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Hunter assumed he would only get 64


problems correct on his test, but he


actually got 78 correct. What was his


percent error?


Hint: Percent error =


Prediction - Actual


Actual


x 100


Round to the nearest percent.


[? ]%


Enter

Answer:

jessie

Step-by-step explanation:

because math is math

The solution for the given equation is -15/7.

The given equation is \(\frac{2}{5}x-\frac{3}{2} =\frac{5}{2}x+6\).

In mathematics, an equation is a formula that expresses the equality of two expressions, by connecting them with the equals sign =.

The given equation can be solved as follows:

\(\frac{2}{5}x-\frac{3}{2} =\frac{5}{2}x+6\)

⇒ \(\frac{2}{5}x-\frac{5}{2}x=6-\frac{3}{2}\)

⇒ \(\frac{4}{10}x-\frac{25}{10}x=\frac{12}{2} -\frac{3}{2}\)

⇒ (-21/10) x =9/2

⇒ x = 9/2 × (-10/21)

⇒ x = 3/1 × (-5/7)

⇒ x = -15/7

Therefore, the solution for the given equation is -15/7.

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To reduce bias when conducting an experiment, it is important to employ methods that minimize the influence of confounding factors and ensure the results are representative of the population.

Randomization plays a key role in reducing bias by eliminating systematic patterns in treatment assignment. By randomly assigning treatments, all types of members in the population have an equal chance of receiving each treatment, which helps mitigate bias. Additionally, choosing a random sample from the population enhances the generalizability of the results and reduces bias that could arise from selecting a non-representative sample.

The researcher choosing who gets which treatment can introduce bias because it allows for potential bias in treatment allocation based on preconceived notions or preferences.

Random assignment of treatments helps reduce bias by ensuring that the treatments are assigned without any systematic pattern. This allows for equal representation of all types of individuals in the population, minimizing potential confounding variables.

Assigning treatments in a way that ensures all results in the experiment are the same can lead to bias as it disregards individual differences and does not account for potential variations and interactions between treatments and participants.

Choosing a random sample from the population is important to reduce bias as it ensures that every individual in the population has an equal chance of being selected, increasing the likelihood of a representative sample. A random sample helps minimize selection bias, where certain groups are over- or under-represented, thus improving the generalizability of the findings to the larger population.

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The correct answer is that the probability of a cash flow being between $16,000 and $19,000 is approximately 18.59%.

To calculate the probability of a cash flow being between $16,000 and $19,000, we can use the standard deviation and assume a normal distribution.

We are given that the average cash flow is $14,000 with a standard deviation of $5,000. These values are necessary to calculate the probability.

The probability of a cash flow falling within a certain range can be determined by converting the values to z-scores, which represent the number of standard deviations away from the mean.

First, we calculate the z-score for $16,000 using the formula: z = (x - μ) / σ, where x is the cash flow value, μ is the mean, and σ is the standard deviation. Plugging in the values, we get z1 = (16,000 - 14,000) / 5,000.

z1 = 2,000 / 5,000 = 0.4.

Next, we calculate the z-score for $19,000: z2 = (19,000 - 14,000) / 5,000.

z2 = 5,000 / 5,000 = 1.

Now that we have the z-scores, we can use a standard normal distribution table or calculator to find the corresponding probabilities.

Subtracting the probability corresponding to the lower z-score from the probability corresponding to the higher z-score will give us the probability of the cash flow falling between $16,000 and $19,000.

Looking up the z-scores in a standard normal distribution table or using a calculator, we find the probability for z1 is 0.6554 and the probability for z2 is 0.8413.

Therefore, the probability of the cash flow being between $16,000 and $19,000 is 0.8413 - 0.6554 = 0.1859, which is approximately 18.59%.

So, the correct answer is that the probability of a cash flow being between $16,000 and $19,000 is approximately 18.59%.

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The probability of a cash flow between $16,000 and $19,000 is approximately 18.59%.

To calculate the probability of a cash flow being between $16,000 and $19,000, we can use the standard deviation and assume a normal distribution.

We are given that the average cash flow is $14,000 with a standard deviation of $5,000. These values are necessary to calculate the probability.

The probability of a cash flow falling within a certain range can be determined by converting the values to z-scores, which represent the number of standard deviations away from the mean.

First, we calculate the z-score for $16,000 using the formula: z = (x - μ) / σ, where x is the cash flow value, μ is the mean, and σ is the standard deviation. Plugging in the values, we get z1 = (16,000 - 14,000) / 5,000.

z1 = 2,000 / 5,000 = 0.4.

Next, we calculate the z-score for $19,000: z2 = (19,000 - 14,000) / 5,000.

z2 = 5,000 / 5,000 = 1.

Now that we have the z-scores, we can use a standard normal distribution table or calculator to find the corresponding probabilities.

Subtracting the probability corresponding to the lower z-score from the probability corresponding to the higher z-score will give us the probability of the cash flow falling between $16,000 and $19,000.

Looking up the z-scores in a standard normal distribution table or using a calculator, we find the probability for z1 is 0.6554 and the probability for z2 is 0.8413.

Therefore, the probability of the cash flow being between $16,000 and $19,000 is 0.8413 - 0.6554 = 0.1859, which is approximately 18.59%.

So, the correct answer is that the probability of a cash flow being between $16,000 and $19,000 is approximately 18.59%.

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Answer:

the midpoint would be (-2,-2)

Step-by-step explanation:

Answer:

y=85

Step-by-step explanation:

Answer:

The value of x is 5x that the value of X in my oppion.

Step-by-step explanation:

If the value of determinant a is 3, determinant b is 5 then the value of determinant ab is 15.

Given that the value of determinant a is 3, determinant b is 5.

We are required to find the value of determinant ab.

Determinant of a matrix is the scalar value computed for a given square matrix.It means the matrix which is not square does not have a determinant value.  It is denoted by IAI.

We know that,

IaI*IbI=IabI

So we have to just put the values in the above formula to get the determinant of ab.

IabI=3*5

=15

Hence if the value of determinant a is 3, determinant b is 5 then the value of determinant ab is 15.

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Therefore, the rank of matrix 'a' in this case would be 5.

To find the rank of a matrix, we need to perform row reduction to obtain its row echelon form (REF) or reduced row echelon form (RREF). However, since the matrix 'a' is not provided, I cannot perform the calculations or determine its rank.

The rank of a matrix is equal to the number of non-zero rows in its row echelon form or reduced row echelon form. If the system of equations 'ax = 0' has a two-dimensional solution space, it means that the rank of matrix 'a' is less than the number of columns (6) but greater than 4 (since the solution space is two-dimensional).

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The linear equation that is represented by the given table is:

y = -3*x + 4

The relation on the table seems to be a linear equation.

Remember that a linear equation is written in general form as:

y = a*x + b

Where a is the slope and b is the y-intercept.

On the table we can see the point (0, 4), which means that the y-intercept (the value of y when x = 0) is b= 4, then we can replace that in the general linear equation above to get:

y = a*x + 4

To find the value of a, we can use one of the other pairs on the table, for example if we use (1, 1), then we will get.

1 = a*1 +  4

1 = a + 4

1 - 4 = a

-3 = a

Then we conclude that the linear equation represented in the table is:

y = -3x + 4

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the answer is 0.6

the force would be 6.0, and acceleration would be 10 pretty much you divided force and acceleration to find your mass

m=f/a

m=6.0/10

m=0.6

Answer:

A; B; D; F; G

Step-by-step explanation:

Standard form: Ax+By=C

The answer is 64 degrees

Answer:

10 and 11

Step-by-step explanation:

If I am incorrect in my reasoning, please let me know so that I can plan better for my future answers. Have an amazing day.

B. The period of y = 2 sin(x) is π.
F. The amplitude of y = 2 sin(x) is 2.

In physics, engineering, and mathematics, amplitude refers to the maximum displacement or distance of a wave from its undisturbed position. It is a measure of the strength or intensity of a wave.

For example, in the case of a sound wave, the amplitude corresponds to the maximum pressure variation caused by the sound wave. The greater the amplitude of the sound wave, the louder the sound.

In the case of an electromagnetic wave, such as light, the amplitude corresponds to the maximum electric or magnetic field strength of the wave. The greater the amplitude of the light wave, the brighter the light.

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Answer:

27

Step-by-step explanation:

We substitute all the variables to get:

(5)2 + 2(8) ÷ 2 + 3(3)

We multiply everything to get

10 + 16 ÷ 2 + 9

Divide:

10 + 8 + 9

Add:

18 + 9

27

Answer:

42

Step-by-step explanation:

We plug in the given values into the equation:

The order of operations is:

Parentheses

Exponents

Multiplication & Division (whichever comes first)

Addition & Subtraction (whichever comes first)

\(5^{2} +2(8)\div2+3(3)\)

\(25+16\div2+9\)

Remember that division comes before addition

\(25+8+9\)

\(42\)

Answer:

1 7/8

Step-by-step explanation:

3/8 * 5/1 = 15/8

<-- First multiply 3/8 by 5

----------------------------------------------

15/8 = 1 with a remainder of 7

<-- Then convert 15/8 to a mixed number by dividing 15 by 8

15/8 = 1 7/8

We can use the given points to solve.

Slope formula: y2-y1/x2-x1

3-(-3)/-4-2

6/-6

-1

Best of Luck!

(2, -3) and (-4, 3)

The slope of the line through (2, -3) and (-4, 3).

y2 - y1 / x2 - x1

3 + 3 / -4 - 2

= 6 / -6

= -1

-1

The sample space refers to the set of all possible outcomes of a random experiment, while the support of a probability distribution represents the set of outcomes that have a non-zero probability assigned to them.

In probability theory, the sample space is the collection of all possible outcomes of a random experiment or process. It represents the set of all conceivable results that could occur. For example, when flipping a fair coin, the sample space consists of two outcomes: "heads" and "tails". In more complex experiments, the sample space can be much larger and may include combinations of outcomes.

On the other hand, the support of a probability distribution refers to the subset of the sample space where the probability assigned by the distribution is non-zero. It represents the specific outcomes that are deemed possible or likely according to the probability distribution. In other words, the support is the range of values for which the probability density function (PDF) or probability mass function (PMF) is positive. The support can vary depending on the specific distribution being used.

To illustrate this concept, consider a fair six-sided die. The sample space consists of the numbers 1 to 6. If we assume a fair and unbiased die, the probability distribution assigns equal probabilities to each outcome. Therefore, the support of this distribution is the entire sample space, as all outcomes have a non-zero probability assigned to them. However, if we consider a biased die that favors even numbers, the support of the probability distribution would only include the even numbers in the sample space, while the odd numbers would have a probability of zero.

In summary, the sample space encompasses all possible outcomes of a random experiment, while the support of a probability distribution represents the subset of outcomes that have a non-zero probability assigned to them.

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The combination of the expression is \(5\sqrt{5} + \sqrt{3} + 10\)

We are given that;

The expression= 1/3√45- 1/2√12 +√20+2/3√27 3 + 4 + 3

To combine the expressions, we need to simplify the radicals and find the common factors.

Rewrite the radicals as fractional exponents

= \(\frac{1}{3}(45)^{\frac{1}{2}} - \frac{1}{2}(12)^{\frac{1}{2}} + (20)^{\frac{1}{2}} + \frac{2}{3}(27)^{\frac{1}{2}} + 3 + 4 + 3\)

Simplify the coefficients and combine the like terms:

\(=5\sqrt{5} + \sqrt{3} + 10\)

Therefore, the expression will be \(5\sqrt{5} + \sqrt{3} + 10\).

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We can see that there is at least one row where all premises are true (row 7), but the conclusion is false. Therefore, the argument is invalid.

To construct a symbolic model of the argument, let's define the following symbols:

P: Jayco qualifies as a small business.

Q: Jayco has sales that are not large enough to influence its environment.

R: Jayco is privately owned by a small group of individuals.

Now we can represent the statements in symbolic form:

Premise 1: P ≡ (Q • R)

Premise 2: ~P

Conclusion: ~R

To determine if the argument is valid or invalid, we can construct a truth table:

| P | Q | R | P ≡ (Q • R) | ~P | ~R |

|---|---|---|-------------|----|----|

| T | T | T |      T      |  F |  F |

| T | T | F |      F      |  F |  T |

| T | F | T |      T      |  F |  F |

| T | F | F |      F      |  F |  T |

| F | T | T |      F      |  T |  F |

| F | T | F |      T      |  T |  T |

| F | F | T |      F      |  T |  F |

| F | F | F |      T      |  T |  T |

From the truth table, we can see that there is at least one row where all premises are true (row 7), but the conclusion is false. Therefore, the argument is invalid.

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48 plastic bandages should a small kit have

A ratio is an ordered pair of numbers a and b, written a / b where b does not equal 0.

Given that the ratio of fabric bandages to plastic bandages in each kit is 3 to 9

A small kit has 16 fabric bandages then we have to find the number of plastic bags.

Let x be the number of plastic bags for 16 fabric bandages.

3/9=16/x

Apply cross multiplication

3x=16×9

3x=144

Divide both sides by 3

x=48.

Hence, 48 plastic bandages should a small kit have

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Answer:

4.

Step-by-step explanation:

7n - 12 = 16

7n = 16 + 12 = 28

Since 7n = 28, n = 28 / 7 = 4.

Answer:

x = - 3

Step-by-step explanation:

g(x) = 4x + 1...... (1)

g(x) = -11.... (2)

From equations (1) & (2)

-11 = 4x + 1

-11 - 1 = 4x

-12 = 4x

-12/4 = x

-3 = x

x = - 3

The equation of the regression line that predicts carbon dioxide emissions from GDP is y = 166.9x + 115.725. This regression line provides a simplified representation of the relationship between GDP and carbon dioxide emissions, allowing for predictions and further analysis of their association.  

The regression line equation is in the form of y = mx + b, where y represents the dependent variable (carbon dioxide emissions) and x represents the independent variable (GDP). The slope of the regression line, denoted by m, indicates the rate at which carbon dioxide emissions change with respect to GDP. In this case, the slope is 166.9, meaning that for every unit increase in GDP, carbon dioxide emissions are predicted to increase by 166.9 units.

The y-intercept, represented by b, gives the value of the dependent variable (carbon dioxide emissions) when the independent variable (GDP) is zero. In this equation, the y-intercept is 115.725, implying that when GDP is zero, the predicted carbon dioxide emissions are 115.725 units. By substituting the given values into the equation, y = 166.9x + 115.725, we can estimate carbon dioxide emissions based on a given GDP value.

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The estimated total time for all five pools is approximately 13.85 hours.

To estimate the time required to install the fifth pool using the learning curve, we can use the formula:

Time for nth unit = Time for first unit * (n^b)

Where:

Time for nth unit is the estimated time to install the nth pool

Time for first unit is the estimated time to build the first pool (30 hours)

n is the number of units (in this case, n = 5 for the fifth pool)

b is the learning curve exponent (85% learning rate corresponds to b = log(0.85) / log(2))

Let's calculate the estimated time for the fifth pool:

b = log(0.85) / log(2) ≈ -0.157

Time for fifth pool = Time for first pool * (5^b)

Time for fifth pool = 30 * (5^(-0.157))

Calculating this, we find:

Time for fifth pool ≈ 30 * 0.6764 ≈ 20.29 hours

Therefore, the estimated time required to install the fifth pool is approximately 20.29 hours.

To calculate the total time for all five pools, we need to sum the time required for each pool from the first to the fifth. Since the learning curve assumes decreasing time with increasing units, we can use a summation formula:

Total time for all units = Time for first unit * ((1 - (n^b)) / (1 - b))

Using this formula, let's calculate the total time for all five pools:

Total time for all five pools = Time for first pool * ((1 - (5^b)) / (1 - b))

Total time for all five pools = 30 * ((1 - (5^(-0.157))) / (1 - (-0.157)))

Calculating this, we find:

Total time for all five pools ≈ 30 * 0.4615 ≈ 13.85 hours

Therefore, the estimated total time for all five pools is approximately 13.85 hours.

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a=1

Hope this helps

have a great day!

Step-by-step explanation:

Answer:

b

Step-by-step explanation: