Question A & Question B

Answer:

Ki lekso?

Step-by-step explanation:

Kisu bujina

Answer:

I need some help in this part

solving system of equations in 3 variable

-×-5y+z=17

-5×-5y+5z=5

2×+5y-3z=-10

HELP PLEASEEEEE

Answer:

AB/ZX and CB/YX and AC/ZY

Step-by-step explanation:

Hope this helps :)

Answer:

Rational

Step-by-step explanation:

irrational numbers aren't ever repeating

gimme braliest plz

The maximum number of real zeros in a polynomial will same as its degree thus 3 degrees will have 3 zeros.

The roots of an equation are the solution of that equation since an equation consists of hidden values of the variable to determine them by different processes and then the resultant is called roots.

An n degree of a polynomial can have a maximum of n number of variables.

For example, a quadratic equation ax² + bx + c = 0 is a two-degree equation so it has a maximum of two roots or zeros.

As per the given a polynomial is having 3 degrees so it will have exactly 3 roots.

Hence "A polynomial can have as many real zeros as the number of degrees it has, therefore one with three degrees can have up to three of them.".

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Answer:

y= 7/9x -17/9

Step-by-step explanation:

(5,2) (-4,-5)

slope intercept of a line is

y = mx +b

m = y2-y1/ x2-x1

= -5-2/ -4-5 = -7/-9

=7/9

if the line is passing through (5,2)

2= 7/9(5)+ b

2=35/9 +b

b = 2-35/9

b= -17/9

y= 7/9x -17/9

Answer :

is approximately 100 cm ²

Step -by-step explanation

\(r \: = 10 \\ l \: = 21.81 \\ T.S.A \: of a \: cone\: = \pi \times r(r + l)\)

\( \frac{22}{7} \times 10(10 + 21.81) \\ \frac{22}{7} \times 10(31.81) \\ \frac{22}{7} \times 318.1\)

\( \frac{22}{7} \times 318.1 \\ = 999.7 \\ = 100 {cm}^{2} \)

We cannot compute the percentage of variation in final exam scores, Without knowing the correlation coefficient or regression equation.

To determine the percentage of variation in final exam scores that is explained by the linear relationship with Internet instruction time, we need to calculate the coefficient of determination, denoted \(R^2.\)

R-squared is the proportion of the variance of the dependent variable (final grade) that can be explained in a linear regression model by the independent variable (internet class hours).

It ranges from 1, showing that the demonstration does not clarify the change, and 1 demonstrating that the demonstration clarifies all the fluctuation.

In case you've got as of now calculated the relationship coefficient (r) between Web class hours and last exam scores, you'll be able to calculate \(R^2\)as follows:

\(R^2 = r^2\)

Then again, once you've got the relapse condition, you'll be able to compute\(R^2\)the square of the relationship between the anticipated and genuine values ​​of the subordinate variable. 

\(R^2 = (SSR/SST)\)

where SSR is the sum of squared residuals (also called the explained sum of squares) and SST is the total sum of squares.

You cannot calculate \(R^2\)without knowing the correlation coefficient or the regression equation.

Therefore, we need more information on studies such as:  Using data or summary statistics,

to determine the value of \(R^2\)to determine the percentage of variation in final exam scores explained by a linear relationship with Internet instruction time.  

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Answer:

Step-by-step explanation:

always follow BODMAS or BIDMAS-

Do the multiplication, which is 15/3 and when simplifiyed becomes 5.

Then work out 6 divided by 3/2. In division for fractions, you always find the reciprocal of the 2nd number and multiply instead of divide, so its 6 x 2/3 which is 12/3, simplifiyed to be 4. 5+4=9. 9+10 is 19, and 19-4=15

Answer:

Y= -1/3 |x+3| +5

Step-by-step explanation:

An absolute value will always make a V line.

In your particular problem it wants you to reflect it over the x axis, and to do this you simply need to place a negative.

A negative in the beginning of the problem is only there to say whether you flip your line or not, and this means you don't have to worry about it any more.

What it looks like so far: Y= -

Next it wants you to compress the line vertically by 1/3

A number that causes your line to compress is always less than one

A number that stretches your line would be 1 or more

This number is always placed right next to the left of the parenthesis or absolute value.

What it looks like so far: Y= - 1/3

Now we want the line to move left 3 units.

We are now inside of the absolute value because this is where we move the line left or right. This can get a little confusing, but once you get it then you don't forget it.

Inside the line.. a -# moves right and a +# moves left.

This number should be placed inside the absolute value and to the right of the x.

What it should look like: Y= - 1/3 |x + 3|

Now they want us to move the line up by 5 points.

To the outer right side of the absolute value is where we move things up or down.

To move a number up you need to place a + sign with however many places it wants you to move to the right of the sign, but to move the line down you need to place a - sign with however many places it wants you to move to the right of the sign.

To move this up you simply need to place a +5 to the outer right side of the absolute value.

What you should end up with: Y= - 1/3 |x+3| +5

The approximate area covered by the cell tower without any devices is 2,827.4 square miles.

The area of a circle with a radius of 30 miles is calculated using the formula A = πr^2, where A is the area and r is the radius. Substituting in the values, we get A = 3.14 x 30^2 = 2,827.4 square miles.

However, one-quarter of this area has a device, which means that the actual area covered by the cell tower without any devices is 75% of 2,827.4, or approximately 2,120.55 square miles. We round this value to the nearest tenth, which gives us the answer of 2,120.6 square miles.

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The solution to the problem ut - kuxx + tu = 0 with u(x,0) = e^-x and ux(0,t) = 0 is given by u(x,t) = e^(-x+t^2/2k).

To solve the problem ut - kuxx + tu = 0, with initial condition u(x,0) = e^-x and boundary condition ux(0,t) = 0 using the Fourier cosine transform, we can follow these steps:

Step 1: Apply the Fourier Cosine Transform

Apply the Fourier cosine transform to both sides of the partial differential equation with respect to the spatial variable x. The Fourier cosine transform pair for the derivative is given by:

C{uxx} = -ω^2C{u}

Using the properties of the Fourier cosine transform, we obtain:

∂(C{u})/∂t + kω^2C{u} + tC{u} = 0

Step 2: Solve the Transformed Equation

The transformed equation is now an ordinary differential equation in terms of the transform variable ω. Solve this equation using standard techniques for ordinary differential equations. The solution will involve an arbitrary function C{u}(ω) and the initial condition C{u}(ω, 0) = C{e^-x}(ω).

Step 3: Apply the Inverse Fourier Cosine Transform

Apply the inverse Fourier cosine transform to the solution obtained in step 2 to obtain the solution u(x, t) in the original variables:

u(x, t) = C^(-1){C{u}(ω)}

Step 4: Apply the Initial and Boundary Conditions

Use the given initial condition u(x, 0) = e^-x and boundary condition ux(0, t) = 0 to determine the specific form of the arbitrary function C{u}(ω) and obtain the final solution u(x, t).

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By answering the presented question, we may conclude that I used the following procedures to produce this graph.

Mathematicians use graphs to visually display or chart facts or values in order to express them coherently. A graph point usually represents a connection between two or more items. A graph, a non-linear data structure, is made up of nodes (or vertices) and edges. Glue the nodes, also known as vertices, together. This graph contains vertices V=1, 2, 3, 5, and edges E=1, 2, 1, 3, 2, 4, and (2.5), (3.5). (4.5). Statistical graphs (bar graphs, pie graphs, line graphs, and so on) are graphical representations of exponential development. a logarithmic graph shaped like a triangle.

I used the following procedures to produce this graph:

I classified the personnel as full-time, part-time, and temporary.

I estimated the proportion of employees who assessed the company's work-life balance as "very good" or "excellent" for each employee category, as well as the percentage who rated it as "good" or "fair/poor."

I used the following procedures to produce this graph:

I classified the personnel as full-time, part-time, and temporary.

I estimated the proportion of employees who assessed the company's work-life balance as "very good" or "excellent" for each employee category, as well as the percentage who rated it as "good" or "fair/poor."

I made the segmented bar graph using these percentages.

The graph was made using Excel technology. You may make a similar graph with Excel or any other software that supports segmented bar graphs.

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The amount that the painter will charge is $519.75.

From the information illustrated, the painter can paint 175 square feet per hour and she charges $0.54 per square foot and then paints for 5.5 hours.

The amount that she will charge will be:

= Number of square foot × Amount charged × Number of hours

= 175 × $0.54 × 5.5

= $519.75

The amount is $519.75.

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Kotaro made a total of 20 kites during his 15 hours of kite-making. He was able to make 8 kites in the first 3 hours and an additional 6 kites in the next 9 hours.

Kotaro's kite-making progress can be divided into two parts: the first 3 hours and the remaining 12 hours. During the first 3 hours, he made 8 kites according to his mom's count. This means that on average, he made 8 kites / 3 hours = 2.67 kites per hour.

To determine how many kites he made in the remaining 12 hours, we can use the average rate of kite-making from the first 3 hours. If Kotaro was able to make approximately 2.67 kites per hour, then in 12 hours, he would have made 2.67 kites/hour x 12 hours = 32 kites. However, we know that at the 12-hour mark, he had 14 kites in total.

To find the additional kites made in the next 12 hours, we subtract the kites he had at the 12-hour mark from the expected total: 32 kites - 14 kites = 18 kites. Therefore, in the remaining 12 hours, he made an additional 18 kites.

Adding the kites made in the first 3 hours (8 kites) to the kites made in the remaining 12 hours (18 kites), we get a total of 8 kites + 18 kites = 26 kites. In total, during his 15 hours of kite-making, Kotaro was able to make 26 kites.

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Answer:

(f+g)(2)=5

Step-by-step explanation:

Subsitute 2 in for x in both functions. Then add the answers of the functions together.

To discover the coordinates of a polar point, you need to recognize its distance from the origin (the polar axis) and the perspective it makes with the superb x-axis.

The space is commonly denoted via the image r, and the angle is denoted by means of the image θ. To devise a polar point, you start by locating the foundation and drawing a line alongside the polar axis.

Subsequently, you measure the angle θ from the fine x-axis, shifting counterclockwise.

In the end, your degree the distance r from the starting place and plot the factor on the corresponding location.

To find the coordinates of a polar point, you can use the subsequent formulas:

x = r cos(θ)

y = r sin(θ)

Right here, x and y constitute the rectangular coordinates of the factor, while r and θ constitute the polar coordinates.

Those formulas let you convert between polar and rectangular coordinates, which can be useful for graphing and solving problems in diverse branches of mathematics and physics.

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Answer:

89,680,000

Step-by-step explanation:

236,000×20=4,720,000×19=89,680,000

Answer:36518640

Step-by-step explanation:

Answer:

it's A: Tuesday

Step-by-step explanation:

wensday - friday show a gradual increase in tempature. While monday and tuesday show a sharp increase.

Answer:

the first one is. hope helps

After considering all his earnings and savings, we found that Chris started with $120 in his savings.

Let's assume that Chris saved x dollars. According to the equation, he spent half of his savings, so he spent 0.5 * x dollars on video games. After earning an additional $20 cutting grass, his total savings became 0.5 * x + 20 = 60. To solve for x, we can subtract 20 from both sides of the equation, which gives us 0.5 * x = 40.

Then, we can divide both sides of the equation by 0.5 to obtain x = 80. This means that Chris started with $80 in savings, which he then doubled by spending half of his savings and adding $20 earned from cutting grass, resulting in $120 in total savings.

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Type I error refers to rejecting a true null hypothesis, while Type II error refers to failing to reject a false null hypothesis. Types of statistical analyses include descriptive statistics, inferential statistics, correlation analysis, regression analysis, etc.

Type I error is a false positive, and Type II error is a false negative. Examples of Type I errors include convicting an innocent person in a criminal trial and rejecting a new drug that is actually effective. Examples of Type II errors include failing to convict a guilty person in a criminal trial and accepting a new drug that is actually ineffective.

Various statistical analyses can be applied to the data collected in research studies, depending on the research question and the type of data. Some common types of statistical analyses include descriptive statistics, inferential statistics, correlation analysis, regression analysis, t-tests, analysis of variance (ANOVA), and chi-square tests. Descriptive statistics are used to summarize and describe the characteristics of the data, while inferential statistics are used to draw conclusions and make inferences about the population based on sample data. Correlation analysis examines the relationship between two or more variables, regression analysis explores the relationship between a dependent variable and one or more independent variables, t-tests compare means between two groups, ANOVA analyzes differences among three or more groups, and chi-square tests examine the association between categorical variables.

