solve= 4x + 210 -2x =260

Answer:

1/2

Step-by-step explanation:

hope it helps :)

Answer:

1 and 6 thousandths.

Step-by-step explanation:

To say the decimal point into words, you say and.

The decimal points are tenths, hundreths, thousandths, ten thousandths, hundred thousands, millionths

Answer:

one and six thousandths

Step-by-step explanation:

Hope this helps

Answer:

Step-by-step explanation:

To find the scale factor, take the value of one side length from the scaled copy and divide it by the value of the corresponding side length of the original.

39/13 = 3

Therefore, the scale factor is 3.

Answer:

240766 - 52731x + 840x^2 + 144x^3

Answer:

The property showed in the number 21 is the distributive property

log(2) * log(5) * log2(32) ≈ 1.052245.

We can simplify this expression by using the fact that log a(b^c) = c*log a(b) and the values of log(2) and log(5) which are approximately 0.301 and 0.699 respectively.

We have:

log(2) * log(5) * log2(32)

= log(2) * log(5) * 5

= 0.301 * 0.699 * 5

= 1.052245

Therefore, log(2) * log(5) * log2(32) ≈ 1.052245.

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Answer:

Step-by-step explanation:

First Number : x - 5

Second Number : x

x + ( x - 5) = 31

     2x - 5 = 31

            2x = 31 + 5

           2x/2 = 36/2

               x = 18

Then plugin x= 18 into First numer X - 5

   x - 5

  18 - 5 = 13

18 + 13 = 31

so .....

First Number is 13

Second number is 18

A multiple regression analysis was performed to predict a team's points in the National Football League (NFL) based on rushing yards (x1), passing yards (x2), and first downs (x3). The estimated regression equation was obtained as the model for predicting points.

In the multiple regression analysis, the goal is to establish a relationship between the dependent variable (points) and multiple predictor variables (rushing yards, passing yards, and first downs). The estimated regression equation provides a mathematical representation of this relationship. The equation takes the form:

Points = b0 + b1(x1) + b2(x2) + b3(x3)

where b0 is the intercept term, and b1, b2, and b3 are the coefficients associated with the predictor variables x1, x2, and x3, respectively. These coefficients represent the estimated effect of each predictor variable on the points scored by a team.

By utilizing the estimated regression equation, one can input the values of rushing yards, passing yards, and first downs for a particular team and calculate the predicted points for that team based on the model. This analysis allows for making predictions and understanding the relationships between the predictor variables and the dependent variable in the context of NFL games.

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The conjugate which is 3 - √7 is also a root of f(x).

The root of a polynomial function f(x) is the value of x for which f(x) = 0.

Now if a polynomial function has a root x = a + √b then the conjugate of x which is x' = a - √b is also a root of the function, f(x).

Given that the polynomial function, f(x), with rational coefficients has roots

3 + √7, then by the above, the conjugate which is 3 - √7 is also a root of f(x).

So, 3 - √7 is also a root of f(x).

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Answer:

6

Step-by-step explanation:

Answer:

x = 6

Step-by-step explanation:

So we know that:

5x-10 = 20

5x=20+10

5x=30

x=6

hope this helps :)

To stretch the spring from its natural length to 0.6 feet beyond its natural length, the work done is 0.2 foot-pounds.

The work done in stretching a spring is given by the formula:

Work = (1/2)k(x2^2 - x1^2),

where k is the spring constant, x2 is the final displacement, and x1 is the initial displacement.

Given that a force of 2 pounds is required to hold the spring stretched 0.5 feet beyond its natural length, we can calculate the spring constant using Hooke's Law:

F = kx,

where F is the force applied, k is the spring constant, and x is the displacement.

2 pounds = k * 0.5 feet,

k = 2 pounds / 0.5 feet = 4 pounds/feet.

Now we can calculate the work done:

Work = (1/2) * (4 pounds/feet) * ((0.6 feet)^2 - (0.5 feet)^2),

Work = (1/2) * (4 pounds/feet) * (0.36 - 0.25),

Work = (1/2) * (4 pounds/feet) * 0.11,

Work = 0.2 foot-pounds.

The work done in stretching the spring from its natural length to 0.6 feet beyond its natural length is 0.2 foot-pounds. This calculation is based on the given force required to hold the spring stretched 0.5 feet beyond its natural length and the spring constant.

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The correct option would be -4...4.

The expression (randgen.nextInt(9) - 4) uses a random number generator object named randgen to generate a random integer between 0 (inclusive) and 9 (exclusive) using the nextInt() method.

By subtracting 4 from this random integer, we determine the range of possible values for the expression.

Since the original random integer ranges from 0 to 8, subtracting 4 shifts the range to -4 to 4. This means that the possible values for (randgen.nextInt(9) - 4) can be any integer between -4 and 4, inclusive.

In other words, the expression can yield values such as -4, -3, -2, -1, 0, 1, 2, 3, and 4. These values cover a total of nine integers, including both positive and negative numbers.

Therefore, the correct option is -4...4, which represents the range of possible values for the expression (randgen.nextInt(9) - 4).

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The largest palindrome made from the product of two 3-digit numbers is 906609.

To find the largest palindrome made from the product of two 3-digit numbers, we can start by considering all possible products of two 3-digit numbers, ranging from 100 to 999. We can then check if each product is a palindrome.

A palindrome is a number that reads the same forwards and backwards. We can iterate through the products in decreasing order and check if each product is a palindrome. If we find a palindrome, we compare it with the current largest palindrome found and update it if necessary.

Starting from 999 and iterating downwards, we multiply each number by all the 3-digit numbers below it. For example, we multiply 999 by 999, 998, 997, and so on. We continue this process until we find the largest palindrome.

After checking all possible products, we find that the largest palindrome made from the product of two 3-digit numbers is 906609. This palindrome is obtained by multiplying 993 by 913.

Therefore, the largest palindrome made from the product of two 3-digit numbers is 906609.

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Answer:

I think its b

Step-by-step explanation:

Thanks to the person above me

Answer:

B Is called legs

Step-by-step explanation:

Answer:

what are the answers ?

Step-by-step explanation:

I cant see the other answers I only see leg

Answer:

$$0.8^4=0.4096$$ Explanation: The introduction to logarithms and definition of it is explained in the first link. 0.8 is the base of both logarithm and exponent

Step-by-step explanation:

Equation A is converted to equation B by multiplying or dividing both parts by a non-zero constant. Thus, option C is correct.  

If a function accepts more than one value, it is said to be nonconstant (if there is more than one element in its range).

As an illustration, a polynomial with real numbers as its domain and codomain becomes nonconstant. Just observing that and means the function accepts at least two distinct values allows us to demonstrate this.

Starting with the variable solely on a single side of the equation, we can start resolving equation A for x:

\(x/4 + 1 = -3\sx/4 = -3 - 1\sx/4 = -4\)

We obtain x = -16 by multiplying both of the equation's sides by 4.

Starting with the variable with one of the equation's equations, we can solve equation B for x:

\(x + 4 = -12\)

Therefore, We obtain \(x = -16\) by deducting  \(4\) from both of the equation's components.

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The procedure for revising probabilities based on additional information is referred to as Bayesian updating

The procedure for revising probabilities based on additional information is referred to as Bayesian updating. Bayesian updating is a fundamental concept in Bayesian statistics, which allows for the incorporation of new evidence or data to update and refine prior beliefs or probabilities.

In Bayesian updating, the process begins with an initial prior probability, which represents the initial belief or knowledge about an event or hypothesis before any evidence is observed. As new evidence or data becomes available, it is used to update the prior probability and generate a posterior probability. The posterior probability represents the revised belief or probability after incorporating the new information.

Bayesian updating follows the principles of Bayes' theorem, which mathematically describes the relationship between prior probabilities, likelihoods, and posterior probabilities. It involves combining the prior probability with the likelihood of observing the data given the hypothesis and then normalizing the result to obtain the posterior probability.

The beauty of Bayesian updating is that it allows for a flexible and iterative process of continuously updating beliefs and probabilities as new information emerges. It provides a framework for incorporating both subjective prior beliefs and objective data to make more informed decisions and predictions. Bayesian updating has applications in various fields, including machine learning, decision-making, and scientific research.

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Answer:

-0.6 yards

Step-by-step explanation:

To prove that a⊆c if a⊆b and b⊆c, we need to arrange the steps in the correct order to construct a logical proof.

The correct order is as follows:

Step 1: Start by assuming that a⊆b and b⊆c are true.

Step 2: Take an arbitrary element x and assume that x∈a.

Step 3: Using the assumption a⊆b, conclude that x∈b.

Step 4: Using the assumption b⊆c, conclude that x∈c.

Step 5: Since x was an arbitrary element, we have shown that for any element x, if x∈a, then x∈c.

Step 6: Therefore, by definition, a⊆c.

Let's briefly explain the reasoning behind each step:

Step 1: This is the initial assumption given in the problem statement. We assume that a⊆b and b⊆c are true.

Step 2: To prove that a⊆c, we need to show that every element of a is also an element of c. We start by taking an arbitrary element x and assuming that it belongs to a (x∈a).

Step 3: Using the assumption a⊆b, we know that if x∈a, then x∈b. This follows directly from the definition of subset: every element of a is also an element of b.

Step 4: Similarly, using the assumption b⊆c, we know that if x∈b, then x∈c. Again, this follows directly from the definition of subset: every element of b is also an element of c.

Step 5: Combining the conclusions from Steps 3 and 4, we can infer that if x∈a, then x∈c. Since x was an arbitrary element, this holds true for any element in a. Therefore, we have shown that every element of a is also an element of c.

