What is the solutions set for -4x - 10< 2?

Answer:

D

Step-by-step explanation:

1×2=2

1×\(\sqrt{3}\)=\(\sqrt{3}\)

The other leg of right triangle s is √3 units and hypotenuse of the right triangle is 2 units. Therefore, option D is the correct answer.

The sides and angles of a right-angled triangle are dealt with in Trigonometry. The ratios of acute angles are called trigonometric ratios of angles. The six trigonometric ratios are sine (sin), cosine (cos), tangent (tan), cotangent (cot), cosecant (cosec), and secant (sec).

In the given right triangle, one of the leg is 1 unit, other leg is s unit and the hypotenuse is h units.

We know that, tanθ=Opposite/Adjacent

So, tan30°=1/s

1/√3 = 1/s

s=√3

We know that, sinθ=Opposite/Hypotenuse

sin30°=1/h

1/2 = 1/h

h=2

Therefore, option D is the correct answer.

Learn more about the trigonometric ratios here:

brainly.com/question/25122825.

#SPJ7

Answer:

81.859%

Step-by-step explanation:

We solve the question using z score formula

z = (x-μ)/σ, where

x is the raw score

μ is the population mean = 80 mph

σ is the population standard deviation = 7 mph

For x = 66 mph

z = 66 - 80/7

z = -2

Probability value from Z-Table:

P(x = 66) = 0.02275

For x = 87 mph

z = 87 - 80/7

z = 1

Probabilith value from Z-Table:

P(x = 87) = 0.84134

The probability of the trials will give the DeLorean a speed between 66 mph and 87 mph is calculated as:

P(x = 87 mph) - P(x = 66 mph)

0.84134 - 0.02275

= 0.81859

The percentage of the trials will give the DeLorean a speed between 66 mph and 87 mph?

100 × 0.81859

81.859%

(A) Total number of points served by Samson and multiply by 100  (B) Null hypothesis(H0) and Alternative hypothesis (Ha) (C)  there would be a 24% chance of observing a difference in performance as extreme as the one observed in the data.

(D) Based on the p-value of 0.24, we do not have strong evidence to reject the null hypothesis. (E) it would be a Type II error. (F) Type II error would mean that we concluded there is no difference in Samson's performance when serving and when his opponent is serving, but in reality, there is a difference. (G) To reduce the likelihood of a Type II error occurring, we can increase the sample size (H)  No, we cannot conclude that Samson's serving is the cause of the difference in his ability to win points when serving compared to when his opponent is serving

a) The difference in the percentage of points won when serving and when the opponent is serving can be calculated by subtracting the percentage of points won when the opponent is serving from the percentage of points won when serving.  To find the percentage of points won when serving, we divide the number of points won when serving by the total number of points served by Samson and multiply by 100. Similarly, to find the percentage of points won when the opponent is serving, we divide the number of points won when the opponent is serving by the total number of points served by the opponent and multiply by 100.

b) The hypotheses we are interested in testing are:
- Null hypothesis (H0): There is no difference in Samson's performance when serving and when his opponent is serving.
- Alternative hypothesis (Ha): Samson performs better when serving compared to when his opponent is serving.

c) A p-value of 0.24 indicates that if the null hypothesis were true, there would be a 24% chance of observing a difference in performance as extreme as the one observed in the data. In other words, the p-value represents the probability of obtaining the observed difference in performance or a more extreme difference, assuming that there is no actual difference in Samson's performance when serving.

d) Based on the p-value of 0.24, we do not have strong evidence to reject the null hypothesis. This means that the data does not provide convincing evidence that Samson plays better when serving compared to when his opponent is serving.

e) If our conclusion from part d was in error, it would be a Type II error. This occurs when we fail to reject the null hypothesis even though it is false. In this case, it would mean that there is a difference in Samson's performance when serving, but we failed to detect it.

f) In the context of this question, a Type II error would mean that we concluded there is no difference in Samson's performance when serving and when his opponent is serving, but in reality, there is a difference. This could potentially lead to underestimating Samson's ability to perform better when serving.

g) To reduce the likelihood of a Type II error occurring, we can increase the sample size. By collecting more data, we can increase the power of our test and improve our ability to detect a difference in performance if it truly exists. Additionally, we can also adjust the significance level of our test (e.g., from 0.05 to 0.01) to make it more likely to detect smaller differences.

h) No, we cannot conclude that Samson's serving is the cause of the difference in his ability to win points when serving compared to when his opponent is serving. The data provided only shows an association between serving and winning points, but it does not establish a causal relationship. Other factors, such as skill, strategy, or the opponent's performance, could also contribute to the difference observed. To establish causality, further investigation and controlled experiments would be needed.

To know more about hypotheses refer to:

https://brainly.com/question/25263462

#SPJ11

Answer:

x=25

Step-by-step explanation:

because i divided

The fraction cannot be worked out, given the information on the numerator being even and the denominator being odd.

When fractions are said to be in their simplest forms as 1 / 1, then it means that both the numerator and the denominator are the same. This way, they can divide each other and leave one.

For such a situation to happen, the numbers will have to either both be even numbers, or odd numbers. The numerator cannot be even while the denominator is odd.

This fraction therefore cannot be worked out.

Find out more on fractions at https://brainly.com/question/27852893

#SPJ1

Answer:

Vertex: ( − 5 , − 9 ) Focus: ( − 5 , − 35 4 ) Axis of Symmetry: x = − 5 Directrix: y = − 37 4 Select a few x values, and plug them into the equation to find the corresponding y values. The x values should be selected around the vertex. Tap for more steps... x y − 7 − 5 − 6 − 8 − 5 − 9 − 4 − 8 − 3 − 5 Graph the parabola using its properties and the selected points. Direction: Opens Up Vertex: ( − 5 , − 9 ) Focus: ( − 5 , − 35 4 ) Axis of Symmetry: x = − 5 Directrix: y = − 37 4 x y − 7 − 5 − 6 − 8 − 5 − 9 − 4 − 8 − 3 − 5

Hoped I helped

Answer:

It's the one that's on the left of the y axis. I took the test.

Answer:

the car is traveling 60 miles per hour

Step-by-step explanation:

Since it is going 30 miles in half an hour, we just need to double both values to find the speed for an hour

30*2=60

1/2*2=1

60 miles per hour

hope this helps pls give crown <3

Answer:24

Step-by-step explanation: 4(3)= 12.  -6(-2)= 12 Add them, equals 24

Lower class limits are 15, 25, 35, 45, 55, 65, 75, Upper class limits are 24, 34, 44, 54, 64, 74, 84, Class width are 10 (all classes have a width of 10), Class midpoints are 19.5, 29.5, 39.5, 49.5, 59.5, 69.5, 79.5, Class boundaries are [15, 25), [25, 35), [35, 44), [45, 54), [55, 64), [65, 74), [75, 84) and Number of individuals included in the summary is 76.

Here are the details for the given frequency distribution:

Lower class limits are the least number among the pair

Here, Lower class limits are 15, 25, 35, 45, 55, 65, 75 respectively.

Upper class limits are the greater number among the pair

Here, upper limit class are 24, 34, 44, 54, 64, 74, 84 respectively.

Class width is the difference between the Lower class limits and Upper class limits which is 10 (all classes have a width of 10).

Class midpoints is the middle point of the lower class limits and Upper class limits which is 19.5, 29.5, 39.5, 49.5, 59.5, 69.5, 79.5 respectively.

Class boundaries are the extreme points of the classes which are  [15, 25), [25, 35), [35, 44), [45, 54), [55, 64), [65, 74), [75, 84) respectively.

Number of individuals = 27 + 33 + 14 + 4 + 6 + 1 + 1

                                     = 76

To learn more about Lower class limits here:

https://brainly.com/question/29027902

#SPJ4

The p-value for a t-score of -0.92 is approximately 0.18 and since it is greater than the significant level, the null hypothesis is rejected.

The first step in testing this hypothesis is to calculate the test statistic, which in this case is a t-score. The formula for the t-score is (y - mu) / (s / sqrt(n)), where y is the sample mean, mu is the hypothesized population mean, s is the sample standard deviation, and n is the sample size.

In this case, the sample mean is 25.9, the hypothesized population mean is 26, the sample standard deviation is 7.6, and the sample size is 50. Plugging these values into the formula, we get a t-score of -0.92.

Next, we need to find the p-value associated with this t-score. We can use a t-table or a calculator to do this. Using a t-table with 49 degrees of freedom (since we have a sample size of 50 and one parameter estimated from the sample), we find that the p-value for a t-score of -0.92 is approximately 0.18.

Since the p-value is greater than the significance level of 0.05, we fail to reject the null hypothesis. In other words, we do not have substantial evidence to conclude that the population mean is less than 26. However, it is important to note that the sample mean is slightly below the hypothesized population mean, and the p-value is relatively close to the significance level. Therefore, it may be worthwhile to conduct additional studies with larger sample sizes or different populations to further investigate this question.

Know more about null hypothesis here:

https://brainly.com/question/19263925

#SPJ11

The volume of oil exiting the pipe is approximately 100 cu in/hr, 2,400 cu in/day, and 1.39 cu ft/day when converting cu in/day to cubic feet per day.



To calculate the volume of oil exiting the pipe every hour, you would need to know the flow rate of the oil in cubic inches per hour. Let's assume the flow rate is 100 cubic inches per hour.To find the volume of oil exiting the pipe every day, you would multiply the flow rate by the number of hours in a day. There are 24 hours in a day, so the volume of oil exiting the pipe every day would be 100 cubic inches per hour multiplied by 24 hours, which equals 2,400 cubic inches per day.

To convert the volume from cubic inches per day to cubic feet per day, you would need to divide the volume in cubic inches by the number of cubic inches in a cubic foot. There are 1,728 cubic inches in a cubic foot. So, dividing 2,400 cubic inches per day by 1,728 cubic inches per cubic foot, we get approximately 1.39 cubic feet per day.

Therefore, the volume of oil exiting the pipe is approximately 100 cubic inches per hour, 2,400 cubic inches per day, and 1.39 cubic feet per day.

To learn more about volume click here

brainly.com/question/22907480

#SPJ11

The scatterplot that displays the line of best fit for the data would be the scatterplot that includes the calculated line of best fit plotted on the graph along with the data points.

A line of best fit, also known as a regression line, is a line that represents the relationship between two variables in a scatterplot. The line of best fit is used to describe the overall trend in the data and can be used to make predictions about one variable based on the values of the other variable.

The line of best fit in a scatterplot can be represented as a straight line, a polynomial, or another type of mathematical function, depending on the relationship between the variables. To find the line of best fit, the student would need to use statistical techniques such as linear regression or polynomial regression to calculate the equation of the line that best represents the data.

The line of best fit is then plotted on the scatterplot along with the data points, creating a visual representation of the relationship between the two variables. The line of best fit can be used to make predictions about one variable based on the values of the other variable, and to determine the strength and direction of the relationship between the two variables.

Thus, In conclusion, the scatterplot that displays the line of best fit for the data would be the scatterplot that includes the calculated line of best fit plotted on the graph along with the data points.

To learn more about scatterplots,

Visit; brainly.com/question/5102661

#SPJ4

The scatterplot that displays the line of best fit for the data is the scatterplot that includes the computed line of best fit drawn on the graph with the data points.

The scatterplot that includes the computed line of best fit shown on the graph with the data points is the scatterplot that displays the line of best fit for the data.

A line of best fit, also known as a regression line, is a line in a scatterplot that illustrates the connection between two variables. The line of best fit is used to depict the general trend in the data and may be used to forecast one variable based on the values of another.

Depending on the relationship between the variables, the line of best fit in a scatterplot can be depicted as a straight line, a polynomial, or another sort of mathematical function. The learner would need to apply statistical techniques such as linear regression or polynomial regression to derive the equation of the line that best represents the data in order to obtain the line of best fit.

The line of best fit is then drawn alongside the data points on the scatterplot, producing a visual depiction of the connection between the two variables. The line of best fit may be used to anticipate the value of one variable based on the value of another variable, as well as to identify the strength and direction

To summarize, the scatterplot that displays the line of best fit for the data is the scatterplot that includes the computed line of best fit drawn on the graph with the data points.

To learn more about data points click here :

brainly.com/question/17148634

#SPJ4

Answer:

First bank last function

Second blank, the middle function

Third blank, middle function

Fourth blank, first function

There are three types of systems of linear equations in two variables: Consistent System,Inconsistent System,Dependent System.

A linear system is a mathematical model of a system of linear equations, in which the variables and constants have a linear relationship. This type of system is widely used in engineering, physics, economics, and other areas of study. Linear systems are often used to find solutions to problems in areas such as optimization or forecasting. They are also used in many machine learning algorithms. Linear systems are characterized by their linearity and they are usually solved using linear algebra techniques.

1. Consistent System: A consistent system of linear equations in two variables has at least one solution. This means that there is at least one set of values for the two variables that will make all equations true.

2. Inconsistent System: An inconsistent system of linear equations in two variables has no solution. This means that there is no set of values for the two variables that will make all equations true.

3. Dependent System: A dependent system of linear equations in two variables has an infinite number of solutions. This means that there is more than one set of values for the two variables that will make all equations true.

To know more about linear systems click-
https://brainly.com/question/2248255
#SPJ4

Selecting all students with last names beginning with the letter M would not produce a random sample of a school population of 1000 students. Hence the answer is no.

A random sample is obtained by selecting individuals from a population in a way that ensures every member of the population has an equal chance of being included in the sample.

By choosing only students with last names beginning with the letter M, you are introducing a bias and not providing an equal chance for all students to be selected.

To obtain a random sample of 1000 students from a school population, you would need to use a random selection method that ensures each student has an equal probability of being chosen.

This could be achieved through techniques such as random number generators, random sampling software, or random sampling techniques like stratified or cluster sampling.

Selecting all students with last names beginning with the letter M would not meet the requirements of a random sample, as it would not provide an equal chance for all students in the population to be included.

To know more about random sample refer here:

https://brainly.com/question/33334850#

#SPJ11

Answer:

16

Step-by-step explanation:

8/ 2*(2+2) = 4*(2+2) = 4*4 = 16

Answer:

\(y - 3 = - 4(x + 2)\)

The results obtained using the algebraic approach and the matrix approach should be the same. Both methods are mathematically equivalent and provide the most probable values of A and B that minimize the sum of squared weighted residuals.

To solve the system of equations using the weighted least squares method, we need to minimize the sum of the squared weighted residuals. Let's solve the problem using both the algebraic approach and matrices.

Algebraic Approach:

We have the following equations:

A + 2B = 10.50 + V1 ... (1)

2A - 3B = 5.55 + V2 ... (2)

2A - B = -10.50 + V3 ... (3)

To minimize the sum of squared weighted residuals, we square each equation and multiply them by their respective weights:

\(2^2 * (A + 2B - 10.50 - V1)^2\)

\(3^2 * (2A - 3B - 5.55 - V2)^2\\1^2 * (2A - B + 10.50 + V3)^2\)

Expanding and simplifying these equations, we get:

\(4(A^2 + 4B^2 + 10.50^2 + V1^2 + 2AB - 21A - 42B + 21V1)\\9(4A^2 + 9B^2 + 5.55^2 + V2^2 + 12AB - 33A + 16.65B - 11.1V2)\\(A^2 + B^2 + 10.50^2 + V3^2 + 2AB + 21A - 21B + 21V3)\\\)

Now, let's sum up these equations:

\(4(A^2 + 4B^2 + 10.50^2 + V1^2 + 2AB - 21A - 42B + 21V1) +\\9(4A^2 + 9B^2 + 5.55^2 + V2^2 + 12AB - 33A + 16.65B - 11.1V2) +\\(A^2 + B^2 + 10.50^2 + V3^2 + 2AB + 21A - 21B + 21V3)\int\limits^a_b {x} \, dx\)

Simplifying further, we obtain:

\(14A^2 + 31B^2 + 1113 + 14V1^2 + 33V2^2 + 14V3^2 + 14AB - 231A - 246B + 21V1 - 11.1V2 + 21V3 = 0\)

Now, we have a single equation with two unknowns, A and B. We can use various methods, such as substitution or elimination, to solve for A and B. Once the values of A and B are determined, we can substitute them back into the original equations to find the most probable values of A and B.

Matrix Approach:

We can rewrite the system of equations in matrix form as follows:

| 1 2 | | A | | 10.50 + V1 |

| 2 -3 | | B | = | 5.55 + V2 |

| 2 -1 | | -10.50 + V3 |

Let's denote the coefficient matrix as X, the variable matrix as Y, and the constant matrix as Z. Then the equation becomes:

X * Y = Z

To solve for Y, we can multiply both sides of the equation by the inverse of X:

X^(-1) * (X * Y) = X^(-1) * Z

Y = X^(-1) * Z

By calculating the inverse of X and multiplying it by Z, we can find the values of A and B.

Comparing Results:

The results obtained using the algebraic approach and the matrix approach should be the same. Both methods are mathematically equivalent and provide the most probable values of A and B that minimize the sum of squared weighted residuals.

For more such questions on matrix visit:

https://brainly.com/question/1279486

#SPJ8

Answer:

C Subtraction property of equality

Step-by-step explanation:

You are subtracting 21 from both sides in step 3

Answer:

I would guess C

Step-by-step explanation:

I hope I'm correct, good luck.

The dimensions of the rectangle with a perimeter of 98 cm are 34 cm by 15 cm.

To find the dimensions of the rectangle, we need to use the formula for the perimeter of a rectangle, which is P = 2l + 2w, where P is the perimeter, l is the length, and w is the width.

In this case, the length is 2(3x - 1) cm and the width is (2x + 3) cm. We are given that the perimeter is 98cm, so we can plug in these values into the formula and solve for x:

98 = 2(2(3x - 1)) + 2(2x + 3)

98 = 4(3x-1) + 2(2x+3)

98 = 12x - 4 + 4x + 6

98 = 16x + 2

96 = 16x

x = 6

Now that we know the value of x, we can plug it back into the expressions for the length and width to find the dimensions of the rectangle:

Length = 2(3x - 1) = 2(3(6) - 1) = 2(17) = 34 cm

Width = (2x + 3) = (2(6) + 3) = 15 cm

So, the dimensions of the rectangle are 34 cm by 15 cm.

Learn more about perimeter of rectangle here: https://brainly.com/question/19819849.

#SPJ11

Answer:

Step-by-step explanation:

Step-by-step explanation:

To find the Highest Common Factor (H.C.F.) of 567 and 255 using Euclid's division lemma, we can follow these steps:

Step 1: Apply Euclid's division lemma:

Divide the larger number, 567, by the smaller number, 255, and find the remainder.

567 ÷ 255 = 2 remainder 57

Step 2: Apply Euclid's division lemma again:

Now, divide the previous divisor, 255, by the remainder, 57, and find the new remainder.

255 ÷ 57 = 4 remainder 27

Step 3: Repeat the process:

Next, divide the previous divisor, 57, by the remainder, 27, and find the new remainder.

57 ÷ 27 = 2 remainder 3

Step 4: Continue until we obtain a remainder of 0:

Now, divide the previous divisor, 27, by the remainder, 3, and find the new remainder.

27 ÷ 3 = 9 remainder 0

Since we have obtained a remainder of 0, the process ends here.

Step 5: The H.C.F. is the last non-zero remainder:

The H.C.F. of 567 and 255 is the last non-zero remainder obtained in the previous step, which is 3.

Therefore, the H.C.F. of 567 and 255 is 3.

When two normal distributions have the same mean, but different standard deviations, the distribution with the larger standard deviation will have a wider spread, while the distribution with the smaller standard deviation will have a narrower spread.

We have,

Let's consider two normal distributions with a mean of 50.

One distribution has a standard deviation of 5, while the other has a standard deviation of 15.

The distribution with the smaller standard deviation of 5 will have the majority of the data points clustered closely around the mean of 50.

This means that there will be less variation in the data and the curve will be taller and narrower.

On the other hand,

The distribution with the larger standard deviation of 15 will have more variation in the data, resulting in a flatter and wider curve.

The data points will be more spread out, with some data points falling far away from the mean of 50.

Thus,

When two normal distributions have the same mean, but different standard deviations, the distribution with the larger standard deviation will have a wider spread, while the distribution with the smaller standard deviation will have a narrower spread.

Learn more about normal distribution here:

https://brainly.com/question/31327019

#SPJ1

Based on the information provided and considering the terms "pendulum" "positions a, b, and c," and "neglect friction," the true statement about the swinging pendulum is:

At position A, the pendulum has maximum potential energy and no kinetic energy. As it swings towards position B, its potential energy decreases while its kinetic energy increases. At position B, the pendulum has maximum kinetic energy and minimum potential energy. Then, as it moves towards position C, the kinetic energy decreases while the potential energy increases. At position C, it has the same potential energy as at position A, and the cycle repeats.

Potential energy is the energy possessed by an object due to its position or configuration relative to other objects. It is a form of stored energy that has the potential to be converted into other forms of energy and do work.

In the case of an object in a gravitational field, such as a pendulum, potential energy is associated with its vertical position above a reference point, often the ground. The higher the object is lifted, the greater its potential energy. The two most common forms of potential energy are gravitational potential energy and elastic potential energy.

To know more about gravitational potential energy, visit:

https://brainly.com/question/3910603

#SPJ11

Answer:

768 cookies

Step-by-step explanation:

48 divided by 3= 16

16 * 48= 768

The y-intercept of the quadratic function f(x) = (x – 8)(x + 3) is (0, –24).

The quadratic function f(x) = (x – 8)(x + 3) is given. In the general form, a quadratic equation can be represented as f(x) = ax² + bx + c, where x is the variable, and a, b, and c are constants. We can rewrite the given quadratic function into this form: f(x) = x² - 5x - 24Here, the coefficient of x² is 1, so a = 1. The coefficient of x is -5, so b = -5. And the constant term is -24, so c = -24. Hence, the quadratic function is f(x) = x² - 5x - 24. Now, to find the y-intercept of this function, we can substitute x = 0. Therefore, f(0) = 0² - 5(0) - 24 = -24. So, the y-intercept of the quadratic function f(x) = (x – 8)(x + 3) is (0,-24).The y-intercept of the quadratic function f(x) = (x – 8)(x + 3) is (0, -24).

To know more about y-intercept visit:

https://brainly.com/question/14180189

#SPJ11

Answer:

L x W = 432

Step-by-step explanation:

18 X 24 = 432

The ellis weight is heavier and by 7.23 lbs.

We are given that;

Weight= 5pounds

Now,

To convert Ed’s weight from kilograms to pounds, we can multiply by the conversion factor of 2.20462262185. We get:

Ed’s weight in pounds = 50 kg * 2.20462262185 lbs/kg Ed’s weight in pounds = 110.2311310925 lbs

To convert Ellis’s weight from stones and pounds to pounds, we can multiply the number of stones by 14 and add the number of pounds. We get:

Ellis’s weight in pounds = 7 stones * 14 lbs/stone + 5 lbs Ellis’s weight in pounds = 98 + 5 Ellis’s weight in pounds = 103 lbs

To compare the weights, we can subtract them and see which one is larger. We get:

Ed’s weight - Ellis’s weight = 110.2311310925 lbs - 103 lbs Ed’s weight - Ellis’s weight = 7.2311310925 lbs

Therefore, by unitary method the answer will be 7.23 lbs.

Learn more about the unitary method, please visit the link given below;

https://brainly.com/question/23423168

#SPJ1