows:

Var(X) = ∫[(x - E(X))²* f(x)] dx

For 0 < x ≤ 75:

Var(X) = ∫[(x - 22.5)² * 0.008] dx

      = 0.008 * [(x - 22.5)³ / 3] | from 0 to 75

      = 0.008 * [(75 - 22.5)³ / 3]

      = 0.008 * [(52.5)³ / 3]

      ≈ 432.1875

For 75 < x < 100:

Var(X) = ∫[(x - 40)² * 0.016] dx

      = 0.016 * [(x - 40)³ / 3] | from 75 to 100

      = 0.016 * [(100 - 40)³ / 3]

      = 0.016 * [(60)³ / 3]

      = 1152

Therefore, the variance (Var(X)) of the random loss amount prior to the deductible is:

Var(X) = 432.1875 + 1152

      ≈ 1584.1875

2. Mean and Variance of Insurance Payment per Loss \((Y^L)\):

The insurance payment per loss is calculated as follows:

\(Y^L\) = X - 40 (deductible)

The mean \((E(Y^L))\) of the insurance payment per loss is:

\(E(Y^L)\) = E(X - 40)

      = E(X) - 40

      = 62.5 - 40

      = 22.5

The variance \((Var(Y^L))\) of the insurance payment per loss is equal to the variance of X since the deductible does not affect the variance.

Therefore, the variance \((Var(Y^L))\) of the insurance payment per loss is:

\(Var(Y^L)\) ≈ 1584.1875

3. Mean and Variance of Insurance Payment per Payment \((Y^P)\):

The insurance payment per payment is equal to the insurance payment per loss \((Y^L)\) when there is a loss (X) and 0 otherwise.

The mean \((E(Y^P))\) of the insurance payment per payment is equal to the probability of a loss multiplied by the mean payment per loss:

\(E(Y^P) = P(X > 40) * E(Y^L)\)

For 0 < x ≤ 75:

P(X > 40) = ∫[f(x)] dx | from 40 to 75

         = 0.008 * (75 - 40)

         = 0.28

For 75 < x < 100:

P(X > 40) = ∫[f(x)] dx | from 40 to 100

         = 0.016 * (100 - 40)

         = 0.96

\(E(Y^P)\) = (0.28 * 22.5) + (0.96 * 22.5)

      ≈ 23.76 + 21.6

      ≈ 45.36

The variance \((Var(Y^P))\) of the insurance payment per payment is equal to the variance of \(Y^L\) multiplied by the probability of a loss:

\(Var(Y^P) = P(X > 40) * Var(Y^L)\)

Var(Y^P) = (0.28 * 1584.1875) + (0.96 * 1584.1875)

        ≈ 444.372 + 1520.699

        ≈ 1965.071

Therefore, the mean \((E(Y^P))\) of the insurance payment per payment is approximately 45.36, and the variance \((Var(Y^P))\) is approximately 1965.071.

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Since t^11 approaches infinity faster than t, this limit is infinite, which means that the integral (and thus the series) diverges. Therefore, we can say that the series diverges.

Hi! Since f(x) = 13x^10 is continuous, positive, and decreasing on the interval [1, infinity), we can evaluate the convergence or divergence of the series. In this case, the series is given by:

∑(from n=1 to infinity) 13n^10

To determine if this series converges or diverges, we can apply the Integral Test. The integral of f(x) from 1 to infinity is:

∫(from 1 to infinity) 13x^10 dx

Unfortunately, this integral diverges as it represents the area under the curve of a polynomial with a positive exponent, which grows without bound. Therefore, the series also diverges.

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