-4-6 answer now pls iwill mark yall brainliest

Answer:

False

Step-by-step explanation:

\(4000\ =\ \frac{2}{5}\)

Is really equaled to:

\(4000 = 0.4\)

Hope this helped you!

Answer:

4,000 is equal to 2/5 of 10,000

Step-by-step explanation:

I didn't feel like writing the steps so I put added a picture, hope it helps

Answer:

b is not a polynomial

Step-by-step explanation:

b is not a polynomial because in y-3/y the y in denomination means y to the power -1 when it is taken to numerator and if power is negative then it is not a polynomial

The appropriate decision for this problem would depend on the calculated test statistic and its comparison to the critical value from the t-distribution table with a significance level of 0.01.

To determine the appropriate decision for this problem, the researcher needs to perform a hypothesis test. The null hypothesis (H0) would state that there is no difference in the mean prices of midrange homes between the two cities, while the alternative hypothesis (Ha) would state that there is a difference.

Since the sample sizes are relatively large (21 and 26), and the data is assumed to be normally distributed with similar variances, a two-sample t-test would be appropriate for comparing the means. The researcher can calculate the test statistic by using the formula:

\(t = (x1 - x2) / \sqrt{((s1^2 / n1) + (s2^2 / n2))}\)

Where x1 and x2 are the sample means, s1 and s2 are the sample standard deviations, and n1 and n2 are the sample sizes.

With the calculated test statistic, the researcher can compare it to the critical value from the t-distribution table with (n1 + n2 - 2) degrees of freedom, and a significance level of 0.01. If the test statistic falls within the critical region (i.e., it exceeds the critical value), the researcher can reject the null hypothesis and conclude that there is a significant difference in mean prices between the two cities. Otherwise, if the test statistic does not exceed the critical value, the researcher fails to reject the null hypothesis and concludes that there is not enough evidence to suggest a difference in mean prices.

In this case, the appropriate decision would depend on the calculated test statistic and its comparison to the critical value.

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Answer:

the value of x = -3

Step-by-step explanation:

10 (x-5) = -80

10x - 50 = -80

10x = -30

x = -3

CHECK:

10 ( -3 - 5) = -80

10 (-8) = -80

-80 = -80

Answer:

1+1=2

Step-by-step explanation:

Thanks for the ponts

9514 1404 393

Answer:

  A(-8, 6), D(-1, -16), E(17, -3)

Step-by-step explanation:

Any point with an x-value that matches any of {-8, -1, 5, 15, 17} will prove Mariela's claim incorrect. (A function cannot use an x-value more than once.)

Those points are ...

  (-8, 6), (-1, -16), (17, -3)

The complete factorization of the polynomial x³ + 2x² -x - 2 is equal to (x + 2)(x + 1)(x - 1)

An equation is an expression that shows how numbers and variables are related to each other using mathematical operators.

A polynomial is an expression consisting of coefficients and variables forming an equation.

Given the polynomial:

x³ + 2x² -x - 2

Factorizing:

= (x + 2)(x² - 1)

= (x + 2)(x + 1)(x - 1)

The polynomial x³ + 2x² -x - 2 is equal to (x + 2)(x + 1)(x - 1)

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Answer:

Step-by-step explanation: First we start by using the order of operations and do -2 + 16 which is 14. Then we do multiplication left to right, do 3 x 6 = 18x2 =36 +14 =50

No, the ratios 10:12 and 1:21 are not form a proportion.

A relationship that is always in the same ratio and quantity which vary directly with each other is called the proportional.

Given that;

The ratios are,

⇒ 10 : 12 and 1 : 21

We know that;

Two ratio are form a proportional when both are in same quantity or in a a same ratio.

Here, The ratios are,

⇒ 10 : 12 and 1 : 21

Clearly, We get;

10 / 12 = 5 / 6

1 / 21 = 1  21

Thus,

1 / 21 ≠ 5 /6

1 : 21 ≠ 10 : 12

Therefore, The ratios 10:12 and 1:21 are not form a proportion.

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The price elasticity of demand measured using midpoint method, for a price change between $10 and $2 can be determined as follows:Price elasticity of demand (mid-point method) = [ΔQ / {(Q1 + Q2)/2}] ÷ [ΔP / {(P1 + P2)/2}]Given that P1 = $10, P2 = $2, Q1 = Q2, and the price has decreased from $10 to $2.

Therefore, the midpoint price (P) = (P1 + P2) / 2 = ($10 + $2) / 2 = $6The midpoint quantity (Q) = (Q1 + Q2) / 2 = Q1 / 2 + Q2 / 2 = Q / 2 + Q / 2 = Q.ΔP = $2 − $10 = −$8ΔQ = Q − Q = 0Hence, the absolute value of the price elasticity of demand using the midpoint method for a change in price from $10 to $2 is :Price elasticity of demand (mid-point method) = [ΔQ / {(Q1 + Q2)/2}] ÷ [ΔP / {(P1 + P2)/2}]E = [0 / {Q / 2}] ÷ [−8 / $6]E = 0 ÷ −1.3333E = 0

So, the correct answer is option B: 1.

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To determine if the newly discovered plant belongs to the same genus as the horsetail, scientists would look for characteristic(s) that provide the best evidence to support this hypothesis. Here are some key characteristics that could be examined:

1. Morphological similarities: Comparing the physical characteristics and overall morphology of the newly discovered plant with known horsetails would provide important evidence. Scientists would analyze features such as the arrangement and structure of leaves, stems, roots, and reproductive structures (such as cones or spores). If the new plant shares significant similarities in morphology with horsetails, it suggests a closer relationship.

2. Genetic analysis: Conducting genetic studies, such as DNA sequencing or molecular markers, can provide strong evidence of evolutionary relationships. By comparing the genetic information of the new plant with that of horsetails, scientists can identify shared genetic traits that indicate a common ancestry. Similarities in DNA sequences or genetic markers would support the hypothesis of belonging to the same genus.

3. Evolutionary history: Investigating the evolutionary history and phylogenetic relationships of horsetails and the new plant can provide valuable insights. By examining the fossil record and constructing phylogenetic trees, scientists can determine the evolutionary relationships between different plant species. If the new plant shares a more recent common ancestor with horsetails compared to other plant groups, it supports the hypothesis of belonging to the same genus.

4. Reproductive compatibility: Assessing the reproductive compatibility between the new plant and horsetails can provide evidence of their relationship. If they can successfully hybridize or have compatible reproductive structures, it suggests a close evolutionary relationship and supports the hypothesis of belonging to the same genus.

5. Chemical composition: Analyzing the chemical composition of the new plant and comparing it with horsetails can provide additional evidence. Similarities in chemical compounds, such as secondary metabolites or bioactive compounds, can indicate a closer relationship and support the hypothesis.

It is important to consider multiple lines of evidence and conduct thorough investigations to support the hypothesis that the new plant belongs to the same genus as horsetails. A combination of morphological, genetic, evolutionary, reproductive, and chemical evidence would provide a more robust and conclusive assessment of their relationship.

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Answer:

b

Step-by-step explanation:

Answer:

Your answer is correct.

Step-by-step explanation:

82.3 - 46.5 = 35.8

The step 2 should  be m∠p + m∠o  = 180 degrees(supplementary angles)

The external angle theorem  states that the measure of each exterior angle of a triangle is equal to the sum of the opposite and non-adjacent interior angles(remote interior angles) .

Therefore,

Step 1

m∠m + m∠n + m∠o = 180°(sum of angles of a triangle)

It's very correct

Step 2

m∠p - m∠o = 90 degrees(Alternate angles)

This is incorrect.

It should be m∠p + m∠o  = 180 degrees(supplementary angles)

The angles  m∠p  and  m∠o are supplementary angles. This simply implies the angles add up to 180 degrees.

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Step-by-step explanation:

congruent is define as the same shape and size. AAA only prove the two triangle iare same shape but not same size.

a. The truck rental cost when you drive 85 miles is  $85.7.

b. The number of miles driven when the cost is $65.96 is 0.42x.

a. To find the truck rental cost when driving 85 miles, we can substitute the value of x into the given function.

f(x) = 0.42x + 50

Substituting x = 85:

f(85) = 0.42(85) + 50

= 35.7 + 50

= 85.7

Therefore, the truck rental cost when driving 85 miles is $85.70.

b. To determine the number of miles driven when the cost is $65.96, we can set up an equation using the given function.

f(x) = 0.42x + 50

Substituting f(x) = 65.96:

65.96 = 0.42x + 50

Subtracting 50 from both sides:

65.96 - 50 = 0.42x

15.96 = 0.42x

To isolate x, we divide both sides by 0.42:

15.96 / 0.42 = x

38 = x

Therefore, the number of miles driven when the cost is $65.96 is 38 miles.

In summary, when driving 85 miles, the truck rental cost is $85.70, and when the cost is $65.96, the number of miles driven is 38 miles.

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The map that sends a subgroup of the Galois group G to a subfield of E containing Q is known as the Galois correspondence. It establishes a one-to-one correspondence between the subgroups of G and the subfields of E containing Q.

Given a subgroup H of G, the corresponding subfield of E is the fixed field of H, denoted as E^H. It is defined as the set of all elements in E that are fixed under every automorphism in H. In other words, E^H = {α ∈ E : σ(α) = α for all σ ∈ H}.

Conversely, given a subfield F of E containing Q, the corresponding subgroup of G is the Galois group of the extension E/F, denoted as Gal(E/F). It is the set of all automorphisms in G that fix every element in F. In other words, Gal(E/F) = {σ ∈ G : σ(α) = α for all α ∈ F}.

The Galois correspondence establishes the following properties:

1. If H is a subgroup of G, then E^H is a subfield of E containing Q.

2. If F is a subfield of E containing Q, then Gal(E/F) is a subgroup of G.

3. The map is inclusion-reversing, meaning that if H₁ and H₂ are subgroups of G with H₁ ⊆ H₂, then E^H₂ ⊆ E^H₁. Similarly, if F₁ and F₂ are subfields of E containing Q with F₁ ⊆ F₂, then Gal(E/F₂) ⊆ Gal(E/F₁).

4. The map is order-preserving, meaning that if H₁ and H₂ are subgroups of G, then H₁ ⊆ H₂ if and only if E^H₂ ⊆ E^H₁. Similarly, if F₁ and F₂ are subfields of E containing Q, then F₁ ⊆ F₂ if and only if Gal(E/F₂) ⊆ Gal(E/F₁).

These properties establish the 1-1 correspondence between subgroups of G and subfields of E containing Q, which is a fundamental result in Galois theory.

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The angles made by F with the positive x, y and z axes are 62.13 degrees, 53.93 degrees and 117.87 degrees respectively.

The vector F = [(130) i + (160) j + (-130) k] N.

The angles made by F with the positive x, y and z axes are as follows:i. The angle made by F with the positive x-axis: In this case, we have to determine the angle made by the vector F with the positive x-axis which is represented by i.

The angle between the vector and the positive x-axis can be calculated using the following formula:cos(θ) = i . (F / |F|)Here, the dot product of the unit vector i and the vector F gives the magnitude of F along the positive x-axis and the magnitude of the vector F can be obtained by dividing it with its magnitude (|F|).Then, we obtain the value of θ by taking the inverse cosine of the result calculated in the above step. Thus,cos(θ) = [(130) i + (160) j + (-130) k] . (1, 0, 0) / |[(130) i + (160) j + (-130) k]|cos(θ) = 130 / 270cos(θ) = 0.4815θ = cos⁻¹(0.4815)Therefore, the angle made by F with the positive x-axis is θ = 62.13 degrees.ii. The angle made by F with the positive y-axis: In this case, we have to determine the angle made by the vector F with the positive y-axis which is represented by j. The angle between the vector and the positive y-axis can be calculated using the following formula:cos(θ) = j . (F / |F|)

Here, the dot product of the unit vector j and the vector F gives the magnitude of F along the positive y-axis and the magnitude of the vector F can be obtained by dividing it with its magnitude (|F|).Then, we obtain the value of θ by taking the inverse cosine of the result calculated in the above step. Thus,cos(θ) = [(130) i + (160) j + (-130) k] . (0, 1, 0) / |[(130) i + (160) j + (-130) k]|cos(θ) = 160 / 270cos(θ) = 0.5926θ = cos⁻¹(0.5926)Therefore, the angle made by F with the positive y-axis is θ = 53.93 degrees.iii. The angle made by F with the positive z-axis: In this case, we have to determine the angle made by the vector F with the positive z-axis which is represented by k. The angle between the vector and the positive z-axis can be calculated using the following formula:cos(θ) = k . (F / |F|)

Here, the dot product of the unit vector k and the vector F gives the magnitude of F along the positive z-axis and the magnitude of the vector F can be obtained by dividing it with its magnitude (|F|).Then, we obtain the value of θ by taking the inverse cosine of the result calculated in the above step.

Thus,cos(θ) = [(130) i + (160) j + (-130) k] . (0, 0, 1) / |[(130) i + (160) j + (-130) k]|cos(θ) = -130 / 270cos(θ) = -0.4815θ = cos⁻¹(-0.4815)Therefore, the angle made by F with the positive z-axis is θ = 117.87 degrees.

Answer: The angles made by F with the positive x, y and z axes are 62.13 degrees, 53.93 degrees and 117.87 degrees respectively.

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The height of the kite is approximately 84.8 feet.

A kite is flying on a string that is 90 feet long and is fastened to the ground at the other end.

The kite is flying above a point that is 30 feet away from where it is fastened on the​ ground. The height of the the can be found using Pythagoras's theorem.

Therefore,

c² = a² + b²

90² - 30² = b²

8100 - 900 = b²

b² = 7200

b = √7200

b = 84.8528137424

b = 84.8 ft

Therefore,

height of the kite = 84.8 ft

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The linear function that represents the data in the table is given by:

f(x) = 200x - 7.

A linear function is modeled by:

y = mx + b

In which:

Researching the function on the internet, it is found that:

Thus, the function is given by:

f(x) = 200x - 7.

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Answer:

b

Step-by-step explanation:

f(x)=200x-7

These are the roots of the given expressions.

a. The root is \(\(-5 - 5i\).\)

b. The root is\(\(-24i\).\)

a. To find the root of \(\(5(-1 - i)\),\) we can simplify the expression:

\(\(5(-1 - i) = -5 - 5i\)\)

Thus, the root is \(\(-5 - 5i\).\)

b. To find the root of \(\(3(-8i)\),\) we simplify the expression:

\(\(3(-8i) = -24i\)\)

Therefore, the root is\(\(-24i\).\)

In both cases, we multiplied the given complex numbers by their respective coefficients. When we multiply a complex number by a scalar, such as 5 or 3, it scales both the real and imaginary parts of the complex number. In case (a), both the real part (-1) and the imaginary part \((-i) of \(-1 - i\)\) are multiplied by 5, resulting in\(\(-5 - 5i\).\) In case (b), the imaginary part (-8i) is multiplied by 3, yielding \(\(-24i\).\)

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So, the 95% confidence interval for the population NCAA mean race time for that category using the bootstrapping sampling technique is (9.732, 10.642).

Given data:vector of race times of one sample of NCAA runners in a 100 meter dash: 9.79, 10.56, 10.98, 9.2, 10.64, 10.68, 10.12, 10.14The bootstrapping sampling technique is a resampling method used to estimate the population statistic using sample data.

It is a statistical technique that falls under the category of the resampling method. Bootstrapping samples are the random samples of the original data, having the same size as the original sample.To find the 95% confidence interval of the mean race time for NCAA runners.

we need to use the following bootstrap R script:mean_func <- function(data, index){  return(mean(data[index]))}boot_mean <- boot(data=race_time, statistic=mean_func, R=1000)boot_meanboot.ci(boot_mean, type="basic")R Code Explanation:

The mean_func is the function to calculate the mean of the given data and index. Here, the boot() function is used to generate bootstrap samples for the given data. In this function, R is used to define the number of samples to be generated.The boot_mean() function is used to calculate the bootstrap mean of the generated samples.

Here, boot.ci() function is used to calculate the confidence intervals of the given data by the bootstrapping method.In R Script, race_time is a vector of race times of one sample of NCAA runners in a 100 meter dash.

So, the 95% confidence interval for the population NCAA mean race time for that category using the bootstrapping sampling technique is (9.732, 10.642).Thus, the given R Script for the bootstrapping sampling technique can be modified to find the 95% confidence interval for the population NCAA mean race time for that category.

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Answer:

D.40°

Step-by-step explanation:

Angle U is congruent to angle S because UR = RS and UT=TS. Through that we now know U is also = 100°. A quadrilateral has to equal 360° degrees so 360°- 120° - 100°- 100° = 40° degrees

T is 40°

Answer:

its D. 40

hope that helped you

Answer: 21/40

Step-by-step explanation:

I did the test

Answer: 21/40

Hope this helps.

Answer:

28

Step-by-step explanation:

The scale factor is 3.5 which is found out by doing 14 divided by 4. Once you know the scale factor you simply have to do 8 multiplied 3.5 which equals 28.

Answer:

4

Step-by-step explanation:

The underlying function f(x - i) that generates the observed points f'(x - i) in the plot can be determined by integrating the observed points. By integrating f'(x - i), we can obtain f(x - i) up to a constant of integration.

The constant of integration can be determined by incorporating additional information or constraints related to the problem or by considering the behavior of the function at a specific point.

To find the underlying function f(x - i) that generates the observed points f'(x - i), we need to integrate the observed points.

Integration is the reverse process of differentiation, so by integrating f'(x - i), we can recover f(x - i) up to a constant of integration.

The constant of integration arises because integration does not provide a unique solution.

The constant represents an arbitrary additive term that can vary depending on the specific problem or additional constraints.

To determine the constant of integration, we may need additional information or consider specific conditions related to the problem.

It is also important to note that the accuracy of estimating the underlying function f(x - i) depends on the quality and quantity of the observed data points f'(x - i). More data points and precise measurements can lead to a better estimation of the underlying function.

Additionally, the behavior of the function at a specific point can provide valuable insights for determining the constant of integration and refining the estimation of the underlying function.

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Answer:

B.84 sq.units

Step-by-step explanation:

Adding both rectangles

12 + 72

84sq.units

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Yes, gender is a significant factor affecting job hiring outcomes.

Gender is a crucial factor that significantly influences whether a person will be hired for a job. In my analysis strategy, I would compare two groups based on gender: male job applicants and female job applicants. To represent and summarize the data, I would gather information on the number of job applicants and the number of successful hires for each gender.

By comparing the proportions of successful hires between the two groups, I can assess the impact of gender as a determining factor in job hiring outcomes. To analyze the data, I would employ a statistical T test to compare the means of the two groups (males vs. females). The T test allows me to determine if the difference in hiring rates between males and females is statistically significant.

Additionally, I would utilize Levene's Test for Equality of Variances to assess whether the variances of the two groups are significantly different. This step is important to ensure that the groups have comparable levels of variability before conducting the T test.

Statistical tests like the T test and Levene's Test for Equality of Variances provide valuable insights into the influence of gender disparities. These tests help researchers evaluate whether the observed differences are statistically significant or merely due to chance. By employing robust statistical analysis, we can gather reliable evidence to support or refute the hypothesis that male job applicants have a higher likelihood of getting hired compared to female job applicants.

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Answer:

R=70.20-$0.80(12)

Step-by-step explanation: