Factor Completely [tex]3x^{2} -5x+2[/tex]

Answer:

No 1:85

no2:95

no3:96

no4 :78

no5:98

no6:100

no7:10999

no8:200

no9:48

no10:56

The "Fundamental Statistics for the Behavioral Sciences" 9th edition provides a comprehensive guide to the statistical methods used in the behavioral sciences. The book covers important topics such as descriptive statistics, probability, hypothesis testing, and regression analysis.

It also includes numerous examples and exercises to help readers practice and apply these concepts. The answers to the exercises are provided at the end of the book, allowing readers to check their work and ensure that they understand the material. This edition is an essential resource for students and researchers in the behavioral sciences who want to develop a strong foundation in statistics and its application to their field.
"Fundamental Statistics for the Behavioral Sciences" is a textbook that teaches essential statistical concepts and techniques for students in behavioral science fields. The 9th edition covers topics like descriptive statistics, probability, hypothesis testing, and inferential statistics.

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The Fundamental Statistics for the Behavioral Sciences 9th edition is a college-level textbook focusing on different concepts in statistics, as applicable to behavioral sciences. The book helps students learn and apply statistical concepts through examples and exercises. Available on OpenStax, it supports learning using calculators and statistical software.

The textbook Fundamental Statistics for the Behavioral Sciences 9th edition covers diverse topics in statistics, with a focus on their application to the behavioral sciences. The chapters of the book include key statistics concepts, like Sampling and Data, Descriptive Statistics, Probability Topics, Discrete Random Variables, Continuous Random Variables, Normal Distribution, The Central Limit Theorem, Confidence Intervals, Hypothesis Testing with one and two samples, The Chi-Square Distribution, Linear Regression and Correlation, and F Distribution and One-Way ANOVA. The textbook helps students calculate degrees of freedom, test statistics, and p-values both manually and using calculators or statistical software. Through examples and exercises, students reinforce their understanding of statistics concepts applied to behavioral science data. This textbook is available for free in web view or PDF on OpenStax.

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We start by using the chain rule to find the derivative of w with respect to t: dw/dt = (∂w/∂x) (dx/dt) + (∂w/∂y) (dy/dt) + (∂w/∂t)

dw/dt = 320 when t = 1.

To find ∂w/∂x, we treat y and t as constants and differentiate w = x^2 y^2 t with respect to x:

∂w/∂x = 2xy^2 t

To find ∂w/∂y, we treat x and t as constants and differentiate w = x^2 y^2 t with respect to y

∂w/∂y = 2x^2 yt

To find ∂w/∂t, we treat x and y as constants and differentiate w = x^2 y^2 t with respect to t:

∂w/∂t = x^2 y^2

Substituting the given values x = 4t and y = 2t, we get:

∂w/∂x = 2(4t)(2t)^2 t = 32t^4

∂w/∂y = 2(4t)^2 (2t) t = 64t^4

∂w/∂t = (4t)^2 (2t)^2 = 64t^4

Using these values, we can write:

dw/dt = (∂w/∂x) (dx/dt) + (∂w/∂y) (dy/dt) + (∂w/∂t)

= (32t^4)(4) + (64t^4)(2) + (64t^4)

= 320t^4

Finally, substituting t = 1, we get:

dw/dt = 320(1)^4 = 320

Therefore, dw/dt = 320 when t = 1.

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The researcher should conclude that there is strong evidence which practice improves performance.

The researcher's hypothesis is that practice will improve performance, so they are conducting a one-tailed test.

The critical t-value for this test with a significance level of 0.05 and degrees of freedom is equal to the sample size minus one would be 1.96.

The observed t-value is -7.42 which means that the difference between the pre-practice and post-practice scores is much larger than what would be expected by chance.

This concept suggests that there is strong evidence that practice did indeed improve performance.

For make a decision about the hypothesis,

the researcher needs to compare the observed t-value to the critical t-value.

Since the observed t-value (-7.42) is much smaller in magnitude than the critical t-value (1.96).

The researcher can reject the null hypothesis that there is no difference between pre-practice and post-practice performance.

Therefore, the researcher should conclude that there is strong evidence which practice improves performance.

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For two mutually exclusive events A and B, the formula that can be use to find the union of the events is a. P(AUB) = P(A) x P(B)

The basic meaning of exclusive event is the events are unique and there will be no set of common elements between them.

Since A and B are mutually exclusive, the probability of both events occurring together is zero like:

P(A∩B) = 0.

So, the formula to find the union of A and B is given by:

P(AUB) = P(A) + P(B) - P(A∩B)

P(AUB) = P(A) + P(B) - 0

P(AUB) = P(A) + P(B)

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Im not 100% sure but the best answer from what I see is A

The nearest integer 136,043 people. To find the total population within a 3-kilometer radius of the city center, we need to integrate the population density function (∂(x, y)) over the circular region with a radius of 3 kilometers.

Given that the population density (∂) is defined as 7000 (x^2 + y^2)^-0.2 people per square kilometer, we can express the population density as a function of the distance from the origin (r).

Let's perform the integration using polar coordinates, where x = rcos(θ) and y = rsin(θ):

∂(r) = 7000[tex](r^2)^-0.2[/tex]

∂(r) = 7000[tex]r^(-0.4)[/tex]

Now, we need to integrate this population density function (∂(r)) over the circular region with a radius of 3 kilometers.

To do this, we integrate from 0 to 2π for the angle (θ), and from 0 to 3 kilometers for the radius (r).

Total population = ∫∫R ∂(r) r dr dθ

Total population = ∫[0 to 2π] ∫[0 to 3] 7000 [tex]r^(-0.4)[/tex] r dr dθ

Simplifying the integral:

Total population = 7000 ∫[0 to 2π] ∫[0 to 3] [tex]r^(0.6)[/tex] dr dθ

Total population = 7000 ∫[0 to 2π] [([tex]r^(1.6)[/tex])/(1.6)]|[0 to 3] dθ

Total population = 7000 [tex](1.6)^(-1)[/tex]∫[0 to 2π] [([tex]3^(1.6))[/tex]/(1.6)] dθ

Total population = (7000/1.6) [tex](3^(1.6))[/tex] ∫[0 to 2π] dθ

Total population = (7000/1.6) [tex](3^(1.6)[/tex]) (θ)|[0 to 2π]

Total population = (7000/1.6) ([tex]3^(1.6)[/tex]) (2π)

Now, let's evaluate this expression:

Total population ≈ (7000/1.6) ([tex]3^(1.6)[/tex]) (2π)

Total population ≈ 136042.195 people

Rounding up to the nearest integer, the total population within a 3-km radius of the city center is approximately 136,043 people.

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To find the point on the line -3x + 5y - 4 = 0 which is closest to the point (-4, 2), we can use the formula for the distance from a point to a line.First, we need to find the equation of a line perpendicular to -3x + 5y - 4 = 0 that passes through (-4, 2). The slope of -3x + 5y - 4 = 0 is 3/5, so the slope of the perpendicular line is -5/3.

The equation of the perpendicular line passing through (-4, 2) can be found using the point-slope form:

y - 2 = (-5/3)(x + 4)

y = (-5/3)x - 22/3

Now we can find the intersection of the two lines by solving the system of equations:

-3x + 5y - 4 = 0

y = (-5/3)x - 22/3

Substituting y from the second equation into the first, we get:

-3x + 5((-5/3)x - 22/3) - 4 = 0

-18x - 74 = 0

x = -37/9

Substituting x back into the second equation, we get:

y = (-5/3)(-37/9) - 22/3 = -7/3

So the point on the line -3x + 5y - 4 = 0 that is closest to (-4, 2) is (-37/9, -7/3).

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In order to find a 99% confidence interval for the proportion of students who take notes, the student would need to follow certain steps. First, they would need to obtain a random sample of students and record whether or not each student takes notes. Based on this data, they would calculate the sample proportion, which is the number of students who take notes divided by the total number of students in the sample.

Next, they would use a statistical formula to calculate the margin of error, which is the amount by which the sample proportion could vary from the true proportion in the population. They would also use a table or calculator to find the critical value for a 99% confidence level.

Finally, the student would use these values to construct the confidence interval, which is the range of values that is likely to contain the true proportion of students who take notes in the population with 99% confidence. This interval would be expressed as a range of values, such as "between 0.55 and 0.75," and would indicate the level of uncertainty in the estimate based on the sample data.

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To find the divergence of the vector field F(x, y) = −y i + x j / x2 + y2, we need to calculate the partial derivatives of its components with respect to x and y and then take their sum:

∂F/∂x = ∂/∂x (−y) i + ∂/∂x (x) j / x2 + y2

= 0 + 1/(x2 + y2) j

∂F/∂y = ∂/∂y (−y) i + ∂/∂y (x) j / x2 + y2

= −1/(x2 + y2) i + 0

Therefore, the divergence of F is:

div F = ∇ · F = ∂F/∂x + ∂F/∂y

= 1/(x2 + y2) j − 1/(x2 + y2) i

= (1/(x2 + y2), −1/(x2 + y2))

Thus, the divergence of the vector field F(x, y) = −y i + x j / x2 + y2 is the vector (1/(x2 + y2), −1/(x2 + y2)).

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The value of  r(s(-4)) is -32 and the value of composite function , hoh⁻¹(2) is -4/7.

Given that r and s are functions.

r(x)=-x-1

s(x)=2x²-1

We have to find the value of r(s(-4)):

s(-4)=2(-4)²-1

=32-1

=31

Now r(s(-4))=r(31)=-31-1=-32

So the value of  r(s(-4)) is -32.

The one to one functions g and h are defined as follows

g={(3, 8), (4, 7), (6, -5), (7, 4), (8, -9)}

To find g⁻¹(x), we switch the x and y values:

{(8, 3), (7, 4), (-5, 6), (4, 7), (-9, 8)}.

So, g⁻¹(x) = {(8, 3), (7, 4), (-5, 6), (4, 7), (-9, 8)}.

The function h(x) = -x + 10/7.

To find h⁻¹(x), we switch the x and y values and solve for y:

x = -y + 10/7

x - 10/7 = -y

y = -x + 10/7

So, h⁻¹(x) = -x + 10/7.

To find hoh⁻¹(2), we substitute h⁻¹(x) = 2 into h(x):

h(2) = -2 + 10/7

h(2) = -2 + 10/7 = -4/7

Therefore, hoh⁻¹(2) = -4/7.

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(a) We find that t ≈ 5.7 years. So the car will be worth $9000 when it is approximately 5.7 years old. (b) we find that t ≈ 5.0 years. So the car will be worth $8000 when it is approximately 5.0 years old. (c) we find that t ≈ 13.4 years. So the car will be worth $1000 when it is approximately 13.4 years old.

To find when the car will be worth a certain amount, we can set V(t) equal to that amount and solve for t.
(a) To find when the car will be worth $9000:
$9000 = [tex]14,704(0.84)^t[/tex]
Divide both sides by 14,704:
0.612 = [tex]0.84^t[/tex]
Take the logarithm of both sides (using either base 10 or natural logarithm):
log(0.612) = t log(0.84)
Solve for t:
t = log(0.612) / log(0.84)
Using a calculator, we find that t ≈ 5.7 years. So the car will be worth $9000 when it is approximately 5.7 years old.
(b) To find when the car will be worth $8000:
$8000 = [tex]14,704(0.84)^t[/tex]
Following the same steps as before, we find that t ≈ 5.0 years. So the car will be worth $8000 when it is approximately 5.0 years old.
(c) To find when the car will be worth $1000:
$1000 = [tex]14,704(0.84)^t[/tex]
Following the same steps as before, we find that t ≈ 13.4 years. So the car will be worth $1000 when it is approximately 13.4 years old.

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The best measures of center for the data set in the dot plot is mean

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

The dot plot

Where we have the properties to be

When a dataset has an outlier i.e. extreme values, the best measure of center to use is the median

Otherwise, we use the mean

Hence, the best measure is the mean

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If she follows the path shown by the dotted line in the graph, the distance from her house to the store would be = 128m. That is option B.

To calculate the distance between her house and the store the Pythagorean formula should be used which is given as follows;

C² = a² + b²

where;

a= 80

b= 100

c= ?

That is;

c²= 80²+100²

= 6400+10000

= 16,400

c = √16400

= 128.1m

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The objective function q=[tex]x^{2}[/tex] y can be written as q=[tex]x^{2}[/tex](22-x) in terms of x, and as q=[tex](22-y)^2[/tex] y in terms of y, given that x+y=22.

To write the objective function first in terms of x, we need to solve the equation x+y=22 for y. Subtracting x from both sides, we get y=22-x. We can then substitute this expression for y into the objective function q=[tex]x^{2}[/tex] y, giving q=[tex]x^2(22-x)[/tex].
To write the objective function in terms of y, we need to solve the equation x+y=22 for x. Subtracting y from both sides, we get x=22-y. We can then substitute this expression for x into the objective function q=[tex]x^{2}[/tex] y, giving q=[tex](22-y)^2[/tex] y.

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The complementary error function is a function commonly used in communications and signal processing to compute the tail probabilities of Gaussian random variables. It is defined as:

Q(x) = 1/√(2π) ∫x to ∞ e^(-t^2/2) dt

where x is a real number. Geometrically, Q(x) represents the area under the standard normal probability density function to the right of x. This means that Q(x) gives the probability that a standard normal random variable takes on a value greater than x.

The complementary error function is related to the error function, erf(x), which is defined as:

erf(x) = 2/√(π) ∫0 to x e^(-t^2) dt

In fact, Q(x) can be expressed in terms of erf(x):

Q(x) = 1/2 erfc(x/√2)

where erfc(x) is the complementary error function.

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By answering the presented question, we may conclude that As a result, the slope of  y3= -4(x - 5) is -4.

Here, we have,

The slope of a line indicates how steep it is. The term "gradient overflow" refers to a mathematical equation for the gradient (the change in y divided by the change in x).

The slope is defined as the ratio of the vertical change (rise) between two places to the horizontal change (run). The slope-intercept form of an equation is used to express a straight line's equation, which is written as y = mx + b.

The y-intercept is found where the slope of the line is m, b is b, and (0, b). For example, the slope and y-intercept of the equation y = 3x - 7 (0, 7). The slope of the line is m. b is b at the y-intercept, and (0, b).

The above equation is in point-slope form: y -y1 = m(x -x1 ), where (x1,y1 ) is a point on the line and m is the slope.

We can see by comparing the provided equation to the point-slope form that (x1,y1) = (5, 3) and m = -4.

As a result, the slope of y3 = -4(x - 5) is -4.

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complete question;

Linear Functions

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What is the slope of the equation y-3 = -4(x - 5)?

The factored function is given as follows:

[tex]x^4 + 2x^3 - 20x^2 + 64x - 32 = (x^2 + 6x - 4)(x^2 - 4x + 8)[/tex]

The function for this problem is defined as follows:

[tex]y = x^4 + 2x^3 - 20x^2 + 64x - 32[/tex]

The zeros are given as follows:

Hence the function is factored as follows:

[tex]x^4 + 2x^3 - 20x^2 + 64x - 32 = (ax^2 + bx + c)(x - 2 + 2i)(x - 2 - 2i)[/tex]

[tex]x^4 + 2x^3 - 20x^2 + 64x - 32 = (ax^2 + bx + c)(x^2 - 4x + 8)[/tex]

[tex]x^4 + 2x^3 - 20x^2 + 64x - 32 = ax^4 + (-4 + b)x^3 + \cdots + 8c[/tex]

Hence the value of a is given as follows:

a = 1.

The value of b is given as follows:

-4 + b = 2

b = 6.

The value of c is given as follows:

8c = -32

c = -4.

Hence the factored expression is of:

[tex]x^4 + 2x^3 - 20x^2 + 64x - 32 = (x^2 + 6x - 4)(x^2 - 4x + 8)[/tex]

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The value of 6⅔ ÷ 12 is 5/9

The mathematical “operation” refers to calculating a value using operands and a math operator.

Mathematical operations include; Addition subtraction, multiplication, division. This operations are used to define the relationship between two terms.

PEDMAS is used for orderly arrangements for the operation.

6²/3 ÷ 12

We first convert the mixed fraction into improper fraction.

= 20/3 × 1/12

= 20/36

divide through by 4, then we have

= 5/9

Therefore the value of 6⅔ ÷ 12 is 5/9

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For the quadratic function:

(a) Using the information given, determine that the quadratic function has a vertex at (3, -8). Therefore, the output values at x = 0 and x = 6 are also -8.

Also, since the function is symmetric about the vertex, the outputs at x = 4 and x = 2 are the same as those at x = -1 and x = 1, respectively.

Thus, the missing output values are:

x | -1 | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7

g(x) | 24 | -8 | 0 | -6 | -8 | -6 | 0 | 10 | 48

(b) To find the zeroes of the function, solve for g(x) = 0. Since the vertex is at (3, -8), use the vertex form of the quadratic function:

g(x) = a(x - 3)² - 8

where a = coefficient of the squared term.

To find a, use any of the three points on the graph (0, -8), (1, 0), or (6, -6):

-8 = a(0 - 3)² - 8

a = 8/9

Therefore, the quadratic function is:

g(x) = (8/9)(x - 3)² - 8

To find the zeroes, set g(x) = 0 and solve:

0 = (8/9)(x - 3)² - 8

8 = (8/9)(x - 3)²

9 = (x - 3)²

x = 3 ± 3

Thus, the zeroes of the function are x = 0 and x = 6.

(c) To find the y-intercept, set x = 0 and solve for g(x):

g(0) = (8/9)(0 - 3)² - 8

g(0) = 17

Therefore, the y-intercept is (0, 17).

(d) The vertex of the quadratic function is at (3, -8) and the coefficient of the squared term is positive, which means that the parabola opens downwards. Therefore, the maximum value of the function occurs at the vertex and the range of the function is g(x) ≤ -8 for -1 ≤ x ≤ 7.

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Answer:

-2/7 is 3 and -6 is 2

Step-by-step explanation:

to make a slope perpendicular, you need to swap the numerator and denominator and multiply by negative so - becomes + and + becomes -

Answer:

-2/7 is 3 and -6 is 2

Step-by-step explanation:

The popcorn box would hold 168.75 cubic inches of popcorn when it is full. Rounded to the nearest tenth, the answer is 168.8 cubic inches.

To find the volume of the popcorn box, we need to multiply its length, width, and height. However, we need to make sure that all the dimensions are in the same units before we multiply them.

First, let's convert the mixed numbers to improper fractions:

3 3/4 = 15/4

7 1/2 = 15/2

Now, we have the dimensions in the same units (inches):

Length = 15/4 in

Width = 3 in

Height = 15/2 in

To find the volume, we multiply the three dimensions:

Volume = Length x Width x Height

Volume = (15/4) x 3 x (15/2)

Volume = 168.75 cubic inches

Therefore, the popcorn box would hold 168.75 cubic inches of popcorn when it is full. Rounded to the nearest tenth, the answer is 168.8 cubic inches.

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A couple would probably budget for the wedding if they make $70,000 together, you can use the regression equation obtained from the analysis. The regression equation will provide you with the relationship between the couple's income and the wedding cost.

The excel regression tool using the cost as the dependent variable and the couple's income as the independent variable, only those weddings paid for by the bride and groom. A. Interpret all key regression results, hypothesis tests, and confidence intervals in the output. B. Analyze the residuals to determine if the assumptions underlying the regression analysis are valid. C. Use the standard residuals to determine if any possible outliers exist. D. If a couple makes $70,000 together, how much would they probably budget for the wedding?

Weddings Couple's Income Bride's age Payor Wedding cost Attendance Value Rating

$130,000 22 Bride's Parents $60,700. 00 300 3

$157,000 23 Bride's Parents $52,000. 00 350 1

$98,000 27 Bride & Groom $47,000. 00 150 3

$72,000 29 Bride & Groom $42,000. 00 200 5

$86,000 25 Bride's Parents $34,000. 00 250 3

$90,000 28 Bride & Groom $30,500. 00 150 3

$43,000 19 Bride & Groom $30,000. 00 250 3

$100,000 30 Bride & Groom $30,000. 00 300 3

$65,000 24 Bride's Parents $28,000. 00 250 3

$78,000 35 Bride & Groom $26,000. 00 200 5

$73,000 25 Bride's Parents $25,000. 00 150 5

$75,000 27 Bride & Groom $24,000. 00 200 5

$64,000 25 Bride's Parents $24,000. 00 200 1

$67,000 27 Groom's Parents $22,000. 00 200 5

$75,000 25 Bride's Parents $20,000. 00 200 5

$67,000 30 Bride's Parents $20,000. 00 200 5

$62,000 21 Groom's Parents $20,000. 00 100 1

$75,000 19 Bride's Parents $19,000. 00 150 3

$52,000 23 Bride's Parents $19,000. 00 200 1

$64,000 22 Bride's Parents $18,000. 00 150 1

$55,000 28 Bride's Parents $16,000. 00 100 5

$53,000 31 Bride & Groom $14,000. 00 100 1

$62,000 24 Bride's Parents $13,000. 00 150 1

$40,000 26 Bride's Parents $7,000. 00 50 3

$45,000 32 Bride & Groom $5,000. 00 50 5

Multiple R: The multiple correlation coefficient is 0.819, which indicates a strong positive relationship between couple's income and wedding cost.

R Square: The coefficient of determination is 0.671, which means that approximately 67% of the variation in wedding cost can be explained by couple's income.

Adjusted R Square: The adjusted R square is 0.650, which takes into account the number of independent variables in the model and is slightly lower than the R square.

Standard Error: The standard error of the estimate is 10,101.431, which represents the average deviation of the observed values from the predicted values.

The intercept coefficient is 24525.824, which represents the estimated wedding cost when the couple's income is zero. The coefficient for couple's income is 0.397, indicating that a one-unit increase in couple's income is associated with a $397 increase in wedding cost.

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The derivatives for x, y, and dy/dx are dx/dt = 15t² + 3, dy/dt = 4 - 12t, and dy/dx = (4 - 12t) / (15t² + 3), respectively.

To find dx/dt, we need to take the derivative of x with respect to t:

dx/dt = d/dt (5t³ + 3t) = 15t² + 3

To find dy/dt, we need to take the derivative of y with respect to t:

dy/dt = d/dt (4t - 6t²) = 4 - 12t

To find dy/dx, we need to take the derivative of y with respect to x:

dy/dx = (dy/dt) / (dx/dt)

Substituting the expressions we found above, we get:

dy/dx = (4 - 12t) / (15t² + 3)

Note that dy/dx is a function of t, so its value depends on the value of t at a particular point.

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7. The side lengths can represent a triangle.

8. The side lengths cannot represent a triangle.

9. The side lengths cannot represent a triangle.

In a triangle, the sum of the lengths of the two smaller sides has to be greater than the length of the greater side.

Hence:

7. The side lengths can represent a triangle, as 5 + 4 > 7.

8. The side lengths cannot represent a triangle, as 3 + 7 < 11.

9. The side lengths cannot represent a triangle, as 5 + 10 < 16.

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If the psychologists state in a report that M = 16 and SD = 4, they are reporting sample statistics. The sample statistics are calculated based on the data collected from a sample of participants.

M or the mean is the average of the scores in the sample, and SD or standard deviation is the measure of how spread out the scores are from the mean. These sample statistics provide important information about the sample, which can be used to draw conclusions about the population.

On the other hand, if the psychologists state in a report that p = 16, they are reporting a population parameter. A population parameter is a numerical value that describes a characteristic of a population. In this case, p could refer to the proportion of individuals in the population who exhibit a certain behavior or trait. It is important to note that population parameters are typically unknown and are estimated using sample statistics.

Overall, understanding the difference between sample statistics and population parameters is crucial for interpreting research findings and making informed decisions based on data.

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Using​ Green's Theorem ModifyingAbove ModifyingBelow Contour integral With Upper C f dy minus g dx With font size decreased by 6 ∮Cf dy−g dx​, the total line integral is 0.

To use Green's Theorem to evaluate the line integral, we first need to find the partial derivatives of f and g:
∂f/∂x = 0
∂g/∂y = 0
∂f/∂y = 11x^2
∂g/∂x = -6y^2
Now we can apply Green's Theorem:
∮Cf dy − g dx = ∬D (∂g/∂x − ∂f/∂y) dA
where D is the region enclosed by the contour C.
Since C consists of the upper half of the unit circle and the line segment -1 ≤ x ≤ 1 oriented clockwise, we can split region D into two parts: the upper half of the unit circle and the rectangle -1 ≤ x ≤ 1, 0 ≤ y ≤ 1.
For the upper half of the unit circle, we have x^2 + y^2 = 1 and y ≥ 0. So we can parametrize the curve as x = cos(t), y = sin(t), where t goes from 0 to π. Then we have:
∮Cf dy − g dx = ∫0^π (−6sin^3(t))dt = 0
For the rectangle -1 ≤ x ≤ 1, 0 ≤ y ≤ 1, we have:
∂g/∂x − ∂f/∂y = -12y^2
So the line integral over this part of the contour is:
∮Cf dy − g dx = ∫0^1 ∫−1^1 (−12y^2)dxdy = 0
Therefore, the total line integral is 0.

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Total number of edges new polyhedron have after attaching a regular tetrahedron to each face of a regular icosahedron is equal to 150 edges.

A regular tetrahedron has 4 faces and 6 edges, and a regular icosahedron has 20 faces and 30 edges.

When a regular tetrahedron is attached to each face of a regular icosahedron,.

Add 4 tetrahedral faces and 4 tetrahedral vertices to each of the 20 triangular faces of the icosahedron.

This means that the new polyhedron has 20 × 4 = 80 additional faces, and 4 × 20 = 80 additional vertices.

Each of these new vertices is connected to 3 other vertices, one from the original icosahedron and two from the added tetrahedra.

The number of new edges added is 80 × 3/2 = 120.

The original icosahedron had 30 edges, so the total number of edges in the new polyhedron is 30 + 120 = 150 edges.

Therefore, the new polyhedron formed by attaching a regular tetrahedron to each face of a regular icosahedron has 150 edges.

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