PLEASE HELPPPPPPPP
PLEASE IMBEGGING

Answer:

I believe it's the second one

The actual height of the building is 80 feet.If a building in a 1 inch to 2 feet scale drawing is 40 inches tall, we can use proportionality to determine the actual height of the building.

Since the scale is 1 inch to 2 feet, this means that every 1 inch on the drawing represents 2 feet in real life. We can write this as:1 inch / 2 feet = x inches / actual height of the building

To solve for the actual height of the building, we can cross-multiply and simplify:

1 inch * actual height of the building = 2 feet * 40 inches

actual height of the building = (2 feet * 40 inches) / 1 inch

Simplifying the expression, we get:

actual height of the building = 80 feet

Therefore, the actual height of the building is 80 feet.

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Answer:

x=2

Step-by-step explanation:

3x+4=10

3x=10-4

3x=6

x=6/3

x=2

The balance of Marissa’s retirement account after 15 years if She makes an initial deposit of $1,000. Her contributions are $500 a month for the next 15 years is $8500.

When the loan is given to you, then some amount is charged to you for the principal amount and that is called interest.

Given data:

Initial deposit = $1000

Her contributions are $500 a month for the next 15 years

Amount after 15 years = Initial deposit  + 15 × 500

Amount after 15 years = $1000 + 7500

Amount after 15 years = $8500

Therefore, the balance of Marissa’s retirement account after 15 years if She makes an initial deposit of $1,000. Her contributions are $500 a month for the next 15 years is $8500.

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Answer:

q= (23+8a)/a

Step-by-step explanation:

a(q-8)=23

or, aq-8a = 23

or, aq = 23+8a

or, q = (23+8a)/a

(I’m not sure if the A is part of the question or if A is what question you’re answering but I’ll work o for both)

A(q - 8) = 23

Multiply everything inside the brackets by A:

aq- 8a = 23

Divide both sides by a to isolate q - 8a:

q - 8a = 23 / a

Add 8a to both sides to isolate q:

q = 23 + 8a² / a

Without the A:

q - 8 = 23

Add 8 to both sides to isolate q:

q = 31

Sorry if I misunderstood but I hope I helped you, have a great day!!

The probability that the second student chosen is a girl, given that the first one was a boy, is 13/20 or 0.65, which can also be expressed as 65%.

The probability that the second student chosen is a girl, given that the first one was a boy, can be calculated by dividing the number of remaining girls by the total number of remaining students. Initially, there are a total of 14 girls and 8 boys, making a total of 22 students in the class. The first student chosen is a boy, so there are now 13 girls and 7 boys remaining.

To find the probability that the second student chosen is a girl, given that the first one was a boy, we need to determine the number of remaining girls and divide it by the total number of remaining students. In this case, there are 13 remaining girls out of a total of 20 remaining students (13 girls + 7 boys). Therefore, the probability that the second student chosen is a girl, given that the first one was a boy, is 13/20 or 0.65, which can also be expressed as 65%.

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Based on the information in the graph, it can be inferred that team B scores 4 more goals per game.

To compare the populations using measures of center and median we must carry out the following procedure:

Team A

Median = 3

Q₁ = 2

Q₃ = 4

IQR = Q₃ - Q₁ = 4 - 2 = 2

Team B

Median = 7

Q₁ = 6

Q₃ = 8

IQR = Q₃ - Q₁ = 8 - 6 = 2

According to the information above, the variation in goals scored is the same. However, team B usually scores 4 more goals than team A for each game.

Additionally, the difference in the mean of these two values is 2.

Note: This question is incomplete. Here is the complete information:

Attached image

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Answer:

I think its B but not sure

Step-by-step explanation:

Answer:

Step-by-step explanation:

its A& B

Answer:

The critical value Za /2 that corresponds to 98% confidence level is (d) 2.33

Step-by-step explanation:

To obtain the critical value Za/2 that corresponds to a 98% confidence level, we need to determine the value that leaves 2% (0.02) in the tails of the distribution.

Since the confidence level is two-tailed, we need to divide the significance level by 2 to find the area in each tail. In this case, we have 2% divided by 2, resulting in 1% (0.01) in each tail.

Looking up the critical value in a standard normal distribution table or using statistical software, we obtain that the closest value to 0.01 in the table is approximately 2.33.

Therefore, the correct answer is D. 2.33.

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The trend projection for time period 18 is 197.6. The correct option is B

A mathematical equation used to represent the trend or pattern seen in a time series of data is called a linear trend expression, sometimes referred to as a linear trend model.

To find the trend projection for time period 18 using the given linear trend expression, we substitute t = 18 into the equation:

Yt = 129.2 + 3.8t

Y18 = 129.2 + 3.8 * 18

Y18 = 129.2 + 68.4

Y18 = 197.6

Therefore, the trend projection for time period 18 is 197.6.

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Answer:

4*4*4=4^3

Step-by-step explanation:

4 is multiplied by itself 3 times so it's to the third power which equals \(4^{3}\)

Albert used the division and multiplication properties of equality to rewrite the equation.

To understand the properties used by Albert to rewrite the equation, let's analyze the steps taken:

The original equation is: -13x/5 = 286.

Albert's rewritten equation is: x/5 = 286/-13.

To transform the original equation into the rewritten form, Albert applied the following properties:

Division Property of Equality: Albert divided both sides of the original equation by -13/5. This property states that if you divide both sides of an equation by the same non-zero number, the equality remains unchanged.

Multiplication Property of Equality: Albert multiplied both sides of the equation by -13/5. This property states that if you multiply both sides of an equation by the same non-zero number, the equality remains unchanged.

Therefore, Albert used both the division property of equality and the multiplication property of equality to rewrite the equation. The division property was used to isolate the variable term on one side of the equation, and the multiplication property was used to manipulate the coefficients and maintain the equality.

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Answer:

3/26

Step-by-step explanation:

6 of the 52 cards are red

Equation: SA=2πrh+2πr^2
Radius = 4
Height = 10
Plug the values in
SA=2π(4)(10)+2π(4)^2

And just solve with a calculator

≈351.85838

Round to the nearest tenth.

.85 rounds to .9
So the answer is 351.9

Thus, the probability that the result on the spinner is a multiple of 4 and a multiple of 3 when  spinner is spun one time is 7/14.

The probability value represents the likelihood that a specific event or outcome will occur given a list of all conceivable events or outcomes. It is possible to express the probability value as a fraction or percentage.

Given that-

Sample space for multiple of 4 : {4, 8, 12}

Sample space for multiple of 3 : {3, 6, 9,12}

probability = number of favourable outcome / number of total outcome

probability (multiple of 4) = total number of multiple of 4 / total numbers

probability (multiple of 4) = 3 / 14

probability (multiple of 3) = total number of multiple of 3 / total numbers

probability (multiple of 3) = 4 /14

probability (multiple of 3) = 2 / 7

Thus,

probability (multiple of 4 and a multiple of 3) = 3 / 14 + 4 / 14

probability (multiple of 4 and a multiple of 3) = (3 + 4) / 14

probability (multiple of 4 and a multiple of 3) = 7/14

Thus, the probability that the result on the spinner is a multiple of 4 and a multiple of 3 when  spinner is spun one time is 7/14.

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The probability that a randomly selected member of Congress who favours corporate tax reform is a Democrat is 0.4444, rounded to four decimal places.

To solve this problem, we can use Bayes' theorem. Let D represent the event that the selected member is a Democrat, and R represent the event that the selected member is a Republican, and I represent the event that the selected member is an Independent. Let F represent the event that the selected member favors some type of corporate tax reform. We are given the following probabilities:

P(R) = 0.28, P(D) = 0.50, P(I) = 0.22

P(F|R) = 0.34, P(F|D) = 0.35, P(F|I) = 0.31

We want to find P(D|F), the probability that the selected member is a Democrat given that they favor corporate tax reform. We can use Bayes' theorem:

P(D|F) = P(F|D)P(D) / [P(F|D)P(D) + P(F|R)P(R) + P(F|I)P(I)]

Plugging in the values we know, we get:

P(D|F) = 0.35 * 0.50 / [0.35 * 0.50 + 0.34 * 0.28 + 0.31 * 0.22]

P(D|F) = 0.4444 (rounded to four decimal places)

Therefore, the probability that the selected member is a Democrat given that they favour corporate tax reform is 0.4444.

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The house prices data in the prices dataset for King County can be from any time period that the data was collected. There is no information provided in the code or package about the specific time period was collected from.

7. The house_prices dataset from the "moderndive" package contains house sale data for King County. The time period for these house prices is from May 2014 to May 2015.

8. To find the median and mean value for the number of bedrooms in the house_prices dataset, you can use the following code:

```R
median_bedrooms <- median(house_prices$bedrooms)
mean_bedrooms <- mean(house_prices$bedrooms)
```

9. To find the maximum value for the number of bedrooms in the house_prices dataset, use the following code:

```R
max_bedrooms <- max(house_prices$bedrooms)
```

This will give you the maximum number of bedrooms in the dataset.

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The standard normal distribution has a mean of 0 and a standard deviation of 1. M ≈ 30.935. The median of the distribution is also 25.

(a) To find M, we first need to convert the given values of mean and standard deviation to the standard normal distribution. This can be done by using the formula Z = (X - μ) / σ, where Z is the Z-score, X is the value of interest, μ is the mean, and σ is the standard deviation. In this case, we have X ~ N(25, 9). Substituting the values into the formula, we get Z = (X - 25) / 3. Now we need to find the Z-score that corresponds to the desired probability of 0.95. Using a standard normal distribution table or a calculator, we find that the Z-score corresponding to a cumulative probability of 0.95 is approximately 1.645. Setting Z equal to 1.645, we can solve for X: (X - 25) / 3 = 1.645. Solving for X, we get X ≈ 30.935. Therefore, M ≈ 30.935.

(b) The median is the value that divides the distribution into two equal halves. In a normal distribution, the median is equal to the mean. In this case, the mean is given as 25. Therefore, the median of the distribution is also 25.

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The maximum likelihood estimate (MLE) for the parameter ⴡ is ⴡ = 5/13. The MLE represents the value of the parameter that maximizes the likelihood of obtaining the observed data.

To find the maximum likelihood estimate (MLE) for the parameter ⴡ, we need to construct the likelihood function and then maximize it with respect to ⴡ.

Given that the lifetime of Badger brand light bulbs is modeled by an exponential distribution, the probability density function (PDF) of the exponential distribution is given by:

f(x; ⴡ) = ⴡ * exp(-ⴡx)

where ⴡ is the parameter of interest and x is the observed lifetime of the light bulb.

In this case, we have observed lifetimes of 2, 3, 1, 3, and 4 years for 5 tested bulbs. Let's denote these observed lifetimes as x₁, x₂, x₃, x₄, and x₅, respectively.

The likelihood function (L) for the observed data can be expressed as the product of the individual probabilities:

L(ⴡ) = f(x₁; ⴡ) * f(x₂; ⴡ) * f(x₃; ⴡ) * f(x₄; ⴡ) * f(x₅; ⴡ)

Taking the logarithm of the likelihood function (log-likelihood) simplifies the calculations:

log L(ⴡ) = log f(x₁; ⴡ) + log f(x₂; ⴡ) + log f(x₃; ⴡ) + log f(x₄; ⴡ) + log f(x₅; ⴡ)

Substituting the exponential distribution PDF into the log-likelihood equation:

log L(ⴡ) = log(ⴡ * exp(-ⴡx₁)) + log(ⴡ * exp(-ⴡx₂)) + log(ⴡ * exp(-ⴡx₃)) + log(ⴡ * exp(-ⴡx₄)) + log(ⴡ * exp(-ⴡx₅))

Simplifying further:

log L(ⴡ) = log ⴡ + (-ⴡx₁) + log ⴡ + (-ⴡx₂) + log ⴡ + (-ⴡx₃) + log ⴡ + (-ⴡx₄) + log ⴡ + (-ⴡx₅)

log L(ⴡ) = 5log ⴡ + (-ⴡx₁) + (-ⴡx₂) + (-ⴡx₃) + (-ⴡx₄) + (-ⴡx₅)

Taking the derivative of the log-likelihood function with respect to ⴡ and setting it equal to zero, we can find the value of ⴡ that maximizes the likelihood:

d(log L(ⴡ))/dⴡ = 5/ⴡ - x₁ - x₂ - x₃ - x₄ - x₅ = 0

Rearranging the equation:

5/ⴡ = x₁ + x₂ + x₃ + x₄ + x₅

ⴡ = 5 / (x₁ + x₂ + x₃ + x₄ + x₅)

Substituting the observed lifetimes:

ⴡ = 5 / (2 + 3 + 1 + 3 + 4)

ⴡ = 5 / 13

In this case, the MLE suggests that the parameter ⴡ, representing the rate parameter of the exponential distribution, is estimated to be 5/13.

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Answer:

4.768×10^3

Step-by-step explanation:

4768 in standard form:

4.768 *10^3

It already is in standard form.

For the arithmetic series, The first number of the 20th line is 575, and the last number is 634 and the next two lines of the pattern are:

23 26 29

32 35 38 41 .

What is a arithmetic series?

An arithmetic series is a sequence of numbers in which each term is obtained by adding a constant value (called the common difference) to the previous term. The general form of an arithmetic series is:

a, a + d, a + 2d, a + 3d, ...

where "a" is the first term and "d" is the common difference between consecutive terms.

Now,

a) To continue the pattern, we add 3 to the first number of each line, and then add 3 to that sum to get the next number in the sequence. Therefore, the next two lines of the pattern are:

23 26 29

32 35 38 41

b) To find the first number of the 20th line, we can use the formula for the nth term of an arithmetic sequence:

aₙ = a₁+ (n - 1)d

where aₙ is the nth term, a₁ is the first term, n is the number of terms, and d is the common difference between consecutive terms.

In this case, we know that the common difference is 3, and we want to find the first term of the 20th line. To do this, we need to find the number of terms in the first 19 lines of the pattern. The first line has 1 term, the second line has 2 terms, the third line has 3 terms, and so on. Therefore, the number of terms in the first 19 lines is:

1 + 2 + 3 + ... + 18 + 19 = (19/2)(1 + 19) = 190

So, the first number of the 20th line is:

a₁ = 5 + (190)(3) = 575

To find the last number of the 20th line, we can use the formula:

aₙ = a₁+ (n - 1)d

where n is the number of terms in the 20th line, and d is still the common difference of 3.

The number of terms in the 20th line is 20, so the last number is:

a₂₀ = a₁+ (n - 1)d = 575 + (20 - 1)(3) = 634

Therefore, the first number of the 20th line is 575, and the last number is 634.

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Answer:

He ate 1 pound

Step-by-step explanation:

3 10/60. 6/60. then minus them so he ate one pound

Answer:

the answer is-1<=x<7.

Step-by-step explanation:

let us replace <= and < sign by equal to(=)

when we do it we get,

-6x +14 = -28 and ex + 28 =25

when we solve them we get,

x=-1 and x= 25 respectively from 1st and 2nd question. so, -1<=x<7 is answer...

hope it will help uh...

Answer:

Domain: (-infinite sign, infinity sign)

Range: (-infinite sign, infinity sign)

OR you can write it as {x|x ∊ R}

the R is real numbers

\(\huge\mathcal {♨Answer♥}\)

\( \large \texttt {The value of Z is :}\)

\((3z + 2) + (8z) = {90}^{0} \)

\(11z = {90} - 2\)

\( \frac{11z}{11} = {88}^{0} \)

\(z = {8}^{0} \)

☆...hope this helps...☆

_♡_mashi_♡_

The type of data that would be used to describe a response is Student: GPAs is Quantitative continuous, option B.

Dimensions like height, breadth, and length are examples of quantitative data that deal with numbers and items that can be measured objectively. humidity and temperature. Prices. Volume and surface.

Qualitative data deals with traits and qualities that are difficult to quantify but can be perceptually experienced, such as flavours, sensations, looks, and colours.

In general, you produce quantitative data when you measure something and assign it a numerical value. Qualitative data is produced when anything is categorised or evaluated. All is well thus far. Yet, this is only the most advanced level of data; there are many several varieties of quantitative and qualitative information.

Given data is identify the type of data that would be used to describe response. Students GPAs

Answer is option (B)) It is "Quantitative continuous"

Continuous Data can take an (within a range) any Value

A Continuous data set is a quantitative data set representing a Scale of measurment that can consist of numbers other than whole numbers, like decimals and fractions. Continuous data set would consist of values like height, weight, length, temperature and Other measurement like that So

Students GPAs is "Quantitative Continuous".

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The type of data that would be used to describe a response is Student: GPAs is Quantitative continuous, option 2.

Dimensions like height, breadth, and length are examples of quantitative data that deal with numbers and items that can be measured objectively. humidity and temperature. Prices. Volume and surface.

Qualitative data deals with traits and qualities that are difficult to quantify but can be perceptually experienced, such as flavours, sensations, looks, and colours.

In general, you produce quantitative data when you measure something and assign it a numerical value. Qualitative data is produced when anything is categorised or evaluated. All is well thus far. Yet, this is only the most advanced level of data; there are many several varieties of quantitative and qualitative information.

Given data is identify the type of data that would be used to describe response. Students GPAs

Answer is option (2)) It is "Quantitative continuous"

Continuous Data can take an (within a range) any Value

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A Continuous data set is a quantitative data set representing a Scale of measurment that can consist of numbers other than whole numbers, like decimals and fractions. Continuous data set would consist of values like height, weight, length, temperature and Other measurement like that So

Students GPAs is "Quantitative Continuous".

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Full Question: Identify the type ofldata that would be used to describe a response. Student:

GPAs Quantitative Discrete

Quantitative IContinuous

Qualitative Categoricalll

Hint: Data Categories Question Help: IRostikoloitumi Submit Question

Answer: If two pairs of corresponding angles in a pair of triangles are congruent, then the triangles are similar. We know this because if two angle pairs are the same, then the third pair must also be equal. When the three angle pairs are all equal, the three pairs of sides must also be in proportion.

Step-by-step explanation:

Answer:

130

Step-by-step explanation:

it shows the answer just look more carefully