if f(x)=2x+3, what is f(-2)​

Answer:

X=12 have a good day!

Step-by-step explanation:

hope this helped

The proportion of a normal distribution located between z = .50 and z = -.50 will be 38.2%.

We have,

A normal distribution located between z = 0.50 and z = -0.50,

So,

Now,

From the Z-score table,

We get,

The Probability corresponding to the Z score of -0.50,

i.e.

P(-0.50 < X < 0) = 0.191,

And,

The Probability corresponding to the Z score of -0.50,

i.e.

P(0 < X < 0.50) = 0.191,

Now,

The proportion of a normal distribution,

i.e.

P(Z₁ < X < Z₂) = P(Z₁ < X < 0) + P(0 < X < Z₂)

Now,

Putting values,

i.e.

P(-0.50 < X < 0.50) = P(-0.50 < X < 0) + P(0 < X < 0.50)

Now,

Again putting values,

We get,

P(-0.50 < X < 0.50) = 0.191 + 0.191

On solving we get,

P(-0.50 < X < 0.50) = 0.382

So,

We can write as,

P(-0.50 < X < 0.50) = 38.2%

So,

The proportion of a normal distribution is 38.2%.

Hence we can say that the proportion of a normal distribution located between z = .50 and z = -.50 will be 38.2%.

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Answer:

2%

Step-by-step explanation:

m = 100(.5)^(1/35) = 98       so   2 % is gone after 1 day

The two-sample z-test statistic for evaluating the null hypothesis that the percentage of students who support capital punishment did not change from 1970 to 2005 is -4.08 (rounded to two decimal places).

To calculate the two-sample z-test statistic, we need to compare the proportions of students who support capital punishment in 1970 and 2005. The null hypothesis states that the percentage of students who support capital punishment did not change.

Let p1 be the proportion of students who support capital punishment in 1970, and p2 be the proportion in 2005. We can calculate the sample proportions as p1 = 590/1000 = 0.59 and p2 = 350/1000 = 0.35.

The formula for the two-sample z-test statistic is given by z = (p1 - p2) / sqrt((p(1 - p)(1/n1 + 1/n2))), where p is the pooled proportion and n1 and n2 are the sample sizes.

To calculate p, we compute the pooled proportion as p = (p1n1 + p2n2) / (n1 + n2) = (0.591000 + 0.351000) / (1000 + 1000) = 0.47.

Substituting the values into the formula, we have z = (0.59 - 0.35) / sqrt((0.47*(1 - 0.47)(1/1000 + 1/1000))) = -4.08.

Therefore, the two-sample z-test statistic for evaluating the null hypothesis is -4.08 (rounded to two decimal places).

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Answer:

I think the answer is C

Step-by-step explanation:

If you have a normal ginger bread cookie, its full size would be 100%. So, if you add the first 25%, 1.25%

The expression best describes the new length of the cookie will be 1.25y.

Expression in maths is defined as the collection of the numbers variables and functions by using signs like addition, subtraction, multiplication and division.

Given that:-

The initial length of the cookie is y after baking the length is increased by 25%

=   y  +  25%y

=   y   +  ( 25 / 100 ) y

=   y  +  0.25 y

=  1.25 y

Therefore the expression best describes the new length of the cookie will be 1.25y.

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Answer:

0.000285714286 or unless you ment 280 divided by 0.08 cuz thats a diferent question and would be 3500

Given half-cup of milk. if we find how many  milliliters are there in this cup we get it approximately equal to 120 milliliters.

In cooking and baking, cup measurements are commonly used. However, it's important to note that cup measurements can vary slightly depending on the country or region. In the United States, a standard cup measurement is equal to 240 milliliters.

A half-cup is exactly half of this measurement, which means it would be approximately equal to 240/2 = 120 milliliters. Therefore, option C, 120, is the closest approximation to the number of milliliters contained in a half-cup of milk. It's worth noting that for more precise measurements, it's always advisable to use a kitchen scale or measuring cup with milliliter markings.

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Each model should be produced on a weekly basis to maximize net profit is $75,900.

What is Net profit?

In both business and accounting, net income or profit is an entity's revenue less cost of goods sold, costs, depreciation and amortisation, interest, and taxes for a certain accounting period.

