Together, teammates Pedro and Ricky got 2670 base hits last season. Pedro had 280 more hits than Ricky. How many hits did each player​ have?

When I run 5280 feet in 5.00 minutes my speed is 12 miles per hour

It is a physical quantity that indicates the displacement of a mobile per unit of time, it is expressed in units of distance per time, for example (miles/h, km/h).

The formula and procedure we will use to solve this exercise is:

v = x /t

Where:

Information about the problem:

Applying the velocity formula, we get:

v = x /t

v = 5280 feet / 5 minutes

v = 1056 feet/ minutes

By converting the unit from feet to miles and from hours to minutes, we have:

1056 feet/ minutes * (1 miles / 5280 feet) * (60 minutes / 1 hour) = 12 miles/hour

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No. of solution exist for the absolute value equation 2|x + 2| + 1 = 9  is 2

The two values are x =  -6,2

The given question has a small mistake, it needs to be written as

2|x + 2| + 1 = 9

Solving the absolute value equation,

2|x + 2| + 1 = 9

2|x + 2|  = 9 -1

2|x + 2| = 8

|x + 2| = 8/2

|x + 2|  = 4

Expanding the absolute value equation,

x + 2 = 4                                       x + 2 = -4

x = 4 -2                                         x = -4 -2

x = 2                                             x = -6

Therefore, the equation has two values ,x = -6,2

Total no. of solution that exist for the given absolute value equation is 2

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Answer: I would go with 3/5, the person who said 7/20 doesn't have any thank you's or ratings besides themselves while 3/5 has thank you's , and confirmation

Step-by-step explanation:

The foci of the ellipse are (4, 0) and (9, 0).

To find the foci of the ellipse, we first need to determine its standard form equation and identify the values of the major and minor axes. Given the endpoints of the major axis are (0,0) and (13,0), we can determine that the length of the major axis (2a) is 13 units. Thus, a = 6.5 units.

The minor axis has a length of 12 units, so the length of the minor axis (2b) is 12 units. Therefore, b = 6 units.

Next, we will find the value of c, which is the distance from the center of the ellipse to each focus. Using the relationship \(c^2 = a^2 - b^2\), we get:

\(c^2 = (6.5)^2 - (6)^2\)
\(c^2 = 42.25 - 36\)
\(c^2 = 6.25\)
c = √6.25
c ≈ 2.5 units

Now, we have all the necessary information to find the foci of the ellipse. Since the major axis is along the x-axis, the foci will be located at a distance of c units to the left and right of the center (which is the midpoint of the major axis). The center of the ellipse is (6.5, 0), so the foci will be at (6.5 - 2.5, 0) and (6.5 + 2.5, 0), which are (4, 0) and (9, 0).

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The probability that one of the scores in the sample is less than 1484 is 0.2437 .

a)Given that mean u = 1403

standard deviation σ = 200

sample size n = 32

P(x>1484) = P(X-u/σ > 1484-1403/200)

                = P (z > 0.405)

P(x>1484) = 0.2437 .

hence the probability that one score is greater than 1484 is 0.405 .

b) Now we have to find the average of the scores of 48 samples.

P(x>1484)

= P(x-μ/ σ/√n> 1484-1403 /200/√48)

= P(z>2.805.)

Now we will use the normal distribution table to calculate the p value to be 0.002516.

p-value = 0.0025

Normal distributions are very crucial to statistics because not only they are commonly used in the natural and social sciences but also to describe real-valued random variables with uncertain distributions.

They are important in part because of the central limit theorem. This claim states that, in some cases, the average of many samples (observations) of a random process with infinite mean and variance is itself a random variable, whose distribution tends to become normal as the number of samples increases.

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Answer:

mean = 8

Step-by-step explanation:

assuming you mean ∑ x = 40

then

mean = ∑ x ÷ n = 40 ÷ 5 = 8

Answer:

Point R: (-2,0)

Point A: (-6,-2)

Point N: (-1,-3)

Step-by-step explanation:

Reflecting a shape across the y-axis means that the y value of the coordinate of the points would reverse its sign, meaning for eg a negative number would turn into a positive one or a positive would turn into a negative.

