-5+4(7+k) please help with this equation!

Answer:

C. (4,6)

D. (6.4)

E. (6,2)

Step-by-step explanation:

The value of m so that the condition satisfies is -2, the correct option is A.

We are given that;

y=f(x) is continuous

Now,

To find the numbers c that satisfy the conclusion of the Mean Value Theorem, we need to solve the equation:

f’© = [f(2) - f(0)] / (2 - 0)

f’(x) = 8x - 2

f(2) = 4(2)^2 - 2(2) + 3 = 23

f(0) = 4(0)^2 - 2(0) + 3 = 3

f’© = (23 - 3) / (2 - 0)

f’© = 10

8m - 2 = 10

8m = 12

m = 12/8

m = -2

Therefore, by the given function the answer will be -2.

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Answer:

B,Friday

Step-by-step explanation:

4 to 9 is 5 hours,the total hours for the week is 32.5 hours

The statement "The height of the probability density function f(x) of the uniform distribution defined on the interval [a, b] is 1/(a-b)" is False.

In a uniform distribution, the probability density function (PDF) is constant within the interval [a, b]. The height of the PDF represents the density of the probability distribution at any given point within the interval. Since the PDF is constant, the height remains the same throughout the interval.

To determine the height of the PDF, we need to consider the interval length. In a uniform distribution defined on the interval [a, b], the height of the PDF is 1/(b - a) for the PDF to integrate to 1 over the entire interval. This means that the total area under the PDF curve is equal to 1, representing the total probability within the interval [a, b].

Therefore, the correct statement is that the height of the probability density function f(x) of the uniform distribution defined on the interval [a, b] is not 1/(a - b), but rather it is a constant value necessary for the PDF to integrate to 1 over the interval, i.e., 1/(b - a).

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Based on John's conclusion that having asthma and the probability of having a fever are not independent, the correct statement is: P(A and O) ≠ P(A) x P(O).

When two events, A and O, are independent, the probability of both events occurring simultaneously (A and O) is equal to the product of their individual probabilities (P(A) x P(O)).

However, John's conclusion states that having asthma (A) and the probability of having a fever (O) are not independent, implying that the occurrence of one event affects the probability of the other event.

Given this information, the correct statement is that P(A and O) ≠ P(A) x P(O).

In other words, the probability of having both asthma and a fever is not equal to the product of the individual probabilities of having asthma and having a fever.

The other options provided do not accurately reflect John's conclusion. P(A and O) # P(A) x P(O) implies that they are approximately equal, which is not what John concluded.

P(A + O) = P(A) + P(O) represents the union of the events (A or O), which is different from their joint probability (A and O). P(D) = P(A) + P(O) does not relate to John's conclusion about asthma and fever.

Therefore, the true statement based on John's conclusion is:

P(A and O) ≠ P(A) x P(O).

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Answer:

x = ± 5

Step-by-step explanation:

x² - 25 = 0 ( add 25 to both sides )

x² = 25 ( take the square root of both sides )

x = ± \(\sqrt{25}\) = ± 5

solutions are x = - 5 , x = 5

Answer:

B

Step-by-step explanation:

The perimeter is decreased by 4 because 2(5+2) = 14 when 2(5+4) = 18

A graphical tool used to help determine whether a process is in control or out of control is known as a Control Chart.

Control charts are essential in quality control and statistical process control (SPC). They allow you to monitor process performance and variability over time, enabling you to identify trends, shifts, or deviations from the established process baseline.

Control charts typically consist of a centerline, representing the process mean, and upper and lower control limits, which indicate the acceptable range of variation. Data points are plotted on the chart, and if they fall within the control limits, the process is considered to be in control. If data points fall outside the control limits or display non-random patterns, the process is considered out of control, signaling potential issues that need to be investigated and addressed.

In summary, control charts are a valuable graphical tool that assists in determining the stability of a process, facilitating continuous improvement efforts and ensuring product quality. They provide a visual representation of process variation and help identify when corrective actions are needed to bring a process back into control.

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131,4..........................................

Vector equation of the line tangent to the graph of r(t) at the point p0 on the curve r(t) = (3t - 1) i + 13t j + 4 k.

To find a vector equation of the line tangent to the graph of r(t) at the point P0 on the curve r(t) = (3t - 1) i + 13t j + 16 k, where P0 is given as (-1,4), we can use the following steps:

Step 1: Find the derivative of r(t) with respect to t:

r'(t) = 3 i + 13 j

Step 2: Evaluate the derivative at the point P0:

r'(-1) = 3 i + 13 j

Step 3: Use the point P0 and the vector r'(-1) to form the vector equation of the tangent line:

r(t) = P0 + r'(-1) t

where t is a scalar parameter.

Plugging in the values, we get:

r(t) = (-1)i + 4j + (3i + 13j)t

Simplifying, we get:

r(t) = (3t - 1) i + 13t j + 4 k

Therefore, the vector equation of the line tangent to the graph of r(t) at the point P0 on the curve

r(t) = (3t - 1) i + 13t j + 16 k  is

r(t) = (3t - 1) i + 13t j + 4 k.

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The range of the function shown on the graph is: D. -1 ≤ y ≤ 1.

A range can be defined as the set of all real numbers that connects with the elements of a domain. This ultimately implies that, a range refers to the set of all possible output numerical values (real numbers), which are shown on the y-axis of a graph.

The vertical extent of a graph represents all range values and they are always read and written from smaller to larger numerical values, and from the bottom of the graph to the top.

By critically observing the graph shown, we can reasonably infer and logically deduce the following:

Range = [-1, 1]

In interval notation, the range of this graph can be rewritten as -1 ≤ y ≤ 1.

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29-3f+2g

=29-3(4)+2(3)

=29-12+6

=23

The distance travelled was 225 miles.

Speed is the unit rate in terms of distance travelled by an object and the time taken to travel the distance.

Speed is a scalar quantity as it only has magnitude and no direction.

Given that,

Average speed = 50 miles per hour

Time taken = 4 1/2 hours = 4.5 hours

Speed can be calculated using the formula,

Speed = Distance / Time

Distance = Speed × Time

               = 50 × 4.5

               = 225 miles

Detroit was 225 miles away.

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Answer:

b

Step-by-step explanation:

just add then then after you add 27=27 multiply it by 2

Answer:

90$

Step-by-step explanation

Step 1: You need to find how much was the 60% discount

Step 2: To find that multiply .6 by 50 you will get 30

Now you know how much was 60% discount

Step 3: Add   30(the discount) + 50(the prce sally pays) = 90 (the oriagnal price)

a-1. The expected value of the sample proportion is 33.33 (rounded to 2 decimal places), and the standard error is 0.0374 (rounded to 4 decimal places).

a-2. Yes, it is appropriate to use the normal distribution approximation for the sample proportion because both conditions np ≥ 5 and n(1 - p) ≥ 5 are satisfied.

b. The probability that more than 20% of smartphone users in the sample have fallen prey to a cyber-attack can be calculated using the normal distribution with a mean of 0.1667.

Expected value: The expected value is given by the formula: E(X) = npwhere,n = sample size = proportion of individuals with the specific characteristic in the population. The sample proportion can be calculated by dividing the number of individuals with the specific characteristic by the sample size.

p = 1/6n = 200E(X) = np = (1/6) × 200 = 33.33 ≈ 33.33. Therefore, the expected value is 33.33.

Standard error: The formula for standard error is given by: SE = √(pq/n)where p = proportion of individuals with the specific characteristic in the population.q = 1 – p (proportion of individuals without the specific characteristic in the population).n = sample size.

Substituting the values, we get,SE = √[(1/6 × 5/6)/200] = 0.0374 ≈ 0.0374Therefore, the standard error is 0.0374.

Yes, because np ≥ 5 and n(1 - p) ≥ 5The normal distribution approximation for the sample proportion is appropriate because np and n(1 - p) are both greater than or equal to 5.

Therefore, the answer is "Yes, because np ≥ 5 and n(1 - p) ≥ 5." b).

To find this probability, we need to calculate the z-score and then use the z-table.From the given information, the proportion of smartphone users that have fallen prey to cyber-attack isp = 1/6 = 0.1667q = 1 – p = 1 – 0.1667 = 0.8333n = 200.

Thus,μ = p = 0.1667σ = √(pq/n) = √[(0.1667 × 0.8333)/200] = 0.0374z = (x – μ)/σz = (0.20 – 0.1667)/0.0374 = 0.8938. Using the z-table, the probability of z > 0.8938 is 0.1867 or approximately 0.187. Therefore, the probability that more than 20% of smartphone users in the sample have fallen prey to cyber-attack is 0.187.

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i. 4 ∈ A (4 is an element of A)

ii. A ⊂ 20 (A is a proper subset of 20)

iii. B ⊃ A (B contains A)

iv. Ø ∈ 8 (Empty set Ø is an element of 8)

i. 4 ∈ A: This statement means that the element 4 is a member of set A. In other words, 4 is one of the values included in set A.

ii. A ⊂ 20: This symbol ⊂ represents a subset relation, indicating that set A is a proper subset of set 20. This means that every element in set A is also an element of set 20, but set 20 contains additional elements that are not in set A.

iii. B ⊃ A: The symbol ⊃ denotes a superset relation, implying that set B is a superset of set A. This means that set B contains all the elements of set A, and possibly additional elements as well.

iv. Ø ∈ 8: The symbol Ø represents the empty set, which is a set with no elements. The symbol ∈ indicates that the empty set is an element of set 8. In other words, 8 includes the empty set as one of its elements.

Each of these symbols provides a way to relate sets and elements within set theory. They help us understand the relationships between sets and their elements, such as membership, subset, superset, and the inclusion of the empty set. These relationships are fundamental in mathematical analysis and provide a foundation for studying set operations, set properties, and set relations.

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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:

x=9 y=2

Step-by-step explanation:

It's really long, but if you need it I can do it in the comments.

Answer:

A function can have many x values for a given y value and still be a function but it cannot have many y values for a given x value. You can easily test this by graphing the equation and doing the vertical line test by seeing if a vertical line will intersect the graph only once at all x values, if it passes it is a function. In short what you have here is a function

Step-by-step explanation:

Bryant Industries uses forecasting to estimate the number of orders that will be placed by their customers. The table below gives the sales figures for the last four months.Month2345Sales92491942004There are different forecasting techniques used by companies like Bryant Industries to predict future sales.

One of the most widely used methods is the time-series method. This method is particularly useful when the demand for a product or service changes over time and when there are no external factors that affect the sales. In this case, we can use a time-series method called the moving average to estimate future sales. The moving average is a time-series method that uses the average of past sales data to estimate future sales. It is particularly useful when there are no external factors that affect the sales. In this case, we can use a 3-month moving average to estimate future sales. The 3-month moving average is calculated as follows: (924 + 919 + 420) / 3 = 754.33. This means that we can expect sales of around 754 units next month. The moving average method is easy to use and is a good way to get a quick estimate of future sales. However, it has some limitations. For example, it does not take into account external factors that may affect sales, such as changes in the economy or in consumer behavior.

In conclusion, Bryant Industries can use the moving average method to estimate future sales. However, they should also consider other factors that may affect sales, such as changes in the economy or in consumer behavior. By doing so, they can make more accurate forecasts and improve their overall performance.

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Answer:

x = 1

Step-by-step explanation:

5 - 5 + 3x = 8 - 5

3x = 3

3x/3 = 3/3

x = 1

4039 will be the population of town in 1995 .

In mathematics, a percentage is a number or ratio that is expressed as a fraction of 100. In addition to the percent symbol "%," the abbreviations "pct," "pct," and occasionally "pc" are also used to denote it. A% has neither dimensions nor a defined unit of meas.urement.

initial population  = 577 in 1970

rate of increase =  24 % per year

population in 1995 will be  =

   first we need to find how much exact population in increasing in 1 year =

577 + 57*24/100 = 577 + 13.68 = 590.68

= 577 + 577 * 24 * (1995-1970) /100

= 577 + 3462

= 4039

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Answer:

2%

Step-by-step explanation:

Answer:

20%

Step-by-step explanation:

Input data

S=(3x+47)°

T= (5x+21)°.

The first even multiple of 9 is 18.

Answer:

18

Step-by-step explanation:

1 times 9 is 9;

2 times 9 is 18;

3 times 9 is 27;

and so on.

The first even multiple of 9 is 18.  

Answer:

17 + 15

Step-by-step explanation: