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4 years ago

In 1925, Zbigniew Morón published a rectangle that could be dissected into nine different sized squares as shown in the diagram.

Mathematics

1 answer:

Vlada [557]4 years ago

8 0

Answer:

Area of the rectangle = 1056 square units

Step-by-step explanation:

Rectangle published could be dissected into nine different squares with different sizes.

Area of the squares with different measure of sides will be,

For side length = 1 unit

Area of the square = (Side)²

= 1²

= 1 square units

For side length = 4 units

Area of the square = 4² = 16 units²

For side length = 7 units

Area of the square = 7² = 49 units²

For side length = 8 units

Area of the square = 8² = 64 units²

For side length = 9 units

Area of the square = 9² = 81 square units

For side length = 10 units

Area of the square = 10² = 100 square units

For side length = 14 units

Area of the square = 14² = 196 square units

For side length = 15 units

Area of the square = 15² = 225 square units

For side length = 18 units

Area of the square = 18² = 324 square units

Total area of the rectangle by adding these 9 squares

= 1 + 16 + 49 + 64 + 81 + 100 + 196 + 225 + 324

= 1056 square units

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A school has 200 students and spends $40 on supplies for each student. The principal expects the number of students to increase

Xelga [282]

Answer:

$\mathbf{S(t)=200(\frac{105}{100})^{x}}$

$\mathbf{A(t)=40(\frac{98}{100})^{x}}$

$\mathbf{E(t)=S(t) \cdot A(t)=200(\frac{105}{100})^{x} \cdot 40(\frac{98}{100})^{x}=8000(\frac{10290}{10000})^{x}}$

Step-by-step explanation:

<h3>The predicted number of students over time, S(t) </h3>

Rate of increment is 5% per year.

A function 'S(t)' which gives the number of students in school after 't' years.

S(0) means the initial year when the number of students is 200.

S(0) = 200

S(1) means the number of students in school after one year when the number increased by 5% than previous year which is 200.

S(1) = 200 + 5% of 200 = $200+\frac{5}{100}\time200$ = $200(1+\frac{5}{100})$ = $200(\frac{105}{100})$

S(2) means the number of students in school after two year when the number increased by 5% than previous year which is S(1)

S(2) = S(1) + 5% of S(1) = $\textrm{S}(1)(\frac{105}{100})$ = $200(\frac{105}{100})(\frac{105}{100})$ = $200(\frac{105}{100})^{2}$

Similarly $\mathbf{S(x)=200(\frac{105}{100})^{x}}$

<h3>The predicted amount spent per student over time, A(t) </h3>

Rate of decrements is 2% per year.

A function 'A(t)' which gives the amount spend on each student in school after 't' years.

A(0) means the initial year when the number of students is 40.

A(0) = 40

A(1) means the amount spend on each student in school after one year when the amount decreased by 2% than previous year which is 40.

A(1) = 40 + 2% of 40 = $40-\frac{2}{100}\time40$ = $40(1-\frac{2}{100})$ = $40(\frac{98}{100})$

A(2) means the amount spend on each student in school after two year when the amount decreased by 2% than previous year which is A(1)

A(2) = A(1) + 2% of A(1) = $\textrm{A}(1)(\frac{98}{100})$ = $40(\frac{98}{100})(\frac{98}{100})$ = $40(\frac{98}{100})^{2}$

Similarly $\mathbf{A(x)=40(\frac{98}{100})^{x}}$

<h3>The predicted total expense for supplies each year over time, E(t)</h3>

Total expense = (number of students) × (amount spend on each student)

E(t) = S(t) × A(t)

$\mathbf{E(t)=S(t) \cdot A(t)=200(\frac{105}{100})^{x} \cdot 40(\frac{98}{100})^{x}=8000(\frac{10290}{10000})^{x}}$

$\mathbf{E(t)=8000(\frac{10290}{10000})^{x}}$

(NOTE : The value of x in all the above equation is between zero(0) to ten(10).)

6 0

3 years ago

Read 2 more answers

Lisa is making trail mix for her camping trip. Lisa mixes 2 cups of peanuts, 4 cups of raisins, and 0.5 cup of chocolate chips.

jeyben [28]

Add the cups all together

7 0

3 years ago

Is square root of 36 plus 3 a rational or irrational number?

pshichka [43]

Answer:

The answer is D

Step-by-step explanation:

7 0

3 years ago

In a multiple regression equation, two independent variables are considered, and the sample size is 30. The regression coefficie

MAXImum [283]

Answer:

Both the variables are important for the regression analysis and cannot be deleted.

Step-by-step explanation:

(1)

The hypothesis for for the testing of coefficient β₁ are:

<em>H</em>₀: β₁ = 0 vs. <em>H</em>ₐ: β₁ ≠ 0

The test statistic is:

$t=\frac{b_{1}}{S_{b_{1}}} =\frac{2.815}{0.75}= 3.753$

It is provided that H₀ is rejected if <em>t</em> > 2.042.

The test statistic value, <em>t</em> = 3.753 > 2.042.

Thus, the null hypothesis is rejected.

<u>Conclusion:</u>

There is a significant relationship between the regression variable and the dependent variable.

(2)

The hypothesis for for the testing of coefficient β₂ are:

<em>H</em>₀: β₂ = 0 vs. <em>H</em>ₐ: β₂ ≠ 0

The test statistic is:

$t=\frac{b_{2}}{S_{b_{2}}} =\frac{-1.249}{0.41}= -3.046$

It is provided that H₀ is rejected if <em>t</em> < -2.042.

The test statistic value, <em>t</em> = -3.046 < -2.042.

Thus, the null hypothesis is rejected.

<u>Conclusion:</u>

There is a significant relationship between the regression variable and the dependent variable.

Thus, both the variables are important for the regression analysis and cannot be deleted.

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3 years ago

Please put a picture

cupoosta [38]

Hope this helps you with your questions.

8 0

3 years ago