So in this case, point R would stay the same because it's on the y-axis but the two points A and N would change. Point A is (-6,2) so if we change the y coordinate we would get (-6,-2) and point N is (-1,3) so it would become (-1,-3). Therefore the answer is:

Point R: (-2,0)

Point A: (-6,-2)

Point N: (-1,-3)

To simplify the given expression: (-5x-2z-5) -2 (-5x-2z-5) -2, we'll use positive exponents only. As per the order of operations, we'll carry out multiplication first; then simplify the given expression.Now, the numerator cannot be simplified further.

Thus, the simplified form of the given expression: (-5x-2z-5) -2 (-5x-2z-5) -2= 1/[(5x+2z+5)2(5x+2z+5)2]can be expressed in more than 100 words as follows.

To simplify the given expression: (-5x-2z-5) -2 (-5x-2z-5) -2, we'll use positive exponents only. As per the order of operations, we'll carry out multiplication first; then simplify the given expression.

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Recurrence relations are mathematical equations that define the running time of an algorithm in terms of its input size. To find the time complexity of a recurrence relation, we can use one of the three methods: substitution method, recursion tree method, and master theorem.

The substitution method involves replacing the recurrence relation with an assumed solution and then proving it using mathematical induction. The recursion tree method involves constructing a tree diagram to represent the recurrence relation and calculating its running time. The master theorem is a formula that can be used to determine the time complexity of a recurrence relation based on its coefficients.

Assuming the base case t(0), we can find the time complexity of a recurrence relation using any of these methods. For example, if we have a recurrence relation of the form T(n) = 2T(n/2) + n, we can use the master theorem to find its time complexity. The theorem states that if the recurrence relation is of the form T(n) = aT(n/b) + f(n), where a >= 1, b > 1, and f(n) is a polynomial, then its time complexity is O(nlogba) if logba > c, O(nlogba log n) if logba = c, and O(n^c) if logba < c, where c is a constant.

In summary, to find the time complexity of a recurrence relation, we can use one of the three methods: substitution method, recursion tree method, and master theorem. All three methods involve solving the recurrence relation and determining its running time based on its input size.

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The actual length of a cafeteria is 64 ft. Therefore, the option A is the correct answer.

A scale factor is defined as the ratio between the scale of a given original object and a new object, which is its representation but of a different size (bigger or smaller).

The basic formula to find the scale factor of a figure is expressed as,

Scale factor = Dimensions of the new shape ÷ Dimensions of the original shape.

Given that, Austin used a scale that equaled 4 feet for every 1 inch depicted.

The scale drawing he made identified the cafeteria as being 16 inches in length.

Now, 4×16

= 64 feet

Therefore, the option A is the correct answer.

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Answer:

Kindly check explanation

Step-by-step explanation:

Given that :

One time fee = $30

Reduced price of ticket after one time fee payment = $17

Regular ticket cost = $25

Write an inequality that can be used to determine the number of reduced price concert tickets you would need to purchase in order for the total cost to be less expensive than the same number of regular tickets

Let the number of tickets needed to purchase = t

Reduced ticket = 30 + 17t

Regular ticket = 25t

30 + 17t < 25t

30 < 25t - 17t

30 < 8t

30/8 < 8t/8

3.75 < t

t > 3.75

Hence number of ticket must be greater than 3.75

t = 4

Long-Run Average Cost Curve is a curve that shows the lowest average total cost at which it is possible to produce each output when the firm has had sufficient time to change both its plant size and labor employed.

A Long-Run Average Cost Curve is also known as a planning curve. This is considering a firm plans to create an output in the long run by selecting a plant on the long run average cost curve corresponding to the output.

It is also called envelope curve, because it envelopes all short run average cost curves. Particularly, it envelops the short run the production levels or the production points.

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Location of the negative make value different from each other that is  5.3/10^4 and -(5.3 * \(10^{4}\))  

According to this rule, if the exponent is negative, we can change the exponent into positive by writing the same value in the denominator and the numerator holds the value 1.

The negative exponent rule is given as:

   5. 3 x 10^-4

=  5.3/10^4                 (1)

-5. 3 x 10^4

-(5.3 * \(10^{4}\))                  (2)

from equation 1 and 2 these two equations are different from each other.

location of the negative make value different from each other that is  5.3/10^4 and -(5.3 * \(10^{4}\))  

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Answer:

\(7p - ( - 5) + ( - 1) \\ = 7p + 5 - 1 \\ = 7p + 4\)

Answer:7p+4 :)

Step-by-step explanation:

The Laplace transform of a bt + ct^2 for some constants a, b, and c can be found using the linearity property of the Laplace transform. The Laplace transform of a linear combination of functions is equal to the linear combination of their Laplace transforms. Therefore, the Laplace transform of a bt + ct^2 is equal to the Laplace transform of at + the Laplace transform of bt^2.

The Laplace transform of at is a/s, and the Laplace transform of bt^2 is 2b/s^3. Therefore, the Laplace transform of a bt + ct^2 is:

a/s + 2b/s^3

This is the direct answer to the problem.

In more detail, the Laplace transform is a mathematical tool that allows us to convert a function of time into a function of complex frequency. It is defined as the integral of the function multiplied by the exponential function e^(-st), where s is the complex frequency parameter. The Laplace transform has many applications in engineering, physics, and mathematics, particularly in the analysis of linear time-invariant systems.

In this problem, we used the linearity property of the Laplace transform to find the Laplace transform of a bt + ct^2. This property states that the Laplace transform of a linear combination of functions is equal to the linear combination of their Laplace transforms. We first found the Laplace transform of at and bt^2 separately using the Laplace transform formulas. Then, we added them together to obtain the Laplace transform of a bt + ct^2.

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The Laplace transform of a bt + ct^2 for some constants a, b, and c can be found using the linearity property of the Laplace transform. The Laplace transform of a linear combination of functions is equal to the linear combination of their Laplace transforms. Therefore, the Laplace transform of a bt + ct^2 is equal to the Laplace transform of at + the Laplace transform of bt^2.

The Laplace transform of at is a/s, and the Laplace transform of bt^2 is 2b/s^3. Therefore, the Laplace transform of a bt + ct^2 is:

a/s + 2b/s^3

This is the direct answer to the problem.

In more detail, the Laplace transform is a mathematical tool that allows us to convert a function of time into a function of complex frequency. It is defined as the integral of the function multiplied by the exponential function e^(-st), where s is the complex frequency parameter. The Laplace transform has many applications in engineering, physics, and mathematics, particularly in the analysis of linear time-invariant systems.

In this problem, we used the linearity property of the Laplace transform to find the Laplace transform of a bt + ct^2. This property states that the Laplace transform of a linear combination of functions is equal to the linear combination of their Laplace transforms. We first found the Laplace transform of at and bt^2 separately using the Laplace transform formulas. Then, we added them together to obtain the Laplace transform of a bt + ct^2.

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The probability that exactly two of the CDs are in the wrong cases is 1, or 100%.

To solve this problem, we can use the formula for permutations and combinations. The number of ways to place four CDs in four cases is 4!, which equals 24. The number of ways to place exactly two CDs in the wrong cases is the product of two combinations: the number of ways to choose two CDs out of four to be in the wrong cases, and the number of ways to place those two CDs in the wrong cases.

The number of ways to choose two CDs out of four is given by the combination formula:

C(4,2) = 4! / (2! × (4-2)!) = 6

The number of ways to place those two CDs in the wrong cases is 2, since each of the two incorrectly placed CDs can go in one of the two remaining cases.

The number of ways to place the other two CDs in their correct cases is 2, since each CD has exactly one correct case left.

Therefore, the total number of ways to place exactly two CDs in the wrong cases is:

6 × 2 × 2 = 24

So the probability of this happening is:

24 / 4! = 24 / 24 = 1

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The missing angle for x by the measures add up to 90° is 53°

Complementary angles are pairs of angles whose measures add up to 90°. In this problem, we are given two angles, one of which measures 37°, and the other of which has an unknown measure that we will call x. We are also told that these angles are complementary, which means that their measures add up to 90°.

So, we can set up an equation to represent this relationship:

37 + x = 90

We can simplify this equation by subtracting 37 from both sides:

x = 90 - 37

x = 53

Now we know that the measure of the second angle is 53°. But we can go further and solve for x to get a more complete solution.

In the problem statement, we are also given an expression for the second angle in terms of x:

5x + 3

We know that this angle measures 53°, so we can set up another equation to represent this relationship:

5x + 3 = 53

We can solve for x by first subtracting 3 from both sides:

5x = 50

Then, we can divide both sides by 5 to isolate x:

x = 10

Now we know that x has a value of 10, and we can substitute this value back into the expression for the second angle to find its measure:

= 5x + 3

= 5(10) + 3 = 53

Therefore, the missing angle is 53°, and x has a value of 10.

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Answer:

13 P

Step-by-step explanation:

Answer: 13p

Step-by-step explanation:

All three terms have the same variable. Therefore, you can add all three terms together into a singular term (below).

5p + 2p + 6p = 13p

Answer: A. 24 Quarts

Step-by-step explanation:  6*4=24

The "critical-value" for a 98% "confidence-level" and a "sample-size" of 16 is approximately 2.602.

We see that the "sample-size" is "n = 16" is small, we use the t-distribution instead of the standard normal distribution.

The "critical-value" for a specific confidence-level and sample-size is determined by the degrees-of-freedom (df), which is equal to n - 1.

So, in this case, the degrees of freedom is 16 - 1 = 15.

We know that the "critical-value" for a 98% confidence level and 15 degrees of freedom. The critical value is approximately 2.602.

Therefore, the required critical-value is 2.602.

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The given question is incomplete, the complete question is

Find the critical value for confidence level "c = 0.98" and sample-size "n = 16". ​

Answer:

$81.75

Step-by-step explanation:

So, she bought 7 pizzas that cost $11.25 each plus an additional $3 fee. Therefore, the total she spent was:

7(11.25)+3

Multiply:

78.75+3=$81.75

And we're done!

Answer:

3p - 145w ≥ 50

Step-by-step explanation:

w = number of winners

p = number of plays of carnival game

Profits = 3p - 145w

3p - 145w ≥ 50

Answer:

-2(2-5x)

Step-by-step explanation:

3+2×(5x)-7

Calculate the difference

-4+2×(5x)

Factor out -2 from the expression

-2(2-5x)

Thats the answer: -2(2-5x)

Hope this helps

The program provided sets up output destination options and then executes a PROC PRINT statement to display the data from the "orion.test" dataset. However, without running the program, I can still provide an explanation based on the code.

In the code, the ODS (Output Delivery System) statements are used to control the output format and destination. The first line, "ods all close;", closes all open ODS destinations. The second line, "ods html file='c:\test.html' style=meadow;", directs the output to an HTML file named "test.html" located at "c:\test.html" with a specific style called "meadow". The next line, "ods html close;", closes the HTML output destination.

Following that, the "ods listing;" statement directs the output to the default output destination, which is typically the SAS log or output window. Then, the PROC PRINT statement is used to print the data from the "orion.test" dataset.

Considering the output destinations set up in the program, the output will be available in three different places. First, it will be saved as an HTML file named "test.html" at "c:\test.html". Second, if you have the SAS output window or log open, you will be able to see the output there as well. Finally, the output will also be available as a CSV file since the "ods csvall;" statement directs the output to be generated in CSV format.

In summary, the program generates output in three locations: an HTML file, the SAS output window or log, and a CSV file. These destinations allow for different ways to access and review the output data.

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The correlation coefficient of 0.90 indicates a strong positive linear correlation between happiness and GPA of high school students.

A correlation coefficient measures the strength and direction of the relationship between two variables. In this case, the correlation coefficient of 0.90 indicates a strong positive linear correlation between happiness and GPA of high school students.

A positive correlation means that as one variable (in this case, happiness) increases, the other variable (GPA) also tends to increase. The magnitude of the correlation coefficient, which ranges from -1 to 1, represents the strength of the relationship. A value of 0.90 indicates a very strong positive linear correlation, suggesting that there is a consistent and significant relationship between happiness and GPA.

This means that as the level of happiness increases among high school students, their GPA tends to be higher as well. The correlation coefficient of 0.90 suggests a high degree of predictability in the relationship between these two variables.

It is important to note that correlation does not imply causation. While a strong positive correlation indicates a relationship between happiness and GPA, it does not necessarily mean that one variable causes the other. Other factors or variables may also influence the relationship between happiness and GPA.

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The complete formulation of the integer programming problem can be written as:

Minimize Z = Σi=1n Σj=1m cij xij

subject to:

Σj=1m xij = 1, for i = 1, 2, ..., n

Σi=1n xij = 1, for j = 1, 2, ..., m

xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

To formulate an integer programming problem for assigning each route to one bidder (and each bidder to only one route), we can follow these steps:

Define decision variables: Let xij be a binary variable, where xij=1 if bidder i is assigned to route j, and xij=0 otherwise. Here i = 1, 2, ..., n is the index for bidders, and j = 1, 2, ..., m is the index for routes.

Define the objective function: The objective is to minimize the total cost of assignment, which can be represented as the sum of the cost of each assignment, given by cij. Therefore, the objective function can be formulated as:

Minimize Z = Σi=1n Σj=1m cij xij

Define the constraints:

Each bidder can only be assigned to one route: Σj=1m xij = 1, for i = 1, 2, ..., n.

Each route can only be assigned to one bidder: Σi=1n xij = 1, for j = 1, 2, ..., m.

The decision variables are binary: xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

These constraints ensure that each bidder is assigned to only one route, and each route is assigned to only one bidder.

The complete formulation of the integer programming problem can be written as:

Minimize Z = Σi=1n Σj=1m cij xij

subject to:

Σj=1m xij = 1, for i = 1, 2, ..., n

Σi=1n xij = 1, for j = 1, 2, ..., m

xij ∈ {0, 1}, for i = 1, 2, ..., n and j = 1, 2, ..., m.

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Full Question ;

formulate an ip that assigns each route to one bidder (and each bidder must be assigned to only one route)

We can be 99% confident that the average number of miles an automobile is driven annually in Alabama is between 21,342.6 and 24,637.4 miles

To answer this question, we need to use the following formula for a confidence interval for the mean: CI = (μ - z*(σ/√n), μ + z*(σ/√n)), Where μ is the population mean, z is the z-score for the given confidence level, σ is the population standard deviation, and n is the sample size. Using the given information, we can calculate the confidence interval for the mean:CI = (23500 - 2.575*(3900/√100), 23500 + 2.575*(3900/√100)), CI = (21342.6, 24637.4)

To summarize, we used the formula for a confidence interval for the mean and the given information to calculate the confidence interval for the average number of miles an automobile is driven annually in Alabama. This confidence interval is (21342.6, 24637.4), which means we can be 99% confident that the average number of miles an automobile is driven annually in Alabama is between 21,342.6 and 24,637.4 miles.

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a. The probability that the current component has been in operation for at least 50 hours is 0.5

b. The probability that the current component will last for at least 50 more hours is also 0.5.

(a) The probability that the current component has been in operation for at least 50 hours is given by the cumulative distribution function (CDF) of the uniform distribution on [100, 200] evaluated at 50.

The CDF of a uniform distribution on [a, b] is given by:

F(x) = (x - a) / (b - a) for a <= x <= b

F(x) = 0 for x < a

F(x) = 1 for x > b

Therefore, in this case, the CDF is:

F(x) = (x - 100) / 100 for 100 <= x <= 200

F(x) = 0 for x < 100

F(x) = 1 for x > 200

So the probability that the current component has been in operation for at least 50 hours is:

P(ti >= 50) = 1 - F(50) = 1 - ((50 - 100) / 100) = 0.5

(b) The probability that the current component will last for at least 50 more hours is also given by the CDF of the uniform distribution on [100, 200], but evaluated at 150 instead of 50.

That is,

P(ti >= 150) = F(150) = (150 - 100) / 100 = 0.5.

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