You want to buy DVDs and are searching for the best price. You found two stores having sales on DVDS. Which is the one that offers the best percentage off? Then explain your reasoning.
Store 1 - Buy 2 for the price of one!
Store 2 - Buy 3 for the price of two!

Answer:

\(600\)

\( 6 \times {10}^{2} \)

Every 10 nights, she knits 30cm of the scarf.

Take 30cm and divide it by 10 days and you will get 3cm per day

A spool of ribbon contains 13 1/2 inches of ribbon.

Maggie uses 2 1/4 inches of ribbon on each gift box she makes.

How many gift boxes can Maggie make with one spool of ribbon?​

We need to divide 13 1/2 by 2 1/4 to get the number of boxes she can make.

Let us simplify the above expression (first, convert the mixed fractions to simple fractions)

Recall that division is the reciprocal of multiplication

Therefore, Maggie can make 6 gift boxes with one spool of ribbon.

Answer: ( 0, -2 )

Step-by-step explanation:

y = mx + b

x + 2y = -4

2y = x - 4

_______

2          2

(y = - 2)

Answer:

(-4, 0) (0, -2)

Step-by-step explanation:

I took the K12 test I'm right guaranteed.

Answer:

The volume equals 980

Step-by-step explanation:

Volume = L x W x H

14 x 7 x 10 = 980

Step-by-step explanation:

in a triangle, if the hipotenus is 17, the other edges' lenghts are multiples of 8 and 15.

so the Man walked 23km.

subtract 7km

16km left

so he goes 8km north and 15km east

The optimal solution for the given linear programming problem using the graphical solution procedure is at (A, B) = (6, 2) with the objective function value of -4.

To find the optimal solution graphically, we plot the feasible region determined by the constraints. In this case, the feasible region is a polygon bounded by the lines 2A + 3B = 12, A + 4B ≤ 21, 2A + B ≥ 7, 3A + 1.5B ≤ 21, and -2A + 6B ≥ 0. We then evaluate the objective function -2A - B at the vertices of the feasible region to determine the optimal solution. The vertex that gives the minimum value of the objective function is the optimal solution. By calculating the objective function at each vertex, we find that the minimum value of -4 is obtained at (A, B) = (6, 2). This means that the optimal solution is to set A = 6 and B = 2, and the objective function value at this point is -4. For part (b), to determine the amount of slack or surplus for each constraint, we evaluate the constraints at the optimal solution (A, B) = (6, 2). For the constraint 1A + 4B ≤ 21, the left-hand side is 1(6) + 4(2) = 14, which indicates a slack of 7 (21 - 14). For the constraint 2A + 1B ≥ 7, the left-hand side is 2(6) + 1(2) = 14, which indicates a surplus of 7 (14 - 7). For the constraint 3A + 1.5B ≤ 21, the left-hand side is 3(6) + 1.5(2) = 20, which indicates a slack of 1 (21 - 20). Lastly, for the constraint -2A + 6B ≥ 0, the left-hand side is -2(6) + 6(2) = 4, which indicates a surplus of 4 (4 - 0). These slack and surplus values represent the amount by which the left-hand side of each constraint falls short or exceeds the right-hand side at the optimal solution. A positive slack indicates that the constraint is not fully utilized, while a positive surplus indicates that the constraint is exceeded.

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If A has rank 6, then it has 6 linearly independent rows and its row space has dimension 6. If the rank of A is less than 6, then the dimension of the row space will be less than 6.

The row space of a matrix is the span of its row vectors. Therefore, the dimension of the row space is equal to the number of linearly independent rows of the matrix.

For a 9x6 matrix A, the largest possible dimension of the row space is 6. This is because there can be at most 6 linearly independent rows in a 9x6 matrix. If there were more than 6 linearly independent rows, then the matrix would have rank greater than 6, which is impossible since the maximum rank of a 9x6 matrix is 6.

For a 6x9 matrix A, the largest possible dimension of the row space is also 6. This is because the number of linearly independent rows cannot exceed the number of columns in the matrix.

Therefore, if A has rank 6, then it has 6 linearly independent rows and its row space has dimension 6.

However, if the rank of A is less than 6, then the dimension of the row space will be less than 6.

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Answer: A

Step-by-step explanation:

3/5 = 60%

A, Rosa has 7/12 which is about 58%

B, Rosa has 6/12, which is 50%

C, Rosa has 9/12 which is 75%

D, Rosa has 8/12 which is 66%

A would be the closest.

Answer: 2880 flowers

Step-by-step explanation:

Since 648 flowers were arranged in 27 large vases, with the same number in each vase, this means that each vase will contain 24 flowers

= 648/27

= 24 flowers

Therefore, the number of flowers needed to fill 120 vases will be:

= 24 × 120

= 2880 flowers

The number of red chips in the bag is 4

From the question, we have the following parameters that can be used in our computation:

Number of chips = 10

Colours of chips = Blue and red

When 1 blue chip is removed, we have the following probability value

P(Blue) = 3/5

Express the denominator as 10

So, we have the following representation

P(Blue) = 6/10

This means that

Blue : Total = 6 : 10

This also means that

Blue : Blue + Red = 6 : 10

So, we have

Blue + Red = 10

Blue = 6

Substitute the known values in the above equation, so, we have the following representation

6 + Red = 10

Evaluate

Red = 4

Hence, the number of red chips is 4

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Complete question

a bag contains only red and blue plastic chips. there were 10 chips in the bag and 1 blue chip was removed. the probability of drawing a blue chip was then 3/5. how many red chips were in the bag?

The estimate for the area under the graph of f(x) = x/7 from x = 1 to x = 6 using 5 approximating rectangles and right endpoints is 1.25.

To estimate the area under the graph using rectangles, we divide the interval [1, 6] into smaller subintervals. In this case, we have 4 rectangles, each with a width of 1. The right endpoint of each subinterval is used as the height of the rectangle.

We can also use the right Riemann sum approach.

For the first rectangle, the height is f(2) = 2/7 = 0.28

For the second rectangle, the height is f(3) = 3/7 = 0.42.

For the third rectangle, the height is f(4) = 4/7 = 0.57.

And for the fourth rectangle, the height is f(5) = 5/7 = 0.71.

Adding up the areas of the rectangles, we get 0.28 + 0.42 + 0.57 + 0.71 = 1.98

However, since the rectangles extend beyond the actual area, we need to subtract the excess.

The excess is equal to the area of the rightmost rectangle that extends beyond the graph, which has a width of 1 and a height of f(5) = 5/7 = 0.71.

Subtracting this excess, we get an estimate of 1.98 - 0.71 = 1.27.

Dividing this estimate by 5, we obtain 0.25, which is the area of each rectangle.

Hence, the estimate for the area under the graph using right endpoints is 5 * 0.25 = 1.2.

Similarly, we can calculate the estimate using left endpoints by using the left endpoint of each subinterval as the height of the rectangle.

In this case, the estimate is 5 * 0.25 = 1.2.

Therefore, the estimate using left endpoints is 1.2.

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Using long division the quotient of  (2x^3-5x^2+3x-6) divided by (x+4)  is 2x^2 - 13x + 55.

Quotients are often used in algebra and other branches of mathematics to solve equations and expressions involving division. They are also commonly used in everyday life, such as when calculating the cost per unit of a product, or the average speed of a journey.

For example, if we divide 10 by 2, the quotient would be 5, since 10 divided by 2 equals 5. Similarly, if we divide 12 by 3, the quotient would be 4, since 12 divided by 3 equals 4.

Now let find the quotient using long division:

2x^2 - 13x + 55

_______________________

x + 4 | 2x^3 - 5x^2 + 3x - 6

- (2x^3 + 8x^2)

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

- 13x^2 + 3x

- (-13x^2 - 52x)

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

55x - 6

- (55x + 220)

-----------

-226

Therefore, the quotient is 2x^2 - 13x + 55 and the remainder is -226.

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The probability of selecting the word "States" is about 1.84%, the probability of selecting either "the" or "States" is about 6.92%, and the probability of selecting a word that is neither "the" nor "States" is about 93.08%.

(a) The probability of selecting the word "States" from the story is determined by dividing the number of occurrences of "States" by the total number of words in the story. In this case, the probability is 92/5000, which simplifies to 0.0184 or 1.84%. (b) To find the probability of selecting either "the" or "States," add the individual probabilities of each word. The probability of "the" is 254/5000 or 0.0508 (5.08%), and we already calculated the probability of "States" as 1.84%. The combined probability is 0.0508 + 0.0184 = 0.0692, or 6.92%. (c) To determine the probability of selecting a word that is neither "the" nor "States," subtract the combined probability of selecting either of those words from 1. The probability of selecting neither "the" nor "States" is 1 - 0.0692 = 0.9308, or 93.08%.

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To form a triangle, the set of line segments must satisfy the triangle inequality theorem, which states that the sum of the lengths of any two sides of a triangle must be greater than the length of the third side. Therefore, we need to check if the given line segments 8 cm, 4 cm, and 3 cm meet this requirement.

We can start by checking if the sum of the two smaller sides (3 cm and 4 cm) is greater than the largest side (8 cm). 3 cm + 4 cm = 7 cm, which is less than 8 cm. Therefore, these three line segments cannot form a triangle.

In general, for a set of line segments to form a triangle, the largest side must be smaller than the sum of the other two sides. In this case, the line segment of 8 cm is too long compared to the other two sides, which makes it impossible to form a triangle.

In conclusion, there are no line segments that meet the requirements to form a triangle with lengths of 8 cm, 4 cm, and 3 cm.

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Answer:

value + value = 8379.70

249.99x + 329.99*30-329.99x = 8379.70

-80x + 9899.70 = 8379.70

-80x = -1520.00

x = 19

30-x = 11

Step-by-step explanation:

5. An action or process of solving a problem

Thats all I can answer for u :D

Translating words into algebraic expressions means taking words and replacing them with mathematical symbols to create an equation. For example, the expression "five more than a number" can be written as "x + 5" where "x" represents the number.

Translating words into algebraic expressions is a useful skill when solving math problems. It involves taking words and replacing them with mathematical symbols to create an equation. For example, the expression "five more than a number" can be written as "x + 5" where "x" represents the number. By translating words into an algebraic expression, it becomes easier to solve problems using the correct equations. It is important to remember to use the correct symbols and to be mindful of the order of operations when translating words into algebraic expressions. When done correctly, translating words into algebraic expressions can help to make complex math equations easier to understand and solve.

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Sufficient evidence to support the claim that the population variances are not equal.

a. F-value, we divide the mean square for treatments by the mean square for error.

b. Sufficient evidence to support the claim that at least one mean is different.

c. The means are significantly different from each other.

Population variances are equal, we use the F-test for equality of variances.

The test statistic is calculated as the ratio of the sample variances, with the larger variance in the numerator.

The null hypothesis is that the variances are equal, and the alternative hypothesis is that they are not equal.

In this case, we have:

Sample 1: n1 = 13, \(s1^2 = 4.1\)

Sample 2: n2 = 25, \(s2^2 = 9.2\)

The test statistic is:

\(F = s2^2 / s1^2 = 9.2 / 4.1 = 2.2439\)

The degrees of freedom are df1 = n2 - 1 = 24 and df2 = n1 - 1 = 12.

Using a significance level of 5%, the critical value for the F-test with:

df1 = 24 and df2 = 12 is 3.055.

Since the calculated F-value (2.2439) is less than the critical value (3.055), we fail to reject the null hypothesis.

a. To construct an ANOVA table, we need to calculate the sum of squares for treatments (SST), sum of squares for error (SSE), and total sum of squares (SSTO).

The formula for SST is:

\(SST = \Sigma (xi)^2 / n - (\Sigma xi)^2 / N\)

xi is the sum of the scores in each group, n is the sample size in each group, and N is the total sample size.

In this case, we have:

xi1 = 69, xi2 = 57, xi3 = 100, xi4 = 44

n1 = 5, n2 = 4, n3 = 4, n4 = 3

N = 16

Plugging in the values, we get:

\(SST = [(69)^2/5 + (57)^2/4 + (100)^2/4 + (44)^2/3] - [(69 + 57 + 100 + 44)^2 / 16] = 309.158\)

The sums of squares for error (SSE) is calculated as:

\(SSE = \Sigma (xi - \bar xi)^2\)

\(\bar xi\) is the mean of the scores in each group.

In this case, we have:

\(\bar x1 = 13.8, \bar x2 = 14.25, \bar x3 = 19.25, \bar x4 = 12.8\)

Plugging in the values, we get:

\(SSE = (12 - 13.8)^2 + (11 - 13.8)^2 + (14 - 19.25)^2 + (10 - 12.8)^2 + (14 - 14.25)^2 + (16 - 14.25)^2 + (20 - 19.25)^2 + (22 - 19.25)^2 + (17 - 12.8)^2 + (9 - 12.8)^2 + (13 - 12.8)^2 + (12 - 12.8)^2 + (23 - 12.8)^2 + (10 - 12.8)^2 = 64.425\)

The total sum of squares (SSTO) is:

\(SSTO = \Sigma xi^2 - (\Sigma xi)^2 / N\)

Plugging in the values, we get:

\(SSTO = (69^2 + 57^2 + 100^2 + 44^2) - (69 + 57 + 100 + 44)^2 / 16 = 1742.75\)

Using these values, we can construct the ANOVA table:

Source    Squares (SS)  Freedom (DF)   Mean Square (MS)    F-value

Between    309.158               3                       103.053                5.186*

 Error          64.425               12                        5.369

 Total         1742.75               15

b. The null hypothesis for the ANOVA test is that the means of all the groups are equal, and the alternative hypothesis is that at least one mean is different.

Using the ANOVA table, we can calculate the F-value as:

F = MS between / MS error = 103.053 / 5.369 = 19.222

Using a significance level of 5%, and with df1 = 3 and df2 = 12, the critical value for the F-test is 3.104.

Since the calculated F-value (19.222) is greater than the critical value (3.104), we reject the null hypothesis.

c. To determine which means are different, we can conduct a post-hoc analysis.

One common post-hoc test is the Tukey HSD test.

Using the Tukey HSD test, we can calculate the critical value as:

\(q_crit = q(1 - \alpha, df_error, k)\)

α is the significance level, \(df_error\)is the degrees of freedom for error, and k is the number of groups.

α = 0.05, \(df_error\)= 12, and k = 4. Plugging in the values, we get:

\(q_crit = q(0.95, 12, 4) = 3.880\)

The differences between all pairs of means and their standard errors:

     Difference              Std. Error

         0 - 1                        2.124

         0 - 2                       2.124

        0 - 3                        2.382

        1 - 2                         2.124

         1 - 3                        2.382

        2 - 3                       2.382

To determine which means are significantly different, we compare the absolute values of the differences to \(q_crit\) times their corresponding standard errors.

If the absolute value of the difference is greater than \(q_crit\)times the standard error, then the means are significantly different.

In this case, we see that the absolute values of all the differences are greater than\(q_crit\)times their corresponding standard errors.

The means are significantly different from each other.

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Data support do not have enough evidence to support the claim that the population variances are not equal.

To test the claim that the population variances are not equal, we can use the F-test for the equality of variances. The test statistic is:

F = \(s1^2 / s2^2\)

where \(s1^2\) is the sample variance of sample 1, and \(s2^2\) is the sample variance of sample 2. Under the null hypothesis of equal variances, F follows an F-distribution with (n1-1) and (n2-1) degrees of freedom.

Plugging in the given values, we get:

F = 4.1 / 9.2 = 0.445Using a calculator or a table for the F-distribution, we can find that the critical value of F with (12-1) and (25-1) degrees of freedom at a 5% level of significance is 0.41.

Since the calculated F-value is greater than the critical value, we fail to reject the null hypothesis that the population variances are equal. Therefore, we do not have enough evidence to support the claim that the population variances are not equal.

a. We can construct the ANOVA table as follows:

Source | SS | df | MS | F

Between | 267.58 | 3 | 89.193 | 8.498

Within | 41.578 | 16 | 2.5999 |

Total | 309.158| 19 | |

where SS is the sum of squares, df is the degrees of freedom, MS is the mean square, and F is the F-statistic.

The total sum of squares is SST =\(Σ(xi - xbar)^2\) = 309.158, where xi is the i-th observation and xbar is the overall sample mean.

The between-group sum of squares is SSB =\(Σni(xi - xbar_i)^2\), where ni is the sample size of group i and xbar_i is the sample mean of group i. Plugging in the given values, we get:

SSB = \(4(13-1.5)^2 + 4(25-1.5)^2 + 4(18.25-1.5)^2 + 4(11-1.5)^2 = 267.58\)

The within-group sum of squares is SSW = SST - SSB = 41.578.

The degrees of freedom for between groups is dfB = k-1 = 4-1 = 3, where k is the number of groups. The degrees of freedom for within groups is dfW = N - k = 19 - 4 = 15, where N is the total sample size.

The mean square for between groups is MSB = SSB / dfB = 89.193. The mean square for within groups is MSW = SSW / dfW = 2.5999.

b. To test the null hypothesis that the group means are equal, we can use the F-test for one-way ANOVA. The test statistic is:

F = MSB / MSW

Under the null hypothesis of equal means, F follows an F-distribution with (k-1) and (N-k) degrees of freedom.

Plugging in the values from the ANOVA table, we get:

F = 89.193 / 2.5999 = 34.276

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P-value = 0.0384

As P-value < 0.05, reject the null hypothesis.

What is test statistic?

A statistic (a number obtained from the sample) used in statistical hypothesis testing is known as a test statistic. Usually, a hypothesis test is described in words.

A test statistic is a figure obtained from a statistical analysis. It explains how distant your observed data is from the null hypothesis, which states that there is no correlation between the variables or distinction between the sample groups.

The alternative and null hypotheses are listed below.

Lack of hypothesis H0: μ = 13

Ha: 13 Alternative Hypothesis

Statistical test, z = (xbar - mu)/(sigma/sqrt(n))

z = (11 - 13)/(8/sqrt(50))

z = -1.77

Region of Rejection

For α= 0.05, this is a left-tailed test.

Z has a critical value of -1.645.

Therefore, if z -1.645, reject H0 and accept the null hypothesis.

P-value Approach

P-value = 0.0384

As P-value < 0.05, reject the null hypothesis

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Slope can be calculated using the formula: m= \(\frac{y2 - y1}{x2 - x1}\)

y1/x1 represents the first number in the bracket

y2/x2 represents the second number in the bracket

Calculation

m = \(\frac{y2 - y1}{x2 - x1}\)

m =\(\frac{4 - (-2)}{(-9)-3}\)

m= 6/-12

m= -0.5 or -1/2

Therefore, the answer is B.

1.) The value of X would be = 3cm. That is option A.

2.). The value of X (in cm) would be = 4cm. That is option B.

For question 1.)

Given that ∆ABC≈∆PQR

Scale factor = larger dimension/smaller dimension

= 6/4.5 = 1.33

The value of X= 4÷ 1.33 = 3cm

For question 2.)

To calculate the value of X the formula that should be used is given as follows:

PB/PB+BR = AB/AB+QR

where;

PB= 3.2

BR = 4.8

AB = 2

QR= X

That is;

3.2/4.8+3.2= 2/2+X

3.2(2+X) = 2(4.8+3.2)

6.4+3.2x = 16

3.2x= 16-6.4

X= 12.8/3.2 = 4cm.

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Hello,

\(7 \sqrt{8} = \sqrt{7.7.8} = \sqrt{392} \)

Býe býe.

If you are told that a 20 kilogram object is raised by 10 meters, you know that (b) the mass of the object is 20 kilograms.

The force of gravity, also known as gravitational force, is the force that attracts two objects with mass towards each other.

AS we all know that Mass refers to the amount of matter an object contains, and is measured in kilograms. Weight, on the other hand, refers to the force of gravity on an object, and is measured in newtons.

Now, let's look at the options provided.

Option b states that the mass of the object is 20 kilograms, which is correct. This means that the object contains 20 kilograms of matter, regardless of its location or gravitational force acting on it.

In conclusion, we can determine from the given information that the mass of the object is 20 kilograms. However, we cannot determine the force of gravity acting on the object without additional information.

To calculate the force of gravity on an object, we can use the formula

Fg = mg,

where Fg is the force of gravity, m is the mass of the object, and g is the acceleration due to gravity (approximately 9.81 m/s² on Earth).

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Answer:

B i think

Step-by-step explanation:

b

Answer: The square root of 15 is a rational number

explanation: if 15 is a perfect square. ... Since 15 is not a perfect square, it is an irrational number. This means that the answer to the square root of 15 will have an infinite number of decimals. The decimals will not terminate and you cannot make it into an exact fraction.

The widths of Kyle and Myla's boxes are both 2ft respectively.

For Kyle;

The volume of his storage box = 12ft³

The length of the box = 2ft

The height of the box = 3ft

The width of the box = ?

But volume of a box = length×width×height

12 = 2×3×width

make width the subject of formula;

Width = 12/6 = 2 ft

For Myla;

The volume of his storage box = 16ft³

The length of the box = 2ft

The height of the box = 4ft

The width of the box = ?

But volume of a box = length×width×height

16= 2×4×width

make width the subject of formula;

Width = 16/8 = 2 ft

Therefore, the width of the both boxes are the same in measurement.

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The margin of error for the population mean is approximately 3.475 minutes.

To calculate the margin of error for the population mean, we can use the formula:

Margin of Error = Critical Value * Standard Error

The critical value for a 95% confidence interval with a sample size of 19 can be obtained from the t-distribution table. The degrees of freedom for this calculation would be n - 1 = 18.

Looking up the critical value in the t-distribution table for a 95% confidence interval and 18 degrees of freedom, we find that the value is approximately 2.101.

The standard error can be calculated by dividing the standard deviation by the square root of the sample size:

Standard Error = Standard Deviation / √(Sample Size)

Plugging in the values, we get:

Standard Error = 7.2 / √(19) ≈ 1.653

Now we can calculate the margin of error:

Margin of Error = 2.101 * 1.653 ≈ 3.475

Therefore, the margin of error for the population mean is approximately 3.475 minutes.

Interpretation:

The 95% confidence interval for the population mean commute time is (26.9, 33.9) minutes. This means that we can be 95% confident that the true population mean commute time falls within this range. Additionally, the margin of error of 3.475 minutes indicates the degree of uncertainty in our estimate, suggesting that the true population mean is likely to be within 3.475 minutes of the sample mean of 30.4 minutes.

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Answer:

\(\frac{y^{2}}{2x}\)

Step-by-step explanation:

a) simplify

\(\frac{y^{2} }{2x}\)

Answer:

ez y² /2x

Step-by-step explanation: