PHYSICS The distance an object falls afterffseconds is given by d= 161? (ignoring air resistance) To find the height of an object launched upward from ground level at a rate of 32 feet per secand, use the expression 32+ - 16+2 where fis the time in seconds. Factor the expression.

The response variable Y that is explained by the variation in the explanatory variable X.

The coefficient of determination, denoted by R², is a measure of the proportion of the variance in the response variable Y that can be explained by the linear relationship with the explanatory variable X. In other words, it represents the fraction of the total variation in the response variable that is explained by the regression model.

Mathematically, R² is defined as the ratio of the explained variance to the total variance:

R² = Explained variance / Total variance

The explained variance is the variation in Y that is explained by the linear relationship with X, and is measured as the sum of squares of the residuals from the regression line. The total variance is the sum of squares of deviations of Y from its mean value.

An R² value of 1 indicates a perfect fit of the regression line to the data, with all the variation in Y being explained by the linear relationship with X. An R² value of 0 indicates no linear relationship between X and Y, and the regression line provides no explanatory power.

Thus, the interpretation of R² is that it provides a measure of the goodness of fit of the regression model and indicates the proportion of variation in the response variable Y that is explained by the variation in the explanatory variable X.

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The probability that the randomly selected point is in the bullseye is 0.75, or 75%.

The area of the bullseye is the difference between the areas of the larger and smaller circles:

[tex]A = \pi r_1^2 - \pi r_2^2[/tex]

where [tex]r_1[/tex] is the radius of the larger circle (8 cm) and [tex]r_2[/tex] is the radius of the smaller circle (4 cm).

[tex]A = \pi(8^2 - 4^2)A = \pi(64 - 16)A = 48\pi[/tex]

The area of the entire target (both circles) is:

[tex]A = \pi r_1^2[/tex]

A = 64π

Therefore, the probability of selecting a point in the bullseye is:

P(bullseye) = A(bullseye) / A(target)

P(bullseye) = (48π) / (64π)

P(bullseye) = 3/4 or 0.75

So the probability that the randomly selected point is in the bullseye is 0.75, or 75%.

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Both statements are true. When events A and B are mutually exclusive, meaning they cannot occur simultaneously, you can use the special rule of addition.

If events A and B are not mutually exclusive, meaning they can occur together, you should use the general rule of addition. The specific rule of addition can only be used when dealing with mutually exclusive events, while the general rule of addition can be used for any two events, whether they are mutually exclusive or not. The specific rule of addition states that the probability of either event A or event B occurring is equal to the sum of their individual probabilities, while the general rule of addition states that the probability of event A or event B occurring is equal to the sum of their individual probabilities minus the probability of their intersection (if they are not mutually exclusive).

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The magnitude of the error is less than [tex]$\$ 0.015 \$$[/tex], which is our final exact answer.

We can use the Mean Value Theorem to estimate the error in approximating [tex]$(128.012)^{\frac{6}{7}}$[/tex] by [tex]$128^{\frac{6}{7}}$[/tex]. Let [tex]$f(x) = x^{\frac{6}{7}}$[/tex] and [tex]$a = 128.012$[/tex]. Then, by the Mean Value Theorem, there exists some [tex]$c$[/tex] between [tex]$a$[/tex] and [tex]$128$[/tex] such that:

[tex]$$\frac{f(a)-f(128)}{a-128}=f^{\prime}(c)$$[/tex]

Taking the absolute value of both sides and rearranging, we get:

[tex]$$|f(a)-f(128)|=|a-128| \cdot\left|f^{\prime}(c)\right|$$[/tex]

Now, we can find [tex]$\$ f^{\prime}(x) \$$[/tex] :

[tex]$$f(x)=x^{\frac{6}{7}}=e^{\frac{6}{7} \ln x}$$[/tex]

Using the chain rule, we get:

[tex]$$f^{\prime}(x)=\frac{6}{7} x^{-\frac{1}{7}} e^{\frac{6}{7} \ln x}=\frac{6}{7} x^{-\frac{1}{7}} f(x)$$[/tex]

Plugging in [tex]$\$ \mathrm{c} \$$[/tex] and simplifying, we get:

[tex]$$|f(a)-f(128)|=|128.012-128| \cdot\left|\frac{6}{7} c^{-\frac{1}{7}}\left(\frac{128.012}{c}\right)^{\frac{6}{7}}\right|$$[/tex]

We want to find an upper bound for this expression, so we will use the fact that [tex]$\$ c \$$[/tex] is between [tex]$\$ 128 \$$[/tex] and [tex]$\$ 128.012 \$$[/tex]. Therefore, we have:

[tex]$$|f(a)-f(128)| < 0.012 \cdot \frac{6}{7} 128^{-\frac{1}{7}}(128.012)^{\frac{6}{7}}$$[/tex]

Plugging in the values, we get:

[tex]$$|f(a)-f(128)| < 0.012 \cdot \frac{6}{7} \cdot 128^{-\frac{1}{7}}(128.012)^{\frac{6}{7}} \approx 0.015$$[/tex]

Therefore, the magnitude of the error is less than [tex]$\$ 0.015 \$$[/tex], which is our final exact answer.

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If Pepe and Leo continue to deposit the same amount of money every month, their balances will be the same and continue to grow at the same rate i.e. Pepe's balance = $3,600 and Leo's balance = $3,600.

If we assume that Pepe and Leo continue to deposit the same amount of money every month and that the interest rate remains constant, we can use a formula to calculate the future value of their savings. The formula for future value is:

FV = PV x (1 + r)n

Where:

FV stands for the savings account's future value.

PV stands for the savings account's initial balance's present value.

The interest rate, r, is considered to be zero in this instance.

The number of months is n.

If we assume that Pepe and Leo deposit $100 each per month, we can use this formula to calculate the future value of their savings after a certain number of months. For example:

After 12 months:

Pepe's balance = $1,200

Leo's balance = $1,200

After 24 months:

Pepe's balance = $2,400

Leo's balance = $2,400

After 36 months:

Pepe's balance = $3,600

Leo's balance = $3,600

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The first two approximations of the root of f(a) using Newton's method starting at x=0 are: X₁ = 1/3 X₂= 19/54

Newton's Method Algorithm: (1) Choose a beginning value x0 (ideally near to a root of f). (2) Create a new estimate xn+1=xnf(xn)f′(xn) for each estimate xn. (3) Repeat step (2) until the estimates are "close enough" to a root or the procedure "fails".

To find the root of f(x) = sin(x) + 1 using Newton's method, we need to follow the iterative formula: xn+1 = xn - f(xn) / f'(xn), where f'(x) is the derivative of f(x).

First, find the derivative of f(x): f'(x) = cos(x)

Now, compute x₁ and x₂ using the formula:

x₁ = x0 - f(x0) / f'(x0) = 0 - (sin(0) + 1) / cos(0) = 0 - 1/1 = -1

x₂ = x1 - f(x1) / f'(x1) = -1 - (sin(-1) + 1) / cos(-1)

The first two approximations of the root of f(a) using Newton's method starting at x=0 are:

X1 = 1/3

X2 = 19/54

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The rectangle which should go in position I is rectangle A.

We are given that;

The rectangles A,B,C and D with numbers

Now,

To take the same the number of side

If we take A on 1 place

F will be on second place

And  B will be on 4th place

Therefore, by algebra the answer will be rectangle A.

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This is because the function f(t) is a constant function, which is an even function and has no odd component.

The half-range Fourier series is a representation of a periodic function over a finite interval, where the function is assumed to be even or odd. In the case of the function f(t) = 0, the function is even and the interval is from 0 to π.

(a) The half-range cosine series:

To find the half-range cosine series, we first need to find the Fourier coefficients:

[tex]a_0 &= \frac{2}{\pi} \int_0^{\pi} f(t) dt = \frac{2}{\pi} \int_0^{\pi} 0 dt = 0 \a_n &= \frac{2}{\pi} \int_0^{\pi} f(t) \cos(nt) dt = \frac{2}{\pi} \int_0^{\pi} 0 \cos(nt) dt = 0 \\[/tex]

Since all the Fourier coefficients are zero, the half-range cosine series for f(t) is:

[tex]$\begin{align*}f(t) &= \frac{a_0}{2} + \sum_{n=1}^{\infty} a_n \cos(nt) \&= 0\end{align*}$[/tex]

b) The half-range sine series:

To find the half-range sine series, we need to find the Fourier coefficients:

[tex]b_n &= \frac{2}{\pi} \int_0^{\pi} f(t) \sin(nt) dt = \frac{2}{\pi} \int_0^{\pi} 0 \sin(nt) dt = 0 \\[/tex]

Since all the Fourier coefficients are zero, the half-range sine series for f(t) is:

[tex]$\begin{align*}f(t) &= \sum_{n=1}^{\infty} b_n \sin(nt) \&= 0\end{align*}$[/tex]

Therefore, both the half-range cosine series and the half-range sine series for f(t) are zero. This is because the function f(t) is a constant function, which is an even function and has no odd component.

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The probability of 3 dying of SIDS in this situation is approximately 0.000227. The number of SIDS cases in this hospital is significantly higher than the expected rate.

a. The probability of 3 infants dying of SIDS in this situation can be calculated using the binomial probability formula:
P(X=k) = C(n,k) * p^k * (1-p)^(n-k)
Where:
P(X=k) is the probability of k successes (SIDS cases) in n trials (infants),
C(n,k) is the number of combinations of n items taken k at a time,
p is the probability of SIDS (0.0001),
n = 100 infants,
k = 3 SIDS cases.
P(3 SIDS cases in 100 infants) = C(100,3) * (0.0001)^3 * (1-0.0001)^(100-3)
After calculating, the probability is approximately 0.000227.

b. In this situation, it is alarming that many infants died of SIDS, as the probability of 3 deaths in 100 infants is very low (0.000227), much lower than the prevalence of 0.01%. This indicates that the number of SIDS cases in this hospital is significantly higher than the expected rate.

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Answer:

[tex].12 \times 360 \: degrees = 43.2 \: degrees[/tex]

The answer for the following inequality expressed in interval notation is (-77/3, infinity)

To solve the inequality 2x - 75 < 5x + 2,

we need to isolate the variable x on one side of the inequality sign.

Starting with 2x - 75 < 5x + 2:

Subtracting 2x from both sides:
-75 < 3x + 2

Subtracting 2 from both sides:
-77 < 3x

Dividing both sides by 3 (and flipping the inequality sign because we are dividing by a negative number):
x > -77/3

So the solution to the inequality is x > -77/3.

Expressing this in interval notation, we have:

(-77/3, infinity)

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To answer this question, we'll use the exponential distribution and the concept of the probability density function (pdf). Let X be the time until failure of a single device, with a mean lifetime of 20 months. The exponential distribution has the following pdf:

f(x) = (1/μ) * e^(-x/μ),

where μ is the mean lifetime (20 months in this case).

Now, let's find the probability that the first failure occurs at w months among the 5 independent devices. For this, we need to calculate the probability that none of the other 4 devices fail before w months and that the first device fails at w months.

The probability that a single device does not fail before w months is given by the complementary cumulative distribution function (ccdf) of the exponential distribution:

P(X > w) = e^(-w/μ).

Since the devices are independent, the probability that all 4 devices do not fail before w months is:

P(All 4 devices survive > w) = (e^(-w/μ))^4.

Now, the probability that the first device fails at w months is given by the pdf of the exponential distribution:

P(X = w) = (1/μ) * e^(-w/μ).

Finally, we multiply the two probabilities to find the chance that the first failure occurs at w months:

P(First failure at w) = P(All 4 devices survive > w) * P(X = w)
= (e^(-w/μ))^4 * (1/μ) * e^(-w/μ)
= (1/20) * e^(-5w/20).

Thus, the chance that the first failure will occur at w months is given by the expression (1/20) * e^(-5w/20).

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Rounding to two decimal places, the rate of change of blood pressure with respect to time after 31 years is approximately 0.81 millimeters per year.

The mathematical model relating systolic blood pressure and age is given as P(x)=a+b*ln(x+1), we can differentiate it with respect to time (t) to find the rate of change of pressure with respect to time:

dP/dt = dP/dx * dx/dt

Here dx/dt is the rate of change of age with respect to time, which is simply 1 year per year or 1.

Taking the derivative of P(x) with respect to x, we get:

dP/dx = b/(x+1)

Substituting the given values for a and b, we have:

P(x) = 43 + 25ln(x+1)

dP/dx = 25/(x+1)

Therefore, the rate of change of pressure with respect to time after 31 years is:

dP/dt = dP/dx * dx/dt = (25/(31+1)) * 1 = 0.8065

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The total revenue function, given the marginal revenue function MR = 300 - 13q² + 16q³, is:

R(q) = 300q - (13/3)q³ + 4q⁴ + 28⅔

The process of determining the total revenue function requires us to integrate the marginal revenue function with respect to the quantity q. The given marginal revenue function is:

MR = 300 - 13q² + 16q³.

Applying integration of MR, we obtain the total revenue function, R(q) by integrating each term separately as follows:

R(q) = ∫300 dq - ∫13q² dq + ∫16q³ dq

R(q) = 300q - (13/3)q³ + (16/4)q⁴ + C

Which when simplified becomes:

R(q) = 300q - (13/3)q³ + 4q⁴ + C  

To find the constant value C for a case where the total revenue generated through one unit sale (q=1) is $3,316, we substitute these values into the above function expression and then solve for C. Consequently, C was found to be equal to $29-(1/3).

The total revenue function, given the marginal revenue function MR = 300 - 13q² + 16q³, is:

R(q) = 300q - (13/3)q³ + 4q⁴ + 28⅔

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The statement "an endomorphism is injective if and only if it is not an eigenvalue" is not true in general.

An endomorphism is a linear map from a vector space to itself. An endomorphism is said to be injective if it preserves distinctness of elements, i.e., if it maps different vectors to different vectors. On the other hand, an eigenvalue of an endomorphism is a scalar that satisfies a certain equation involving the endomorphism and a non-zero vector called an eigenvector.

Now, the statement "an endomorphism is injective if and only if it is not an eigenvalue" is not true in general. In fact, the two concepts are not directly related. It is possible for an endomorphism to be injective and have eigenvalues, and it is possible for an endomorphism to not have eigenvalues and not be injective.

However, if we consider a specific case where the endomorphism is a linear transformation on a finite-dimensional vector space, then we can make the following statement: "an endomorphism is injective if and only if it does not have 0 as an eigenvalue." This statement is true because an endomorphism is injective if and only if its kernel (the set of vectors it maps to 0) is trivial (only the zero vector). This happens if and only if 0 is not an eigenvalue, since an eigenvalue of 0 means that there exists a non-zero vector that is mapped to 0.

In summary, the statement "an endomorphism is injective if and only if it is not an eigenvalue" is not true in general, but it is true in the specific case of a linear transformation on a finite-dimensional vector space: "an endomorphism is injective if and only if it does not have 0 as an eigenvalue."

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Answer: $13.39

Step-by-step explanation:

first, you take 25% off 21, by multiplying 21*.25 which is 5.25

next, subtract 5.25 from 21, which gets you 15.75

next, add the 15% off coupon, by multiplying 15.75*.15 which is 2.3625

last, subtract 2.3625 from 15.75, which gets you 13.3875, or $13.39 rounded

The equivalent distance travelled by Mia is 2.3333... and 2[tex]\frac{1}{3}[/tex] miles.

The distance run by Mia is equivalent to 7/3 miles. We can express the fraction as -

7/3 = 2.3333

7/3 = (3 x 2 + 1)/3 = 2[tex]\frac{1}{3}[/tex]

So, the equivalent distance travelled by Mia is 2.3333... and 2[tex]\frac{1}{3}[/tex] miles.

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Answer: 2.33 and 2 1/3

Step-by-step explanation:

Therefore, she used 8 - 5 = 3 quarts of paint in the living room.

An English measurement of volume equal to one-quarter gallon is the quart. There are now three different types of quarts in use: the liquid quart, dry quart, and imperial quart of the British imperial system. One litre is about equivalent to each. It is split into four cups or two pints.

Legally, a US liquid gallon (sometimes just referred to as "gallon") is equal to 231 cubic inches, or precisely 3.785411784 litres.  Since a gallon contains 128 fluid ounces, it would require around 16 water bottles, each holding 8 ounces, to fill a gallon.

Here 2 gallons is equivalent to 8 quarts (2 gallons x 4 quarts/gallon = 8 quarts).

Mieko used 1/4 of the paint on her bedroom, which is 1/4 x 8 = 2 quarts.

She used 3 quarts on the hallway, so she used a total of 2 + 3 = 5 quarts on the bedroom and hallway.

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The closest answer is B. None of these

To find the present value of an income of Rs. 3 lakhs to be received after 1 year at a 5% rate of interest, you can use the present value formula:

Present Value (PV) = Future Value (FV) / (1 + Interest Rate) ^ Number of Years

1. Repeat the question in your answer: The present value of an income of Rs. 3 lakhs to be received after 1 year at a 5% rate of interest is:

2. Step-by-step explanation:

Step 1: Identify the values for the formula.
- Future Value (FV) = Rs. 3 lakhs
- Interest Rate = 5% or 0.05
- Number of Years = 1

Step 2: Plug the values into the formula.
PV = Rs. 3,00,000 / (1 + 0.05) ^ 1

Step 3: Calculate the present value.
PV = Rs. 3,00,000 / 1.05

PV ≈ Rs. 2,85,714.29

Based on the given options, the closest answer is B. None of these, as the calculated present value is approximately Rs. 2,85,714.29, which does not match any of the provided options.

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Answer:

Step-by-step explanation:

from the angles we understand that they are similar, therefore in proportion, we solve, in fact, with a proportion between the corresponding sides

24 : x = 32 : 38

x = 24 x 38 : 32

x = 912 : 32

x = 28.5 units

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

check

24 : 28.5 = 32 : 38

0.84 = 0.84

The answer is good

The missing angle outside the triangle is 137 degrees.

The missing angle in the triangle can be found as follows:

Vertically opposite angles are congruent.

Therefore,

180 - 45  -  60  = (sum of angles in a triangle)

180 - 105 = 75 degrees

Therefore,

180 - 75 - 68 = 37 degrees

Using the exterior angle theorem,

The exterior angle theorem states that the measure of an exterior angle is equal to the sum of the measures of the two remote interior angles of the triangle.

Hence,

let

x = missing angle

100 + 37 = x

x = 137 degrees

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The probability that the experiment ends before the 6th toss and an even number of tosses are required is 5/16.

The given experiment involves tossing a coin until the first time the same result appears twice in succession. This means that the experiment could end after two tosses if both tosses yield the same result (e.g., heads-heads or tails-tails) or it could continue for many more tosses until this condition is met.

The sample space for this experiment can be represented as a binary tree where the root node represents the first toss and the two branches from the root represent the two possible outcomes (heads or tails). The next level of the tree represents the second toss, with two branches emanating from each branch of the root (one for heads and one for tails). This process continues until the experiment ends with two successive outcomes being the same.

The probability of each outcome in the sample space can be computed by multiplying the probabilities of each individual toss. Since each toss has a probability of 1/2 of resulting in heads or tails, the probability of any particular outcome requiring n tosses is 1/2^n.

(a) A = The experiment ends before the 6th toss.

To calculate the probability of this event, we need to sum the probabilities of all outcomes that end before the 6th toss. This includes outcomes that end after the second, third, fourth, or fifth toss. Thus, we have:

P(A) = P(outcome ends after 2 tosses) + P(outcome ends after 3 tosses) + P(outcome ends after 4 tosses) + P(outcome ends after 5 tosses)

= (1/2^2) + (1/2^3) + (1/2^4) + (1/2^5)

= 15/32

Therefore, the probability that the experiment ends before the 6th toss is 15/32.

(b) B = An even number of tosses are required.

An even number of tosses are required if the experiment ends after the second, fourth, sixth, etc. toss. The probability of this event can be calculated as follows:

P(B) = P(outcome ends after 2 tosses) + P(outcome ends after 4 tosses) + P(outcome ends after 6 tosses) + ...

= (1/2^2) + (1/2^4) + (1/2^6) + ...

This is a geometric series with first term a = 1/4 and common ratio r = 1/16. Using the formula for the sum of an infinite geometric series, we have:

P(B) = a/(1-r) = (1/4)/(1-1/16) = 4/15

Therefore, the probability that an even number of tosses are required is 4/15.

(c) A∩B = The experiment ends before the 6th toss and an even number of tosses are required.

To calculate the probability of this event, we need to consider only the outcomes that satisfy both conditions. These include outcomes that end after the second or fourth toss. Thus, we have:

P(A∩B) = P(outcome ends after 2 tosses) + P(outcome ends after 4 tosses)

= (1/2^2) + (1/2^4)

= 5/16

Therefore, the probability that the experiment ends before the 6th toss and an even number of tosses are required is 5/16.

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Answer:

$78.7092

Step-by-step explanation:

He wants to buy a skateboard. The percentage value of the skateboard before any changes is 100%. So $73.56 = 100%. Now when you add a sales tax to it, the price will increase by 7% so it'll now be 107% right? You just have to find how much the 107% is equal to.

100% = 73.56

1% = 73.56÷100 = 0.7356

107 % = 0.7356 × 107 = 78.7092

As given below find the suitable option which gives you the answer for the question. "There are 11 questions in 5 pages. No credit will be given without sufficient work 1. Let Z be a standard normally distributed random variable."

1. Let Z be a standard, normally distributed random variable.
a. P(Z ≤ 2.32)
To find this probability, you need to use the standard normal distribution table (also known as the Z-table) to look up the value corresponding to Z = 2.32. The value you find in the table is the probability P(Z ≤ 2.32).
b. P(Z ≥ -1.56)
To find this probability, first look up the value corresponding to Z = -1.56 in the standard normal distribution table. This value represents P(Z ≤ -1.56). Since we want P(Z ≥ -1.56), we need to find the complement, which is 1 - P(Z ≤ -1.56).
c. P(-1.43 ≤ Z ≤ 2.47)
To find this probability, look up the values corresponding to Z = -1.43 and Z = 2.47 in the standard normal distribution table. The difference between these two values will give you the probability P(-1.43 ≤ Z ≤ 2.47).
d. Find z* so that P(-z* ≤ Z ≤ z*) = 0.99
To find the z* value, you need to look up the value in the standard normal distribution table that corresponds to the area of 0.995 (since 0.99 is the area between -z* and z*, and each tail contains 0.005). Once you find the value in the table, look at the corresponding Z value. This value will be your z*.

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Answer: D.34 units

Step-by-step explanation:

Answer:olution:. Given data:. Answer:. sum_(n=4)^10 15(3/10)^(n-1)= sum_(n=4)^10 15(0.3)^(n-1) = 15 [(0.3)^3 + (0.3)^4 + (0.3)^5+ (0.3)^6 + (0.3)^7+ (0.3)^8 + ...

Doesn’t include: 0.58 ‎b ‎1.92 ‎c ‎6.42 ‎d ‎9.43

Evaluate: summation from n equals 4 to 10 of 15 times 3 tenths to the n minus 1 power period Round to the nearest hundredth.

Step-by-step explanation:Example

Evaluate X

4

r=1

r

3

.

Solution

This is the sum of all the r

3

terms from r = 1 to r = 4. So we take each value of r, work out

r

3

in each case, and add the results. Therefore

X

4

r=1

r

3 = 13 + 23 + 33 + 43

= 1 + 8 + 27 + 64

= 100 .

Example

Evaluate X

5

n=2

n

2

.

Solution

In this example we have used the letter n to represent the variable in the sum, rather than r.

Any letter can be used, and we find the answer in the same way as before:

X

5

n=2

n

2 = 22 + 32 + 42 + 52

= 4 + 9 + 16 + 25

= 54 .

Example

Evaluate X

5

k=0

2

k

.

In the context of the Mumbai study, the residual is the difference between the observed value (the child's height or arm span) and the predicted value (based on a statistical model or an average value). Therefore, the residual for this child is -3.1 cm.

To calculate the residual, we need to first determine the predicted arm span for a child with a height of 59 cm using the regression equation from the Mumbai study. Let's assume the regression equation is:

Arm span = 0.9*Height + 10

Plugging in the height of 59 cm, we get:

Arm span = 0.9*59 + 10 = 63.1 cm

The predicted arm span for this child is 63.1 cm.

Now, to calculate the residual, we simply subtract the predicted arm span from the actual arm span:

Residual = Actual arm span - Predicted arm span
Residual = 60 - 63.1
Residual = -3.1 cm

Therefore, the residual for this child is -3.1 cm.

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P(X < Y) = 0.1 + 0.2 + 0.15 = 0.45

P(X > Y) = 0.25 + 0.15 = 0.4.

(a) Since the sum of probabilities for each value of X must be equal to 1, we have:

0.1 + a + b = 0.45

c = 0.25

d + e = 0.3

f = 0.15

Also, since the sum of probabilities for each value of Y must be equal to 1, we have:

a + c + d = 0.3

b + e + f = 0.15

Using these equations, we can solve for the unknowns:

a + b = 0.35

a + b + c = 0.7

d + e = 0.3

f = 0.15

From the first two equations, we get:

c = 0.35 - a - b

Substituting this into the equation for Y probabilities, we get:

a + 0.25 + d = 0.3 - 0.35 + a + b + d

0.65 = 2a + b

Using the equation for X probabilities, we get:

a + b = 0.35

d + e = 0.3

Solving for a, b, d, and e, we get:

a = 0.15

b = 0.2

d = 0.15

e = 0.15

Substituting these values back into the equation for Y probabilities, we get:

c = 0.35 - a - b = 0

And for X probabilities, we get:

f = 0.15

Therefore, the values of a, b, c, d, e, and f are:

a = 0.15, b = 0.2, c = 0, d = 0.15, e = 0.15, f = 0.15.

(b) P(X = Y) is the sum of the probabilities along the diagonal of the table. From the table, we can see that P(X = Y) = 0.15.

P(X < Y) is the sum of the probabilities in the upper triangle of the table, and P(X > Y) is the sum of the probabilities in the lower triangle. From the table, we can see that:

P(X < Y) = 0.1 + 0.2 + 0.15 = 0.45

P(X > Y) = 0.25 + 0.15 = 0.4.

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Answer:

89

Step-by-step explanation:

it is a straight line mean 180 degrees.

180 subtract 91 is 89

Answer:The measure of angle b is 89 degrees.

Step-by-step explanation:

Types of angles:

• Angles between 0 and 90 degrees (0°< θ <90°) are called acute angles.

• Angles between 90 and 180 degrees (90°< θ <180°) are known as obtuse angles.

• Angles that are 90 degrees (θ = 90°) are right angles.

• Angles that are 180 degrees (θ = 180°) are known as straight angles.

• Angles between 180 and 360 degrees (180°< θ < 360°) are called reflex angles.

• Angles that are 360 degrees (θ = 360°) are full turn.

We know that,

 Angles that are 180 degrees (θ = 180°) are known as straight angles.

In this question ,let

a= 91 and we have to find b=?

here,by straight angle

a+b=180

91+b=180

b=180-91

b=89

this is the required answer.

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If the demand for tomato juice falls, it means that consumers are buying less of it at any given price. This will result in a leftward shift in the demand curve, showing a decrease in quantity demanded at each price level.

As a result, the equilibrium price of tomato juice will decrease, and the equilibrium quantity of tomato juice sold in the market will also decrease. This shift in demand will also affect the producers of tomato juice, who may need to adjust their prices and output levels to match the reduced demand. Overall, a decrease in demand for tomato juice will lead to lower prices and lower quantities sold in the market.

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