A number that produces a specific number when multiplied by itself.

Answer:

B.5/6 and 10/12

Step-by-step explanation:

   The given values are;

          \(\frac{5}{6}\)   and  \(\frac{10}{12}\)  

   \(\frac{10}{12}\)  ,

    reducing to the smallest term by dividing by 2;

       is   \(\frac{5}{6}\)  

So;

  \(\frac{5}{6}\)   and  \(\frac{10}{12}\)   are both like fractions.

Answer:

B

Step-by-step explanation:

√((-20)²+21²)=√(400+441)=√841=29

cos θ=-20/29

sec θ=-29/20

Recall that

cos(A + B) = cos(A) cos(B) - sin(A) sin(B)

sin(A + B) = sin(A) cos(B) + cos(A) sin(B)

By definition of cotangent,

cot(A + B) = 1 / tan(A + B) = cos(A + B) / sin(A + B)

and by applying the identities above,

cot(A + B) = (cos(A) cos(B) - sin(A) sin(B)) / (sin(A) cos(B) + cos(A) sin(B))

Now, multiply the expression on the right by 1/(sin(A) sin(B)) to get

cot(A + B) = (cot(A) cot(B) - 1) / (cot(B) + cot(A))

Given tan(A) = 1/4 and tan(B) = 1/5, we have cot(A) = 4 and cot(B) = 5, so that

cot(A + B) = (4×5 - 1) / (5 + 4) = 19/9

Answer:

the answer is C

Step-by-step explanation:

Answer:

a set of four data pairs with a correlation coefficient r = –0.8

Step-by-step explanation:

edg 2022

Answer:

The sweater costs $42 including sales tax.

Step-by-step explanation:

To find this answer, you would first need to find the dollar amount of the sweater's sales tax.

$40 * 5% (or .05) = $2

You would then need to add the sales tax to the current total for your final answer.

$40 + $2 = $42

Answer:

7.1

Step-by-step explanation:

area of a circle is pi times the radius squared

so divide the diameter by 2 to get the radius

then thats 1.5 so square that then multiply by pi

Answer:

ur answer is 7.1

Step-by-step explanation:

The approximate volume of the sphere is 6.01 ft³.

A sphere is simply a three-dimensional geometric object that is perfectly symmetrical in all directions.

The volume of a sphere is expressed as:

Volume =  (4/3)πr³

Where r is the radius of the sphere and π is the mathematical constant pi (approximately equal to 3.14).

Given that the surface area of the sphere is 16 square feet.

First, we determine the radius r:

Surface area = 4πr²

Hence

16 = 4πr²

Dividing both sides by 4π, we get:

r² = 16/4πr

r = √( 16/4πr )

r = 1.128 ft

Plugging in the value of r that we just found, we get:

Volume =  (4/3)πr³

Volume =  (4/3) × 3.14 × (1.128 ft)³

Volume =  6.01 ft³

Therefore, teh volume is 6.01 ft³.

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When the sample size is small and the population distribution is not normal, the mean is a biased estimate.

Nonetheless, the bias of the mean reduces as the sample size grows, making it a more trustworthy estimator. As a result, the mean is the biased estimator whose bias will decrease as the sample size increases.

Increasing the sample size has no impact on the bias of the median, standard deviation, and range estimators since they are non-biased estimators.

These estimators may, however, be made more precise and accurate by increasing the sample size, which increases their dependability for predicting population parameters.

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Complete question:

Which biased estimator will have a reduced bias based on increased sample size? mean median standard deviation range

Answer:

\(v = 21\)

Step-by-step explanation:

\(21 = - 7v + 8v \\ 21 = v \)

I hope I helped you^_^

When the level of significance is 0.07, the corresponding confidence level is 93%.

The level of significance (α) in statistical hypothesis testing represents the probability of rejecting the null hypothesis when it is actually true. In contrast, the confidence level represents the degree of certainty or reliability we have in the estimated results from a statistical analysis.

The confidence level is calculated as the complement of the level of significance, subtracted from 1. In this case, if the level of significance is 0.07, we subtract it from 1 to find the confidence level:

Confidence level = 1 - level of significance

Confidence level = 1 - 0.07

Confidence level = 0.93 or 93%

Therefore, when the level of significance is 0.07, the corresponding confidence level is 93%. This means that we can be 93% confident that the estimated results from a statistical analysis will fall within the desired range, while allowing for a 7% chance of Type I error (rejecting the null hypothesis when it is true).

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The growth rate between 2015 and 2016 of this random variable was 2%.

Given that the data collection is {100, 102, 104, 106, 105, 108}.

First element 100 is the value of some random variable in year 2015.102 is the value of the random variable in year 2016.Now the growth rate between 2015 and 2016 of this random variable was (in %) .

Growth rate= (final value - initial value)/initial value×100Given initial value=100, final value=102Growth rate= (102-100)/100 × 100=2%

Therefore, the growth rate between 2015 and 2016 of this random variable was 2%.

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Answer:

what situation?

Step-by-step explanation:

Answer:

a<x and x<b

Step-by-step explanation:

because there is no situation provided, here is an example of what it would be

Answer:

d

Step-by-step explanation:

Option D "The location of the stage between floor and the top of the bookcase" is the correct answer.

This is because, the distance between stage to floor and stage to top of the bookcase , the common is stage . Therefore, stage is equidistant from both bookcase and floor.

By Benjemin

Answer:

7. <ekh and <fkg

8. <ekf and <hkg

9. <hke and <ekf

10. <jkg and <gkf

11. <jkg

12. <hkg

Step-by-step explanation:

The probability that it will not snow on January 1st in that town in a given year is 0.815.

Based on the meteorological records, A probability forecast includes a numerical expression of uncertainty about the quantity or event being forecast. Ideally, all elements (temperature, wind, precipitation, etc.)

The probability that it will not snow in a certain town on January 1st in a given year is 0.815. Here's how to arrive at the answer:Given that the probability of snowing on January 1st in that town is 0.185. Then, the probability of not snowing on January 1st is 1 - 0.185 = 0.815.

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The given information probability of it not snowing on January 1st of a given year in that town is 0.815.

Therefore, the probability of it not snowing on January 1st of a given year in that town is 0.815.

Here's how to solve the problem: Given: The probability of it snowing on January 1st of a given year in that town is 0.185. The complement of the probability of it snowing on January 1st is the probability of it not snowing on January 1st of a given year in that town, which is:

P(not snowing on January 1st) = 1 - P(snowing on January 1st)

P(not snowing on January 1st) = 1 - 0.185

P(not snowing on January 1st) = 0.815

Therefore, the probability of it not snowing on January 1st of a given year in that town is 0.815.

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Given :

▪︎Measure of ∠R = 90°

▪︎Segment OR = Segment RN

Which will mean, ∠O = ∠N.

Thus :

\( =\tt ∠R + ∠O + ∠ + N = 180\)

\( = \tt90 + x + x = 180\)

\( =\tt 90 + 2x = 180\)

\( = \tt2x = 180 - 90\)

\( =\tt 2x = 90\)

\( =\tt x = \frac{90}{2} \)

\( =\tt x = 45\)

Which means :

Measure of ∠O = 45°

Measure of ∠N = 45°

Therefore, the measures of these angles in ascending order = 45,45,90.

Answer:

3 OR 8  hope this helps!

Step-by-step explanation:

Answer:

22 lawns could be mowed as it takes 1.5 hours per lawn.

If they sold six lizards they would earn $71.82

If a storage tank holds 50,000 gallons of water then its volume is 189.25 cubic meters.

The volume of the storage tank in cubic meters can be calculated by first converting the volume from gallons to liters and then converting from liters to cubic meters.

Step 1: Convert the volume from gallons to liters:
50,000 gallons * 3.785 liters/gallon = 189,250 liters

Step 2: Convert the volume from liters to cubic meters:
189,250 liters * (1 cubic meter/1000 liters) = 189.25 cubic meters

Therefore, the volume of the storage tank is 189.25 cubic meters.

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To find the critical values for the given distribution with a significance level of \( \alpha = 0.10 \) and degrees of freedom (\( df \)) equal to 18, we need to determine the critical values for both the z-distribution (Zc) and the t-distribution (TC).

These critical values are used to establish the rejection region in hypothesis testing.

For the z-distribution, since the degrees of freedom are not specified, we can directly find the critical value using the standard normal distribution table or software. With a significance level of 0.10, the critical value for the upper tail (Zc) is 1.28 (rounded to 2 decimal places).

For the t-distribution, we use the degrees of freedom (df = 18) to find the critical value from the t-distribution table or software. With a significance level of 0.10 and 18 degrees of freedom, the critical value (TC) is approximately 1.33 (rounded to 2 decimal places).

Therefore, the critical values for the given distribution with a significance level of \( \alpha = 0.10 \) and degrees of freedom (\( df \)) equal to 18 are Zc = 1.28 and TC = 1.33.

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The density of this certain material is 37.2 pounds per liter.

In Science and Mathematics, the density of a chemical or physical substance such as a material can be calculated by using the following formula:

Density = M/V

Where:

Conversion:

1 kg equals 2.20462 pounds

1 cup of volume equals 0.237 liter.

Density, d = (4 × 2.20462)/0.237

Density, d = 37.15 ≈ 37.2 pounds per liter.

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If f = q (v x b) and v is perpendicular to b, then the direction of b will be perpendicular to both f and v.

The cross product, also known as the vector product, is a mathematical operation performed between two vectors in three-dimensional space. The result of the cross product is another vector that is perpendicular to both original vectors.

If we have the cross product (v x b) v is perpendicular to b, then the direction of b will be perpendicular to both f and v. This is because the cross product of two vectors, v x b, will result in a vector that is perpendicular to both of the original vectors. Therefore, the direction of b will be in a direction that is perpendicular to both f and v.

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Answer:

\( 5.99 \times {10}^{ - 9} \\ \\ 1.80 \times {10}^{9} \\ \\ 3.42 \times {10}^{ - 9} \)

Step-by-step explanation:

Following numbers are written in scientific notations.

\(5.99 \times {10}^{ - 9} \\ \\ 1.80 \times {10}^{9} \\ \\ 3.42 \times {10}^{ - 9} \)

To determine whether the sequence converges or diverges, we can use the Squeeze Theorem.

We can see that

4/ n+5n^2 < = An <= 4+3n^2/ n+5n^2

As n tends to infinity,  4/ n+5n^2  tends to 0 and 4+3n^2/ n+5n^2 tends to  4/5n^2 which also tends to 0.

So by the Squeeze Theorem, we can say that An tends to 0 as n tends to infinity. Hence the limit of the sequence is Lim n-> An = 0

We can also see that the numerator of An is a constant and the denominator is a polynomial with degree 2. Since the denominator's degree is greater than the numerator, the limit will be zero as n -> infinity.

Therefore, the sequence converges to 0.

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Answer:

a=6 b=4 3=2.55555555567

Answer:

127°

Step-by-step explanation:

I remember a teacher gave me a solution to solve these types of questions.

choose only one corner and draw lines from that Corner to the rest of the corners to form triangles.

for example, in this question, I choose 120°. 1 line to 125°, 1 to 133°, one to 112°. you can't draw any straight lines to the rest of the corners.

now you have 4 triangles. and the sum of the angles of each triangle, is 180°. so, the sum of the angles of this Irregular hexagon is 4×180=720°.

now:

112+133+120+100+128+x=720

593+x=720

x=720-593

x=127°

i know it seems a little complicated, but if you read it carefully, you'll probably understand.if anything is unclear, ask freely.

To obtain the residuals from the fit in 8.4a and plot them against y and x, as well as prepare a normal plot, we need the specific details of the fit and the data used.

WE know that residuals represent the differences between the observed values and the predicted values from a statistical model or regression analysis.

Since the residuals against y and x can help identify patterns or trends in the data that may indicate issues with the model's fit.

A normal plot, known as a Q-Q plot, compares the distribution of the residuals to a theoretical normal distribution. If the residuals closely follow a straight line in the normal plot, the residuals are normally distributed, which is an assumption of many statistical models.

Interpreting these plots involves examining the patterns and deviations from expected behavior. If the residuals exhibit a consistent pattern, it might indicate that the model does not capture all the relevant information in the data.

Thus if the residuals appear randomly scattered around zero with no discernible pattern, it suggests that the model adequately explains the data. Deviations in the normal plot may indicate departures from the assumption of normality in the residuals, which could impact the reliability of statistical inferences.

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