As given,

Number of products sold:

T ≥ 1.5G

Maximize Profit Z = 150T + 130G

Labor Constraint:

Labor hours Available:

Production Department:

Number of labor hours available per day = 58 × 7 = 406

Number of days in a week = 5

Number of lobor ours available per week = 406 × 5 = 2030

Assembly Department:

Number of labor hours available per day = 25 × 7 = 175

Number of days in a week = 5

Number of labor hours available per week = 175 × 5 = 875.

Labor hours Required:

Labor hours required for G1 model:

Labor hours required at Production department = 3.5G

Labor hours required at assembly department = 2G

Labor hours required for T1 model:

Labor hours required at Production department = 4T

Labor hours required at Assembly department = 1.5T

Total labor hours required at Production department = 3.5G + 4T

Total labor hours required at Assembly department = 2G + 1.5T.

Constraint:

Labor hours required ≤ Labor hours Available.

Production department Labor constraint

3.5G + 4T ≤ 2030

Assembly department Labor constraint:

2G + 1.5T ≤ 875

The function:

Maximum Profit Z = 150T +130G

Constraint:

3.5G +4T ≤ 2030

2G + 1.5T ≤ 875

T ≥ 1.5G

Suppose that for example:

10.5G +12T = 6090

 16G + 12T = 7000

Solve both equations simultaneously,

5.5G = 7000 - 6090

5.5G = 910

    G = 910/5.5

    G = 363

Since, T > G

Hence,

T = 363,

G = 165

Calculate Profit:

150T + 130G = 150 × 363 + 130 × 165

                     = 54450 + 21450

                     = 75900

Hence, each model should be produced on a weekly basis to maximize net profit is $75,900.

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Answer:

4 if you are subtracting, 32 if you are multiplying, 12 if you are adding, and 2 if you are dividing.

Step-by-step explanation:

Hope this helps.

Answer: 100 dollars

Step-by-step explanation: If he has 50 dollars and the bike costs 150 he need 100 more dollars to get 150 dollars

a) The 90% confidence interval for the population proportion is approximately (0.7777, 0.8423).

b) The 95% confidence interval for the population proportion is approximately (0.7737, 0.8463).

To calculate the confidence intervals for the population proportion, we can use the formula:

Confidence Interval = sample proportion ± margin of error

The margin of error can be calculated using the formula:

Margin of Error = critical value * standard error

where the critical value is determined based on the desired confidence level and the standard error is calculated as:

Standard Error = \(\sqrt{((p * (1 - p)) / n)}\)

Given that the sample proportion (p) is 0.81 and the sample size (n) is 500, we can calculate the confidence intervals.

a. 90% Confidence Interval:

To find the critical value for a 90% confidence interval, we need to determine the z-score associated with the desired confidence level. The z-score can be found using a standard normal distribution table or calculator. For a 90% confidence level, the critical value is approximately 1.645.

Margin of Error = \(1.645 * \sqrt{(0.81 * (1 - 0.81)) / 500)}\)

≈ 0.0323

Confidence Interval = 0.81 ± 0.0323

≈ (0.7777, 0.8423)

Therefore, the 90% confidence interval for the population proportion is approximately (0.7777, 0.8423).

b. 95% Confidence Interval:

For a 95% confidence level, the critical value is approximately 1.96.

Margin of Error = \(1.96 * \sqrt{(0.81 * (1 - 0.81)) / 500)}\)

≈ 0.0363

Confidence Interval = 0.81 ± 0.0363

≈ (0.7737, 0.8463)

Thus, the 95% confidence interval for the population proportion is approximately (0.7737, 0.8463).

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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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The statement 'when finding a minimum in a linear programming problem, it is possible to find more than one minimum value' is True.

In this question, we have been given a statement - 'when finding a minimum in a linear programming problem, it is possible to find more than one minimum value.'

We need to state whether it is true or false.

We know that, the minimum value of the objective function Z = ax + by in a linear programming problem can also occur at more than one corner points of the feasible region.

Therefore, when finding a minimum in a linear programming problem, it is possible to find more than one minimum value.

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Answer:

Step-by-step explanation:

Given two congruent circles,  ⊙A ≅ ⊙V. The correct congruency statements are arc BE ≅ arc ZX and BE ≅ ZX.

Congruence is a term that refers to objects that are the same shape and same size or dimension.

In this problem, two congruent circles are given as in the attached picture.

Notice that:

 ∠BAE ≅ ∠ZVX

Hence,

BE ≅ ZX

Δ BAE ≅ ΔZVX

arc BE ≅ arc ZX

arc CD ≅ arc YW

∠DAB ≅ ∠XVY

arc DE ≅ arc ZY

arc WX ≅ arc BC

Hence, the correct congruency statements from the list of options are: arc BE ≅ arc ZX and BE ≅ ZX.

The picture in your question was missing. Most likely it was like on the attached picture.

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Answer:

B. BE = ZX and F. BE = ZX

Step-by-step explanation:

edg 23

a. The critical value for this test is 103.525

b. The power of this test is 0.0001

c. The probability of committing a Type II Error on this test is 0.9999.

a) Using a standard normal distribution table or calculator, we can find the Zα value for α = 0.05. The Zα value for α = 0.05 is approximately 1.645.

Plugging in the values into the formula, we get:

Critical value  = 100 + 1.645 * (15 / √49)

Critical value = 100 + 1.645 * (15 / 7)

Critical value ≈ 100 + 1.645 * 2.143

Critical value ≈ 100 + 3.525

Critical value ≈ 103.525

b) Using the Z-score formula:

Z = (x - μ) / (σ / √n)

Z = (103.525 - 95) / (15 / √49)

Z = 8.525 / (15 / 7)

Z ≈ 8.525 / 2.143

Z ≈ 3.969

Using a standard normal distribution table or calculator, we can find the probability to the right of Z = 3.969. The power is equal to that probability.

The power ≈ 1 - 0.9999

The power ≈ 0.0001

c) The probability of committing a Type II Error is equal to 1 - power. In this case, the probability of committing a Type II Error is approximately:

= 1 - 0.0001

= 0.9999.

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The Miller-Rabin test is a probabilistic primality test that is based on the observation that if a number is prime, certain congruence conditions should hold.

By testing multiple random values, we can determine with a high level of confidence whether a number is prime or composite.

The Miller-Rabin primality test is used to determine if a number is prime or composite. It is based on the observation that if a number, let's call it "p," is prime and satisfies the condition x^2 ≡ 1 mod p, then x ≡ ±1 mod p.

This means that if x is congruent to -1 mod p or p-1 mod p, it indicates that p is likely to be prime.

To use the Miller-Rabin test, we select a number, let's call it "n," to test for primality. We can choose a random number between 2 and n-2.

If n is prime, then for any x between 2 and n-2, the condition x^2 ≡ 1 mod n should hold. However, if n is composite, there will be values of x that do not satisfy this condition.

Here's a step-by-step explanation of the Miller-Rabin primality test:

1. Select a number, n, to test for primality.

2. Choose a random number, a, between 2 and n-2

3. Compute b = a^k mod n, where k = (n-1)/2.

4. If b ≡ 1 mod n or b ≡ -1 mod n, go to step 7.

5. For i = 1 to i = s-1 (where s is a parameter that determines the accuracy of the test):
  - Compute b = b^2 mod n.
  - If b ≡ -1 mod n, go to step 7.
  - If b ≡ 1 mod n, go to step 6.
6. Return "n is composite."

7. Repeat steps 2-6 for a different random number, a.

8. If all the tests pass without finding n to be composite, return "n is probably prime."

The Miller-Rabin primality test can provide a high level of confidence in determining if a number is prime.

By repeating the test with different random values, we can increase the probability of correctly identifying a composite number.

However, it is important to note that the Miller-Rabin test is probabilistic, meaning there is a small chance of falsely identifying a composite number as prime (known as a "false positive").

In summary, the Miller-Rabin test is a probabilistic primality test that is based on the observation that if a number is prime, certain congruence conditions should hold.

By testing multiple random values, we can determine with a high level of confidence whether a number is prime or composite.

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In terms of relative growth rate Exponential growth is characterized by a constant relative growth rate.

Exponential growth is the process of increasing quantity over time. Occurs when the instantaneous rate of change of a quantity over time is proportional to the quantity itself. The exponential growth model has the form

y (t) = C eᵏᵗ, where k is the rate constant.

Relative Growth Rate:Relative growth rate (RGR) is the rate of growth relative to size. That is, the rate of growth per unit time relative to the size at that point in time and y'(t)/y(t) is the relative growth rate of a function y at time t.

1/y dy/dt = 1/y d(C eᵏᵗ)/dt

= 1/y(kC eᵏᵗ)

= 1/y ( ky) ( since, y (t) = C eᵏᵗ)

= k

Therefore a constant relative growth rate.

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Complete question:

In terms of relative growth rate, what is the defining property of exponential growth? Choose the correct answer below.

A. The relative growth rate at time t is the slope of the exponential function at time t.

B. dy dt If y represents a population, then the relative growth rate can be represented by dy/dt

C. The relative growth rate is proportional to the size of the population

D. The relative growth rate is constant.

Answer:

Kay has 49 pencils

Step-by-step explanation:

Answer:

Sample Response: 13    

Step-by-step explanation:

4 is equal to 1.75. I would plot 1.5 and 1.75 between 1 and 2, but 1.75 would be closer to 2. Since 1.75 is further to the right, it is greater than 1.5.

Answer:

13

4

is equal to 1.75. I would plot 1.5 and 1.75 between 1 and 2, but 1.75 would be closer to 2. Since 1.75 is further to the right, it is greater than 1.5.

Step-by-step explanation:

The 98% confidence interval for the population mean (μ) is approximately (2.711, 3.009).

1: Identify the given data

Sample size (n) = 150 students

Sample mean (x) = 2.86

Population standard deviation (σ) = 0.78

Confidence level = 98%

2: Find the critical z-value (z*) for a 98% confidence level

Using a z-table or calculator, you'll find that the critical z-value for a 98% confidence level is 2.33 (approximately).

3: Calculate the standard error (SE)

SE = σ / √n

SE = 0.78 / √150 ≈ 0.064

4: Calculate the margin of error (ME)

ME = z* × SE

ME = 2.33 × 0.064 ≈ 0.149

5: Construct the confidence interval

Lower limit = x - ME = 2.86 - 0.149 ≈ 2.711

Upper limit = x + ME = 2.86 + 0.149 ≈ 3.009

The 98% confidence interval is approximately (2.711, 3.009).

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Answer:

3*3*3-1*1

Step-by-step explanation:

Answer:

7

Step-by-step explanation:

3x3=9

1x2=2

so 9-2=7

Answer:

6 total vertices shown in the picture.

Answer:

XY = 13 cm

Step-by-step explanation:

Area of a triangle formula:

area = base × height / 2

a = bh / 2

Plug numbers into equation:

32.5 = b × 5 / 2

Multiply both sides by 2 to isolate the variable

65 = b × 5

Divide both sides by 5 to isolate the variable

13 = b

Check your work:

32.5 = 13 × 5 / 2

32.5 = 65 / 2

32.5 = 32.5

Correct

Answer:

13

Step-by-step explanation:

Area=½×b×h

32.5=½×b×5

32.5=5/2b

To get be multiply each side by reciprocal of 5/2 which is 2/5

b =13

Answer:

\(3x^4+4x^3+8x\)

Step-by-step explanation:

\((x^2+2x)(3x^2-2x+4)\\\\(x^2)(3x^2)+(x^2)(-2x)+(x^2)(4)+(2x)(3x^2)+(2x)(-2x)+(2x)(4)\\\\3x^4-2x^3+4x^2+6x^3-4x^2+8x\\\\3x^4+4x^3+8x\)

Answer:

C, my friend. Trust the BlueDragon

Step-by-step explanation:

30% of $30 is 9, $30-$9 is $21.00

He saved $9.00

Answer:

no solution

Step-by-step explanation:

- x + 6y = 9 → (1)

- 4x + 24y = 48 → (2)

multiplying (1) by - 4 and adding to (2) will eliminate x and y

4x - 24y = - 36 → (3)

add (2) and (3) term by term

0 + 0 = 12

0 = 12 ← false statement

this false statement indicates the system has no solution

The electron domain charge cloud geometry of \(BrF_5\) is trigonal bipyramidal.

To determine the electron domain charge cloud geometry of \(BrF_5\), we need to examine the number of electron domains around the central atom (Br).

\(BrF_5\) consists of one central bromine atom (Br) surrounded by five fluorine atoms (F). Each bond and lone pair of electrons represents an electron domain.

In \(BrF_5\), there are five bonding pairs (Br-F) and no lone pairs around the central bromine atom. Therefore, the total number of electron domains is five.

Based on this information, the electron domain charge cloud geometry of \(BrF_5\) is trigonal bipyramidal.

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