a waste management company is designing a rectangular construction dumpster that will be twice as long as it is wide and must hold of debris. find the dimensions of the dumpster that will minimize its surface area.

The p-value associated with the null hypothesis = 0.05

Fail to reject the null hypothesis. The​ P-value is greater than the level of significance.

Candice should reject the null hypothesis as the 50% confidence interval does not contain 10 hours

Small p-values offer proof that the null hypothesis is false. The stronger the evidence is against the null hypothesis, the smaller (closer to 0) the p-value. The null hypothesis is rejected if the p-value is less than or equal to the chosen significance level; otherwise, it is not.

You have the Hypothesis that "students study less than 10 hours, on average, per week"

Symbolically:

H₀:μ≥10hours

H₁:μ<10hours

The significant level for this case study is 50% - 0.05. If the results gotten is less than the significance level, we reject the null hypothesis, but if greater, we fail to reject the null hypothesis.

The p-value of 0.05 is one of the most often used numbers. When the calculated p-values are less than 0.05, the faulty hypothesis is considered to be fraudulent or invalid (subsequently the name invalid theory). Additionally, the faulty theory is taken into consideration to be clear if the value is greater than 0.05.

The edge for that likelihood in our model is 0.05, and it represents the probability that our results will be similar to the invalid speculation. Therefore, if the calculated p-value is less than 0.05, it actually means that there is a very little likelihood that we would have the same results as the flawed hypothesis. Additionally, if the p-value is greater than 0.05, there is a very strong probability that the results will be similar to the flawed speculation, leading us to conclude that it is legitimate.

Therefore,

Fail to reject the null hypothesis. The​ P-value is greater than the level of significance.

The p-value associated with the null hypothesis = 0.05

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The calculated area of the middle shape is 18 square units

From the question, we have the following parameters that can be used in our computation:

The figures

From the figure, we have the middle shape to be a rectangle

The width of the rectangle is

Width = 6

The length of the rectangle is calculated as follows

15 = 3 * 5

27 = 3 * 3 * 3

The common factor is 3

So, we have

Length = 3

The area of the rectangle is calculated as

Area = Length * Width

So, we have

Area = 3 * 6

Evaluate

Area = 18

Hence, the area of the middle shape is 18 square units

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Answer:

P = 8n+2

P = 34 inches

Step-by-step explanation:

P = 2(l+w)

  = 2( 3n+2 + n-1)

   = 2( 4n+1)

    = 8n+2

Let n = 4

P = 8(4)+2

   =32+2

   = 34

The domain of the points (3, 2) and (-5, 2) are all real numbers.

The Range of the points (3, 2) and (-5, 2) is only the value of y = 2.

What is the domain and range of the function?

The domain of a function is the set of all input values (independent variable) for which the function is defined and produces a valid output (dependent variable). The range of a function is the set of all possible output values (dependent variable) that the function can produce for all valid input values (independent variable).

The domain and range of a set of points in a coordinate plane refer to the set of all possible x-values and y-values, respectively.

The domain of the points (3, 2) and (-5, 2) are all real numbers. So, the domain can be represented as (-inf, inf)

The range of the points (3, 2) and (-5, 2) is only the value of y = 2. So, the range can be represented as {2}

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Answer:

x=5 .........................................

a. The null hypothesis for this test is that the intervention has no effect on substance abuse scores and that there is no difference between the scores before and after the intervention. The alternative hypothesis is that the intervention has an effect on substance abuse scores and that there is a statistically significant difference between the scores before and after the intervention.

b. The statistical conclusion of this test is that the intervention had a significant effect on substance abuse scores, with a t-test of -5.918 and a p-value of <0.001. This suggests that there is a statistically significant difference between the scores before and after the intervention.

a. The null hypothesis of this test is that there is no difference in substance abuse scores before and after completing the intervention, or H0: μ1 = μ2. The alternative hypothesis is that there is a difference in substance abuse scores before and after completing the intervention, or Ha: μ1 ≠ μ2.

b. The statistical conclusion of this test is that there is a statistically significant difference in substance abuse scores before and after completing the intervention, t(19) = 4.38, p < 0.001. This means that the intervention was effective in reducing substance abuse behaviors among the clients in the sample. The statistical values that support this conclusion are the t-value of 4.38 and the p-value of less than 0.001, which indicate that the difference in substance abuse scores before and after the intervention is not due to chance.

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The correct answer is "line of best fit." A regression line is also called the line of best fit as it represents the best approximation of the relationship between the independent and dependent variables in a scatterplot.

In statistics and data analysis, a regression line is a straight line that represents the best-fitting relationship between two variables. It is often referred to as the "line of best fit" because it minimizes the overall distance between the line and the actual data points.

When plotting data points on a scatterplot, the regression line is used to approximate the trend or pattern in the data. It helps in understanding the relationship between the independent variable (usually denoted as "x") and the dependent variable (usually denoted as "y"). The goal is to find a line that is as close as possible to all the data points, capturing the general trend or direction of the relationship.

The line of best fit is determined by using a statistical technique called regression analysis. This technique calculates the optimal values for the slope and intercept of the line based on the data. The most common method for fitting a regression line is known as ordinary least squares (OLS), which minimizes the sum of the squared differences between the observed data points and the predicted values on the line.

By fitting a regression line, we can make predictions or estimations about the dependent variable based on the values of the independent variable. The line of best fit provides a visual representation of the relationship between the variables and allows for easier interpretation and analysis of the data.

It's important to note that the line of best fit is an estimation based on the given data, and it may not perfectly pass through every data point. However, it provides a useful summary of the overall trend and can be used for making predictions or drawing conclusions about the relationship between the variables.

Therefore, the correct answer is "line of best fit." A regression line is also called the line of best fit as it represents the best approximation of the relationship between the independent and dependent variables in a scatterplot.

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Answer:

1. divide 1.50 by 3 to get the unit cost of a yard

of ribbon. the ansvwer is .75.

2. you must multiply .75 by 5 to get 3.75 to find the cost of 5 ribbons

Step-by-step explanation:

final answer $30

Answer:

Step-by-step explanation:

By dilation, the image of the vertex M of the quadrilateral is M'(x, y) = (6, 5).

In this problem we find the representation of a quadrilateral whose image by dilation must be found. The dilation formula is introduced below:

P'(x, y) = O(x, y) + k · [P(x, y) - O(x, y)]

Where:

If we know that O(x, y) = (4, 6), k = 1 / 3 and M(x, y) = (10, 9), then image of point M is:

M'(x, y) = (4, 6) + (1 / 3) · [(10, 9) - (4, 6)]

M'(x, y) = (4, 6) + (1 / 3) · (6, 3)

M'(x, y) = (4, 6) + (2, 1)

M'(x, y) = (6, 5)

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Answer:

2,000,000,000.

Step-by-step explanation:

We know that when rounding, we take a look at the digit next to the digit we are rounding. So if I were to ask for you to round 122 to the nearest hundred, then the answer would be 100.

Remember that we round down if the digit next to it is 0-4. If the digit is 5-9, then we round up.

In this case, the digit next to the 2 is a 4. We know that we round down with a 4, so we go to the nearest whole billion, in this case 2 billion.

I hope this helps!

The median is 16.5.

1. Mean: Mean is defined as the average of the given data set. The formula for calculating the mean is:

Mean = (sum of all data values) / (number of data values)

Given data values are 10, 20, 12, 17, and 16.

Number of data values is 5

Therefore, Mean = (10 + 20 + 12 + 17 + 16) / 5= 75 / 5= 15

Hence, the mean is 15.

Median: The median is defined as the middle value of the given data set when the data values are arranged in ascending or descending order.

Given data values are 10, 20, 12, 17, and 16.

To find the median, we first arrange the data in ascending order: 10, 12, 16, 17, 20

As the number of data values is odd, the middle value is the median.

Therefore, Median = 16

Hence, the median is 16.2. Mean: Mean is defined as the average of the given data set.

The formula for calculating the mean is:

Mean = (sum of all data values) / (number of data values)Given data values are 10, 20, 21, 17, 16, and 12.

The number of data values is 6

Therefore, Mean = (10 + 20 + 21 + 17 + 16 + 12) / 6= 96 / 6= 16

Hence, the mean is 16.

Median: The median is defined as the middle value of the given data set when the data values are arranged in ascending or descending order.

Given data values are 10, 20, 21, 17, 16, and 12.

To find the median, we first arrange the data in ascending order:10, 12, 16, 17, 20, 21

As the number of data values is even, and the median is the mean of the middle two values.

Therefore, Median = (16 + 17) / 2= 16.5. Hence, the median is 16.5.

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Johnny can improve his meal in 6 different ways by choosing two condiments from his four options. Some examples of the different combinations include ketchup and salt, ketchup and pepper, salt and pepper, and so on.

To determine the number of different ways Johnny can improve his meal using condiments, we can use the concept of combinations.

Since Johnny can only make two additions to his meal, we need to find the number of combinations of condiments he can choose from his four options: ketchup, salt, pepper, and shredded cheese.

To calculate the number of combinations, we can use the formula for combinations:
nCr = n! / (r! * (n - r)!)

Where n represents the total number of items and r represents the number of items to be chosen.

In this case, n is 4 (since Johnny has four condiment options) and r is 2 (since Johnny can only make two additions).

Plugging these values into the formula, we get:

4C2 = 4! / (2! * (4 - 2)!)

Simplifying this expression:

4C2 = 4! / (2! * 2!)

The exclamation mark (!) represents the factorial operation, which means multiplying a number by all positive integers less than itself down to 1.

Calculating the factorials:
4! = 4 * 3 * 2 * 1 = 24
2! = 2 * 1 = 2

Substituting these values back into the equation:
4C2 = 24 / (2 * 2)

Simplifying further:
4C2 = 24 / 4

Finally, dividing:
4C2 = 6

Therefore, Johnny can improve his meal in 6 different ways by choosing two condiments from his four options. Some examples of the different combinations include ketchup and salt, ketchup and pepper, salt and pepper, and so on.

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Answer:

The answer is Logarithm

Answer: 70ᴼ

Step-by-step explanation:

The triangles are vertical so their angle measures are congruent.

The angles of a triangle add to equal 180ᴼ.

55 + 55 = 110

180 - 110 = 70

The length of DE is 3 units, and the measure of ∠ZEDF is 53°.

Let's analyze the given information and use the properties of similar triangles to find the length of DE and the measure of ∠ZEDF.

First, since triangles AABC and ADEF are similar, we know that their corresponding sides are proportional.

Using the given lengths, we have:

AB/DE = AC/EF = BC/DF

Substituting the known values:

5/DE = 5/3 = 6/DF

Cross-multiplying, we get:

5 \(\times\) 3 = 5 \(\times\) DE

15 = 5 \(\times\) DE

Dividing both sides by 5, we find:

DE = 15/5 = 3 units

Therefore, the length of DE is 3 units.

Now, let's find the measure of ∠ZEDF.

Since ∠ABC and ∠DEF are corresponding angles in similar triangles, they have the same measure.

Given that m/ABC is 53°, we can conclude that m/DEF is also 53°.

Hence, the measure of ∠ZEDF is 53°.

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Answer:

B /second bubble -3 1/3 is 10/3 and 4/9 is a reciprocal 9/4

The lower limit for the 95% confidence interval for the true graduation rate is 0.704.

The percentage (frequency) of acceptable confidence intervals that include the actual value of the unknown parameter is represented by the confidence level.

We can use the formula for the confidence interval for a proportion:

lower limit = sample proportion - z * √((sample proportion * (1 - sample proportion)) / sample size)

where z is the z-score corresponding to the desired level of confidence (95% in this case), and sample size is 500.

The sample proportion is 371/500 = 0.742.

The z-score for a 95% confidence level can be found using a standard normal distribution table or calculator, and is approximately 1.96.

Plugging in the values, we get:

lower limit = 0.742 - 1.96 * √((0.742 * 0.258) / 500)

lower limit = 0.704

Rounding to three decimal places, the lower limit for the 95% confidence interval for the true graduation rate is 0.704.

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The survey's reliability and validity depend on the methodology and quality of the sample data.

In the given scenario, a survey aims to investigate whether the proportion of today's high school seniors who own their own cars is higher than it was a decade ago. The survey proposes an alternative hypothesis that suggests a change in the proportion, while the null hypothesis assumes no change. The survey also mentions that the observed result would occur by chance 1.7% of the time if the null hypothesis were true.

To evaluate the reasonability of the survey, we need to consider the concept of statistical significance. Statistical significance is a measure of how likely the observed result would occur due to chance alone, assuming the null hypothesis is true. In hypothesis testing, a common threshold for statistical significance is α (alpha), typically set at 0.05 or 5%.

In this case, the survey suggests that the observed result would occur by chance 1.7% of the time if the null hypothesis were true. This is known as the p-value. The p-value represents the probability of obtaining a result as extreme or more extreme than the observed result, assuming the null hypothesis is true.

If the p-value is less than the chosen significance level (α), we reject the null hypothesis in favor of the alternative hypothesis. In this scenario, since the p-value is 1.7%, which is less than 5%, we can conclude that the observed result is statistically significant.

Therefore, it is reasonable to conduct the survey and investigate whether the proportion of high school seniors who own their own cars has increased compared to a decade ago. The survey provides evidence to support the alternative hypothesis and suggests that the observed result is unlikely to occur by chance alone, assuming the null hypothesis is true.

However, it's important to note that the survey's reasonability is based on the assumption that the survey methodology and sample data are reliable and representative. The survey should ensure that the sample is randomly selected and sufficiently large to provide accurate results. Additionally, the survey should consider potential confounding variables and sources of bias that could affect the findings.

In summary, the survey investigating the proportion of high school seniors who own their own cars and proposing a higher proportion than a decade ago is reasonable based on the evidence provided, which suggests a statistically significant result. However, the survey's reliability and validity depend on the methodology and quality of the sample data.

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well, for the piece-wise function, we know that hmmm x = -1, -1 is less 1, so the subfunction that'd apply to that will be -2x + 1, because on that section "x is less than or equals to 1".

so f(-1) => -2(-1) + 1 => 3.

Answer:3

Step-by-step explanation:

In this case x=-1 so you will use the top equation because x<1

so f(-1) = -2(-1) + 1

          = 2+1

           =3

Answer:

First find the slope of the line = (y2 - y1) / (x2 - x1)   where the 2 points are (x1, y1 and (x2, t2).  

Then  substitute the values of  the slope (m) and one of the points   into the point-slope formula

y - y1 = m(x - x1)

Step-by-step explanation:

Find the slope using the slope formula  

Use the slope and one of the points to solve for the y-intercept (b).

One of your points can replace the x and y, and the slope you just calculated replaces the m of your equation y = mx + b. Then b is the only variable left. Use the tools you know for solving for a variable to solve for b.

Once you know the value for m and the value for b, you can plug these into the slope-intercept form of a line (y = mx + b) to get the equation for the line.

Answer:

BC≈12.2

Step-by-step explanation:

As we know

24/sin(100°)=BC/sin(30°)

BC=sin(30°)×24/sin(100°)

BC=1/2×24/sin(100°)

BC=12/sin(100°)

BC=12.2 (approximately)

Answer:

BC≈12.2

Step-by-step explanation:

Hope this helped have an amazing day!

For the sample of weight of corn chips dispensed in dispensing machine, probability that the sample mean weight of these 100 bags falls between 10.50 and 10.80 ounces is equals to 0.4332.

We have a sample of weight of corn chips dispensed by the dispensing machine.

Dispensed weight of bag by the dispensing machine = 10 ounces

The sample of weight of bags follows the normal distribution with, sample mean, \( \bar x\) = 10.5 ounces

standard deviations = 2 ounces

Randomly selected from this dispensing machine. Sample size, n = 100

We have to determine probability that the sample mean weight of these 100 bags falls between 10.50 and 10.80 ounces,

\(P( 10.50 < \bar x < 10.80),\)

Using Z-score formula for sample mean in normal distribution, \(Z = \frac{ \bar x - \mu}{ \frac{\sigma}{\sqrt{n}} }\)

where μ--> population mean

σ -->standard deviations

n --> Sample size

Now, the required probability is \(P( 10.50 < \bar x < 10.80)\)

= \(P(\frac{ 10.50 - \mu }{\frac{\sigma}{\sqrt{n}}} < \frac{ \bar x - \mu}{ \frac{\sigma}{\sqrt{n}} } < \frac{ 10.80 - \mu }{\frac{\sigma}{\sqrt{n}}} )\)

= \(P(\frac{ 10.50 - 10 }{\frac{2}{\sqrt{100}}} < z< \frac{ 10.80 - 10 }{\frac{2}{\sqrt{100}}} )\)

= \(P(\frac{ 0.50 }{\frac{2}{10} }< z< \frac{ 0.80 }{\frac{2}{10}})\)

= \(P(2.5 < z< 4)\)

= 0.4332

Hence, required value is 0.4332.

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Answer:

y = -x + 2

Step-by-step explanation:

slope = -1 ;  (-1 , 3)

Equation: y - y1 = m (x - x1)

y - 3 = (-1)(x -[-1])

y - 3 = (-1) (x + 1)

y - 3 = -x - 1

    y = -x - 1 + 3

   y = -x + 2

Answer:

y=-x+2

Step-by-step explanation:

Answer:

Step-by-step explanation:I didn't mean to add

Answer:

$27.50 is the amount of money in total she has to pay.

Step-by-step explanation:

$27.50 means the amount of money total she has to pay for admission fee as well as for each nder.

Answer: Let's solve this problem step by step.

First, let's assume the salaries of An and B to be 5x and 3x, respectively, where x is a common multiplier.

According to the given information, they save Rs. 2600 and Rs. 1800, respectively. Since savings come from the remaining portion of their incomes after spending, we can calculate their expenditures as follows:

For An:

Income of An = Salary of An + Savings of An

Income of An = 5x + 2600

For B:

Income of B = Salary of B + Savings of B

Income of B = 3x + 1800

Now, let's consider the proportion of their expenditures. It is given that the proportion of their expenditures is 9:5. So, we can write the following equation:

(Expenditure of An)/(Expenditure of B) = 9/5

Since expenditure is the complement of savings, we have:

[(Income of An - Savings of An)] / [(Income of B - Savings of B)] = 9/5

Substituting the previously derived expressions for income, we get:

[(5x + 2600 - 2600)] / [(3x + 1800 - 1800)] = 9/5

Simplifying the equation, we have:

5x / 3x = 9/5

Cross-multiplying, we get:

5 * 3x = 9 * 3x

15x = 27x

Subtracting 27x from both sides, we have:

0 = 12x

This implies that x = 0, which is not a valid solution. Therefore, there seems to be an error or inconsistency in the given information or equations. Please recheck the problem statement or provide additional information to help resolve the issue.