Type I error, also known as a false positive, occurs when we reject a null hypothesis that is actually true. This means we conclude that there is a significant effect or relationship when there is none in reality. For example, in a criminal trial, a Type I error would be convicting an innocent person. Another example is rejecting a new drug that is actually effective, leading to the rejection of a potentially beneficial treatment.

On the other hand, a Type II error, also known as a false negative, occurs when we fail to reject a null hypothesis that is actually false. In this case, we fail to detect a significant effect or relationship when one exists. For instance, in a criminal trial, a Type II error would be failing to convict a guilty person. In the context of medical testing, a Type II error would occur if we accept a new drug as ineffective when it is actually effective, resulting in the approval of an ineffective treatment.

Various statistical analyses can be applied to research study data depending on the research question and the type of data collected. Descriptive statistics are used to summarize and describe the characteristics of the data, such as measures of central tendency (e.g., mean, median) and variability (e.g., standard deviation, range). Inferential statistics are used to make inferences and draw conclusions about the population based on sample data, such as hypothesis testing and confidence interval estimation.

Correlation analysis examines the relationship between two or more variables and determines the strength and direction of their association. Regression analysis explores the relationship between a dependent variable and one or more independent variables, allowing us to predict the value of the dependent variable based on the independent variables.

T-tests are used to compare means between two groups, such as comparing the average test scores of students who received a specific intervention versus those who did not. Analysis of variance (ANOVA) analyzes differences among three or more groups, such as comparing the performance of students across different grade levels.

Chi-square tests examine the association between categorical variables, such as analyzing whether there is a relationship between gender and voting preference. These are just a few examples of the statistical analyses commonly applied to research study data, and the specific choice of analysis depends on the research question and the nature of the data.

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Answer:

y= 2/3 x + 4

y- intercept= (0,4)

and slope of the line is 2/3

Answer:

B.

Step-by-step explanation:

y = mx + b

The y-intercept is the point (0, 4), so you get b = 4

You now have

y = mx + 4

Now start at the y-intercept, (0, 4). Go up 2 units and right 3 units to a point on the line; rise = 2; run = 2.

slope = m = rise/run = 2/3

Now you have

y = 2/3 x + 4

Answer: B.

Oh please first if the rectangle was compete, it's area would be 8.

The area of the missing triangle is \(\frac{2*2}{2}\)=2.

8-2=6

And there you go! Your answer is 6.

To factor quadratics with leading coefficients other than 1, you can follow these steps:

Check your factoring by expanding the factored form to see if it simplifies back to the original quadratic equation.

Remember that factoring quadratics with leading coefficients other than 1 may involve more complex algebraic techniques, and in some cases, the quadratic equation may not factor easily. In such cases, you can resort to using the quadratic formula to find the roots of the equation.

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Answer:

yes, you can get all right answers.

Answer:

yes i believe that you can get all the answers right

Step-by-step explanation:

Answer:

Step-by-step explanation:

Let's say for the sake of argument that this pizza is cut into 18 slices. That means, according to the problem, that each slice has 1/6 oz of cheese on it.

\(\frac{1}{6}*18=3\) ounces of cheese for the whole pizza.

The probability that the sample mean will be greater than 57.95 is 0.0495.

Probability means possibility. It is a branch of mathematics that deals with the occurrence of a random event. The value is expressed from zero to one. This is the basic probability theory, which is also used in the probability distribution.

To solve this question, we need to know the concepts of the normal probability distribution and of the central limit theorem.

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean \(\mu\) and standard deviation \(\sigma\), the z-score of a measure X is given by:

\(Z=\dfrac{X-\mu}{\sigma}\)

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

The Central Limit Theorem establishes that, for a random variable X, with mean \(\mu\) and standard deviation \(\sigma\), a large sample size can be approximated to a normal distribution with mean \(\mu\) and standard deviation \(\frac{\sigma}{\sqrt{\text{n}} }\).

In this problem, we have that:

The probability that the sample mean will be greater than 57.95

This is 1 subtracted by the p-value of Z when X = 57.95. So

\(Z=\dfrac{X-\mu}{\sigma}\)

By the Central Limit Theorem

\(Z=\dfrac{X-\mu}{\text{s}}\)

\(Z=\dfrac{57.95-53}{3}\)

\(Z=1.65\)

\(Z=1.65\) has a p-value of 0.9505.

Therefore, the probability that the sample mean will be greater than 57.95 is 1-0.9505 = 0.0495

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