Need help on 7-8, thank you in advance! :)

Answer:

350 Pages or 70 pages a day

Step-by-step explanation:

If the book is 400 pages long and she already read 50 pages she only needs to read 350 pages.

Answer:

True

Step-by-step explanation:

When displaying any sort of data, it is important to make the table or chart as easy to understand and read as possible without compromising the data. In this case, it is simpler to understand the pie chart if we use as few slices as possible that still makes sense for displaying the data set.

In a study of happiness 100 people rate the level of happiness on 1 to 10 scale; the kind of variable is this "quantitative".

The numbers you enter when collecting quantitative data represent real quantities which can be added, subtracted, divided, and so on. There are two kinds for quantitative variables: discrete variables and continuous variables.

Some characteristics of variables are-

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Answer:

She needs to get 88

Step-by-step explanation:

make an equation to find the unknown answer:

\(\frac{81+86+x}{3}= 85\)

to find x

81+86+x=85·3

x=85·3-86-81

x=255-86-81

x=88

Answer:

The functions f(x) = 12x and g(x) = √(x - 12) do not have any key features in common.

The function f(x) is a linear function, which means that it is a straight line on a graph. The slope of this line is 12, and the y-intercept (the point at which the line crosses the y-axis) is 0.

The function g(x) is a square root function, which means that it is a curve on a graph that represents the positive square root of a value. The y-values of this function will always be non-negative, since the square root of a non-negative number is always non-negative. The graph of this function will have a horizontal asymptote at y = 0, meaning that it will get closer and closer to the x-axis but will never actually touch it.

These two functions do not have any key features in common, since one is a straight line and the other is a curve.

Using Euler's Method with a step size of h = 0.1, the approximate values of the solution at t = 0.1, 0.2, 0.3, 0.4, and 0.5 are:

t = 0.1: y ≈ 1.1

t = 0.2: y ≈ 1.22

t = 0.3: y ≈ 1.34

t = 0.4: y ≈ 1.47

t = 0.5: y ≈ 1.61

To use Euler's Method, we start with an initial condition. In this case, the given initial condition is y(0) = 1. We can then iteratively calculate the approximate values of the solution at each desired time point using the formula:

Yn = Yn-1 + h * F(Xn-1, Yn-1)

Here, h represents the step size (0.1 in this case), Xn-1 is the previous time point (t = Xn-1), Yn-1 is the solution value at the previous time point, and F(Xn-1, Yn-1) represents the derivative of the solution function.

For the given differential equation +2y = 2 - ey, we can rearrange it to the form y' = (2 - ey) / 2. The derivative function F(Xn-1, Yn-1) is then (2 - eYn-1) / 2.

Using the initial condition y(0) = 1, we can proceed with the calculations:

t = 0.1:

Y1 = Y0 + h * F(X0, Y0)

= 1 + 0.1 * [(2 - e^1) / 2]

≈ 1 + 0.1 * (2 - 0.368) / 2

≈ 1 + 0.1 * 1.316 / 2

≈ 1 + 0.1316

≈ 1.1

Similarly, we can calculate the approximate values of the solution at t = 0.2, 0.3, 0.4, and 0.5 using the same formula and previous results.

Using Euler's Method with a step size of h = 0.1, we found the approximate values of the solution at t = 0.1, 0.2, 0.3, 0.4, and 0.5 to be 1.1, 1.22, 1.34, 1.47, and 1.61, respectively.

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Answer:

No less than 42 lessons

Step-by-step explanation:

To find the total numbers of hours needed to teach, divide the total amount of money needed by the amount of money made an hour.

$894.60/$21.30 = 42

The probability that a household selected at random does not have an individual under the age of 18 in Nassau County in 2000 is 0.999614.

The round-off to the nearest thousands would be 1.000.

To calculate the probability that the selected household did not have an individual under the age of 18, we must determine the number of households without individuals under 18 and divide it by the total number of households in Nassau County in 2000.

We already know that,

The total households = 447,000

The number of households with individuals under 18 = 173

Now,

Number of households without individuals under 18 =

Total households - Households with individuals under 18

Number of households without individuals under 18 = 447,000-173

= 446,827

Probability = Number of households without individuals under 18/Total number of households

Probability = 446,827/447,000

= 0.999614

∴ The probability that the selected household does not have an individual under the age of 18 is 0.999614.

The round-off to the nearest thousand would be 1.000.

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This whole question: There were a total of 447000 households in Nassau County in 200. If one of these households was selected at random, what is the probability that the selected household did not have an individual under age 18? (Express your answer as a decimal rounded to the nearest thousandth)

43 × 7 = 301

12 × 9 = 108

10 × 6 = 50

9 × 7 = 63

7 × 5 =35

6 × 3 = 18

0 × 8 = 0

30 × 3 =9

11 × 8 =88

73 × 2 =146

83 × 5 = 166

16 × 8 = 128

392 × 7 =2,744

29 × 4 = 116

761 × 9 = 6,849

4,829 × 6 = 28974

12 × 7 = 84

25,500 × 4 =102,000

Answer:

77 this answer is rounded to the nearest tenth

Step-by-step explanation:

The formula for the are of a circle is A=πr² so thats π7² which is equaled to about 153.9 since this is a semicircle you'd divide that by two giving you 76.96902.

There is sufficient evidence to believe that the number of household pets leaving the shelter over the weekend is different from the proportion of wildlife animals leaving the shelter over the weekend.

To determine if there's sufficient evidence,

Let us define the null and alternative hypotheses for this test as follows:

Null hypothesis (H0): The proportion of household pets leaving the shelter over the weekend is the same as the proportion of wildlife animals leaving the shelter over the weekend.

Alternative hypothesis (Ha): The proportion of household pets leaving the shelter over the weekend is different from the proportion of wildlife animals leaving the shelter over the weekend.

The test statistic for two sample test is given by:

z = (p1 - p2) / sqrt(p * (1 - p) * (1/n1 + 1/n2))

where

p1 and p2 are the proportions of household pets and wildlife animals leaving the shelter over the weekend, respectively,

p is the pooled proportion,

n1 and n2 are the sample sizes for household pets and wildlife animals, respectively.

Pooled proportion is

p = (x1 + x2) / (n1 + n2)

where x1 and x2 are the number of household pets and wildlife animals leaving the shelter over the weekend, respectively.

Given

-n1 = 376, n2 = 52, x1 = 29, x2 = 10

p = (29 + 10) / (376 + 52) = 0.091

The observed proportions are:

p1 = x1 / n1 = 29 / 376 = 0.0771

p2 = x2 / n2 = 10 / 52 = 0.1923

The test statistic value

z = (0.0771 - 0.1923) / sqrt(0.091 * (1 - 0.091) * (1/376 + 1/52)) = -3.04

By using a standard normal distribution table,

The p-value is 0.00238.

Since the p-value (0.00238) is less than the level of significance (0.01), we reject the null hypothesis and conclude that there is sufficient evidence to indicate a difference in the number of animals leaving the shelter over the weekend for household pets and wildlife animals.

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Answer:

The are consecutive interior angles.

The researcher should reject the null hypothesis because the calculated z statistic is beyond the critical region.

To determine the critical region and evaluate the hypothesis, let's consider the information provided:

The z-score boundaries at an alpha level alpha = .05 are: z = 1.96 and z = -1.96.

The critical region is the area beyond these boundaries in both tails of the distribution.

The z-score boundaries for an alpha level a = .001 are: z = 2.58 and z = -2.58.

Given that the calculated z statistic for the hypothesis test is 2.64, which is greater than the z-score boundary of 2.58, it falls within the critical region.

Therefore, the researcher should reject the null hypothesis because the calculated z statistic is beyond the critical region. Additionally, the researcher can conclude that the alternative hypothesis is probably correct, as the data suggests evidence against the null hypothesis.

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The alpha level is set _____ the analysis of the data. Use the following Distributions tool to identify the boundaries that separate the extreme samples from the samples that are more obviously consistent with the null hypothesis. Assume the null hypothesis is nondirectional, meaning that the critical region is split across both tails of the distribution. The z-score boundaries at an alpha level alpha = .05 are: z = 1.96 and z = -1.96 z = 3.29 and z = -3.29 z = 2.58 and z = -2.58 To use the tool to identify the z-score boundaries, click on the icon with two orange lines, and slide the orange lines until the area in the critical region equals the alpha level. Remember that the probability will need to be split between the two tails. To use the tool to help you evaluate the hypothesis, click on the icon with the purple line, place the two orange lines on the critical values, and then place the purple line on the z statistic. The critical region is _____. The z-score boundaries for an alpha level a = .001 are: z = 2.58 and z = -2.58 z = 1.96 and z = -1.96 z = 3.29 and z = -3. 29 Suppose that the calculated z statistic for a particular hypothesis test is 2.64 and the alpha is .001. This z statistic is _____ the critical region. Therefore, the researcher _____ reject the null hypothesis, and he ______ conclude the alternative hypothesis is probably correct.

the centroid of the region bounded by the given curves is (x, y) = (15, 225).

To show that f is continuous on (−∞,∞), we need to show that the limit of f(x) as x approaches any point from the left and from the right is equal.

First, let's consider the limit of f(x) as x approaches 1 from the left.

As x approaches 1 from the left, f(x) = 1-x^2, so the limit of f(x) as x approaches 1 from the left is 1.

Now, let's consider the limit of f(x) as x approaches 1 from the right.

As x approaches 1 from the right, f(x) = ln x, so the limit of f(x) as x approaches 1 from the right is 0.

Since the limit of f(x) as x approaches 1 from the left is 1 and the limit of f(x) as x approaches 1 from the right is 0, we can conclude that f is continuous on (−∞,∞).

To find the centroid of the region bounded by the given curves, we need to calculate the area of the region and the area-weighted centroid of the region.

The area of the region is given by the integral of x3 from 0 to 10, which is equal to 1125/4.

The area-weighted centroid of the region is given by the integral of (x3*x)/(1125/4) from 0 to 10, which is equal to 15.

Therefore, the centroid of the region bounded by the given curves is (x, y) = (15, 225).

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Answer:

0.125

7.50/60=1.25

since there 60 minutes in one hour you would divide the hourly rate by 60.

Answer:

-1/8

Step-by-step explanation:

When slopes are perpendicular that means it's completely opposite.

The opposite of 8 is 1/8

But 8 is positive that means we have to make the pereldicular slope negative

Therefore your answer is -1/8

Hope this helps p,z mark brainliest!

Answer:

-1/8

Step-by-step explanation:

Answer:

no they are not

Step-by-step explanation:

21,13,27,45 are prime numbers

Answer:

13, 43, 23, 39

Step-by-step explanation:

Their only factors are themselves and 1

Answer:

x = 4

Step-by-step explanation:
1.Distribute

2. Subtract 2 from both sides
3. Simplify
4. Divide both sides by same factor

5. Simplify
x = 4

Answer: 4

Step-by-step explanation:

We have to try getting x by itself to solve for it. Since we have two sides that are equal to each other, we can add, subtract, multiply, and divide anything on both sides to try to isolate x.

\(2(x+1)=10\)

We can first divide the left side and the right side by 2. This would remove the 2 being multiplied on the outside.

\(\frac{2(x+1)}{2}=\frac{10}{2}\\x+1=10\div 2\\x+1=5\)

Now, we have a + 1 on the left side that we need to remove to get x by itself. If we are adding something, we can remove that by subtracting the same thing. Hence, we can subtract 1 from both sides to remove the + 1.

\(x+1=5\\x+1-1=5-1\\x+0=4\\x=4\)

After all that simplifying, we get that x equals 4.

Step-by-step explanation:

If it is going to decrease, then it is a subtraction problem.

8-12

The answer will be negative.

An easy way to solve this is to subtract 12-8 and slap a '-' sign in front.

-4

hope it helps!

Answer:

Lower Quartile = 13 min; Upper Quartile = 27 min

Step-by-step explanation:

Since we have the median, we now separate the data equally to the left and right of the median.

Thus, on the left (lower) portion we have 10, 11, 13, 18, and 19.  We see 13 is the middle term of these 5 values so 13 is the lower quartile (Q1).

Similarly, one the right (upper) portion, we have 22, 25, 27, 30, and 32.  We see 27 is the middle term of these 5 values so 27 is the upper quartile (Q3)

The perimeter of the square patio is the sum of its side lengths

The length of the patio is: 8x + 2

The given parameters are:

\(\mathbf{Shape = Square}\)

\(\mathbf{Perimeter = 32x + 8}\)

The perimeter of a square is:

\(\mathbf{Perimeter = 4 \times Length}\)

So, we have:

\(\mathbf{4 \times Length = 32x + 8}\)

Divide both sides by 4

\(\mathbf{Length = 8x + 2}\)

Hence, the length of the patio is: 8x + 2

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a. y^ Estimated y-intercept: This refers to the value of y when x is equal to zero. In this case, the estimated y-intercept is 188.

b. -126 Estimated slope: This refers to the coefficient of x in the regression equation, which indicates the change in y for each unit increase in x. In this case, the estimated slope is -126.

c. xβ1: This refers to the independent variable (x) multiplied by its coefficient (β1), which is the estimated slope.

d. y^ Estimated value of the dependent variable: This refers to the predicted value of y based on the regression equation and a given value of x.

e. β0: This refers to the coefficient of the intercept term in the regression equation, which represents the value of y when x is equal to zero. In this case, the estimated value of β0 is 188, which is the estimated y-intercept.

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The cross-correlation function satisfies Ray(T) = R(-7). (b) The cross-power spectral density may or may not be guaranteed to be real-valued, depending on the properties of the jointly WSS random processes. (c) The condition on h(t) for the cross-power spectral density of r(t) and y(t) to be real-valued is that the impulse response h(t) must be a real-valued function.

(a) The cross-correlation function between two jointly wide-sense stationary (WSS) random processes, x(t) and y(t), is denoted as Ray(T), where T represents the time lag. In this case, it is stated that Ray(T) is equal to R(-7), indicating that the cross-correlation function is symmetric around a time lag of -7.

(b) The cross-power spectral density (CPSD) is the Fourier transform of the cross-correlation function. Whether the CPSD is guaranteed to be real-valued depends on the properties of the jointly WSS random processes x(t) and y(t). In general, if the processes are real-valued, the CPSD will also be real-valued. However, if the processes have complex-valued components, the CPSD may have imaginary parts.

(c) Consider a WSS process r(t) at the input of a linear time-invariant (LTI) filter with impulse response h(t), and let the output be denoted as y(t). The condition for the cross-power spectral density of r(t) and y(t) to be real-valued is that the impulse response h(t) must be a real-valued function. This condition ensures that the LTI system preserves the symmetry properties of the input processes, leading to a real-valued cross-power spectral density.

In summary, the cross-correlation function between jointly WSS random processes satisfies the symmetry property Ray(T) = R(-7). The cross-power spectral density may or may not be real-valued, depending on the nature of the input processes. To ensure a real-valued cross-power spectral density between a WSS input process and the output of an LTI filter, the impulse response of the filter must be real-valued.

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Check the picture below, so the parabola looks more or less like so, with the vertex half-way from the focus point and the directrix.

Now, the distance from the directrix to the focus point is only 1 unit, so half that, or namely the "p" distance is 1/2 unit, and since the parabola is opening downwards, "p" is negative, so

\(\textit{vertical parabola vertex form with focus point distance} \\\\ 4p(y- k)=(x- h)^2 \qquad \begin{cases} \stackrel{vertex}{(h,k)}\qquad \stackrel{focus~point}{(h,k+p)}\qquad \stackrel{directrix}{y=k-p}\\\\ p=\textit{distance from vertex to }\\ \qquad \textit{ focus or directrix}\\\\ \stackrel{"p"~is~negative}{op ens~\cap}\qquad \stackrel{"p"~is~positive}{op ens~\cup} \end{cases} \\\\[-0.35em] ~\dotfill\)

\(\begin{cases} h=0\\ k=-\frac{1}{2}\\[1em] p=-\frac{1}{2} \end{cases}\implies 4\left( -\frac{1}{2} \right)\left( ~~y-\left( -\frac{1}{2} \right) ~~ \right)~~ = ~~(x-0)^2 \\\\\\ -2\left( y+\frac{1}{2} \right)=x^2\implies y+\cfrac{1}{2} =\cfrac{x^2}{-2}\implies y = -\cfrac{1}{2}x^2-\cfrac{1}{2}\)

now, we could also write that as either

\(y = -\cfrac{1}{2}(x^2+1)\qquad or\qquad y = \cfrac{1}{2}(-x^2-1)\)

a. The hypothesis test is right-tailed.

b. The P-value is 0.2525.

c. Using a significance level of a = 0.01, we fail to reject the null hypothesis .

a) The hypothesis test is right-tailed because the alternative hypothesis is p > 0.4.

b) To find the P-value, we need to use a standard normal distribution table or a calculator. Since the test statistic is positive, we look for the area to the right of z = 0.67. Using a standard normal distribution table or a calculator, we find that the area to the right of z = 0.67 is 0.2525. This is the P-value.

c) Using a significance level of a = 0.01, we compare the P-value to the significance level. The P-value is greater than the significance level, so we fail to reject the null hypothesis . There is not enough evidence to support the claim that p > 0.4 at the 1% significance level.

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The given question is incomplete, the complete question is :

The test statistic of z = 0.67 is obtained when testing the claim that p>0.4. a. Identify the hypothesis test as being two-tailed, left-tailed, or right-tailed. b. Find the P-value. c. Using a significance level of a = 0.01, should we reject null hypothesis or should we fail to reject null hypothesis?

Answer:

well i belive so that yes it is equivalent

Step-by-step explanation:

well if u am wrong try uskng a number line or you can divide to see if i am right.

The value of 0.0062 is less that our significance level of 0.1, we reject the null hypothesis at the 0.1 level of significance and conclude with sufficient evidence that the manufacturer's MPG rating is incorrect.

To answer the question, we will conduct a hypothesis test to at the 0.1 level to ascertain whether or not the manufacturer's MPG rating is incorrect.

We start by stating the null and alternative hypotheses:

\($H_0$\): The mean miles/gallon for the vans is 53.8

\($H_A$\): The mean miles/gallon for the vans is not 53.8

We choose a significance level $\alpha = 0.1$ and calculate the following test statistic:

\($z = \frac{\bar{x}-\mu}{\sigma/\sqrt{n}} = \frac{53.4-53.8}{1/\sqrt{16}} = -2.5$\)

With a standard normal table, we look for the area to the left of -2.5, which is 0.0062. Because this value of 0.0062 is less that our significance level of 0.1, we reject the null hypothesis at the 0.1 level of significance and conclude with sufficient evidence that the manufacturer's MPG rating is incorrect.

Therefore, the value of 0.0062 is less that our significance level of 0.1, we reject the null hypothesis at the 0.1 level of significance and conclude with sufficient evidence that the manufacturer's MPG rating is incorrect.

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