Step 6: Finally, by definition, if every element of a is also an element of c, we can conclude that a is a subset of c (a⊆c).

By following these steps in the given order, we have logically proven that a⊆c based on the assumptions a⊆b and b⊆c.vTo prove that a⊆c if a⊆b and b⊆c, we need to arrange the steps in the correct order to construct a logical proof. The correct order is as follows:

Step 1: Start by assuming that a⊆b and b⊆c are true.

Step 2: Take an arbitrary element x and assume that x∈a.

Step 3: Using the assumption a⊆b, conclude that x∈b.

Step 4: Using the assumption b⊆c, conclude that x∈c.

Step 5: Since x was an arbitrary element, we have shown that for any element x, if x∈a, then x∈c.

Step 6: Therefore, by definition, a⊆c.

Let's briefly explain the reasoning behind each step:

Step 1: This is the initial assumption given in the problem statement. We assume that a⊆b and b⊆c are true.

Step 2: To prove that a⊆c, we need to show that every element of a is also an element of c. We start by taking an arbitrary element x and assuming that it belongs to a (x∈a).

Step 3: Using the assumption a⊆b, we know that if x∈a, then x∈b. This follows directly from the definition of subset: every element of a is also an element of b.

Step 4: Similarly, using the assumption b⊆c, we know that if x∈b, then x∈c. Again, this follows directly from the definition of subset: every element of b is also an element of c.

Step 5: Combining the conclusions from Steps 3 and 4, we can infer that if x∈a, then x∈c. Since x was an arbitrary element, this holds true for any element in a. Therefore, we have shown that every element of a is also an element of c.

Step 6: Finally, by definition, if every element of a is also an element of c, we can conclude that a is a subset of c (a⊆c).

By following these steps in the given order, we have logically proven that a⊆c based on the assumptions a⊆b and b⊆c.

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Answer:

48

Step-by-step explanation:

multiply both sides by 4

12 times 4 is 48

Answer: C= -2

Step-by-step explanation:

Answer:

C. -2

Step-by-step explanation:

5x + 2(x − 4) = 5x + x − 10

Subtract 5 from both sides,

5x + 2(x - 4) - 5x = 5x + x - 10 - 5x

Simplify,

2(x - 4) = x - 10

Distribute,

2x - 8 = x - 10

Add 8 to both sides,

2x - 8 + 8 = x - 10 + 8

Simplify,

2x = x - 2

Subtract x from both sides,

2x - x = x - 2 - x

Simplify,

x = -2

Work Shown:

5 green discs

7+5+2 = 14 discs total

5/14 is the probability of getting a green disc

(5/14)*140 = 50 green discs are expected if 140 trials are conducted.

The no. of green discs she expects by replacing and drawing again for 140 times is 50.

Probability is the chance of occurrence of a certain event out of the total no. of events that can occur in a given context.

Given A bag contains 7 red discs, 5 green discs, and 2 pink discs.

So, no. of sample space N(S) = 7 + 5 + 2 = 14.

∴ The probability of getting a green disc P(G) = N(G)/N(S).

P(G) = 5/14.

Now she replaces the discs drawn and picks one random disc from the bag again 140 times,

Therefore the probability of getting a green disc will remain the same as an independent event because of the replacement.

∴ The no. of green discs she expects is (5/14)×140 = 50 times.

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Answer:

I think it is 2/12

The degree of freedom, df value for the chi-square statistic is 3.

In this question,

The chi-square goodness of fit test evaluates whether proportions of categorical or discrete outcomes in a sample follow a population distribution with hypothesized proportions. As a hypothesis test, the chi-square goodness of fit test allows you to use your sample to draw conclusions about an entire population.

Here,

Sample, n = 100

Number of categories, the sample is divided = 4

df is the degrees of freedom.

If there is a K category in the dataset and we want to apply chi-square goodness of fit test. Then, their degree of freedom df will be of k-1.

Thus, degree of freedom, df = k - 1

⇒ df = 4 - 1

⇒ df = 3

Hence we can conclude that the degree of freedom, df value for the chi-square statistic is 3.

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Answer:

I exactly don't have or know the answer

If the number of tomato growers in the market increases, it would generally lead to an increase in the supply of tomatoes increases.

The correct answer is A.

The correct answer is A.

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No, should a researcher ever use chi-square to examine the relationship between two variables that are interval level and normally distributed

No, a researcher not uses a chi-square test to examine the relationship between two variables that are interval level and normally distributed. The chi-square test is used to analyze the association between two categorical variables, not interval-level variables.

For interval-level variables that are normally distributed, a more appropriate statistical test to examine the relationship or association would be a correlation analysis, such as Pearson's correlation coefficient. Pearson's correlation measures the strength and direction of the linear relationship between two continuous variables.

The chi-square test is specifically designed for categorical variables and assesses whether there is a significant association or dependency between them. It compares the observed frequencies in different categories to the frequencies that would be expected if the variables were independent.

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