Find the distance between the points (3, -5) and (6, -5).

Rounding to 3 decimal places, the value of the test statistic (Z) is approximately -1.593.

To compute the test statistic for the runs test, we need to follow these steps:

Step 1: Determine the observed number of runs (R).

  - A run is defined as a sequence of consecutive observations of the same type (e.g., acceptable or defective).

  - In this case, we have 45 products, of which 38 are acceptable and 7 are defective.

  - To determine the observed number of runs, we count the number of switches from one type to another.

The observed number of runs (R) can be calculated as follows:

R = 1 + the number of switches

In our case, we have 38 acceptable products followed by 7 defective products. There is only one switch from acceptable to defective.

R = 1 + 1 = 2

Step 2: Calculate the expected number of runs (E[R]) under the assumption of randomness.

  - The expected number of runs can be calculated using the formula:

    E[R] = (2 * n1 * n2) / (n1 + n2) + 1

  - Where n1 is the number of acceptable products (38) and n2 is the number of defective products (7).

E[R] = (2 * 38 * 7) / (38 + 7) + 1

E[R] = (2 * 266) / 45 + 1

E[R] = 532 / 45 + 1

E[R] ≈ 11.822

Step 3: Calculate the standard deviation (σ(R)) of the number of runs under the assumption of randomness.

  - The standard deviation can be calculated using the formula:

    σ(R) = √[(2 * n1 * n2 * (2 * n1 * n2 - n1 - n2)) / ((n1 + n2)^2 * (n1 + n2 - 1))]

  - Where n1 is the number of acceptable products (38) and n2 is the number of defective products (7).

σ(R) = √[(2 * 38 * 7 * (2 * 38 * 7 - 38 - 7)) / ((38 + 7)^2 * (38 + 7 - 1))]

σ(R) = √[(2 * 38 * 7 * (2 * 266 - 45)) / (45^2 * 44)]

σ(R) = √[(2 * 38 * 7 * (532 - 45)) / (45 * 44)]

σ(R) = √[(2 * 38 * 7 * 487) / (45 * 44)]

σ(R) ≈ 6.172

Step 4: Calculate the test statistic (Z).

  - The test statistic can be calculated using the formula:

    Z = (R - E[R]) / σ(R)

Z = (2 - 11.822) / 6.172

Z ≈ -1.593

Rounding to 3 decimal places, the value of the test statistic (Z) is approximately -1.593.

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The correct answer is a) the probability of precipitation is 72%. and b)  the probability of precipitation is 2%.

The given formula to determine the probability of precipitation (PoP) is PoP = (C * A) * 100 percent where C represents the confidence that precipitation will occur somewhere in the forecasted area and A represents the percentage of the area that will receive measured precipitation if it occurs.

(a) If a forecaster expresses confidence that there is an 80% chance of precipitation in the forecasted area, and it is expected to produce measurable precipitation over 90% of the area, then the probability of precipitation is given as follows: PoP = (C * A) * 100 per cent C = 80%A = 90%PoP = (80% * 90%) * 100%

PoP = 72%.

Therefore, the probability of precipitation is 72%.

(b) If a forecaster expresses confidence that there is a 20% chance of precipitation in the forecasted area, and it is expected to produce measurable precipitation over 10% of the area, then the probability of precipitation is given as follows: PoP = (C * A) * 100 per cent C = 20%A = 10%PoP = (20% * 10%) * 100%PoP = 2%

Therefore, the probability of precipitation is 2%.

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The probability of obtaining five tails in a row assuming the coin is​ fair is 1/32.

A person will have to do 5 coin tosses which means,

No. of total observations  = 25

Required outcome → 5 Heads { T , T , T , T , T }

This outcome  can occur only once so required outcome will be 1

Thus, required outcome  =1

Probability (5 Tails) = 1 / 2⁵ = 1 / 32

Hence , the probability of obtaining five tails in a row assuming the coin is​ fair is 1/32.

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Answer:

Eh what answer? I dun see anything :0 - Lily ^_^

Answer:

Step-by-step explanation:

−36w+60

=12(−3w+5)

12(−3w+5)

The bearing is the angle measured clockwise from the north direction to a specified direction. To find the bearing of Town Y from Town B, we use the given information that Town B is located south 38 degrees east from Town Y. By subtracting this angle from 180 degrees, we find that the bearing is 142 degrees.

To determine the bearing, we need to find the angle between the north direction and the direction from Town B to Town Y.

Since Town B is located south of Town Y, the bearing will be a southern direction. The bearing angle can be calculated as 180 degrees minus the given angle, which is 38 degrees.

Therefore, the bearing of Town Y from Town B is 180 - 38 = 142 degrees.

In conclusion, the main answer is that the bearing of Town Y from Town B is 142 degrees.

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According to research, immune function is increased in adolescents who option C: get more than 9 hours of sleep a night.

Yes, sleep deprivation has an impact on your immune system. According to studies, those who don't get enough or good sleep are more likely to become ill after contracting a virus like the one that causes the common cold.

Therefore, The immune system receives crucial support during sleep. A well-balanced immune defense enabled by robust innate and adaptive immunity, effective response to immunizations, and less severe allergy reactions is made possible by getting enough hours of high-quality sleep.

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The radius of the hemisphere is r = 34.6 cm

Given data ,

The volume of a hemisphere can be calculated using the formula:

V = (2/3) π r³

Now , the volume of the hemisphere is V = 86784 cm³

Let the radius be represented as r

86784 = (2/3) x π x (r)³

On solving for r , we get

r³ = ( 86784 x 3 ) / 2π

r³ = 41,436.3077

Taking roots on both sides , we get

r = 34.6 cm

Therefore , the value of r is r = 34.6 cm

Hence , the radius is r = 34.6 cm

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4 elephants

20 monkeys

6 zebras

//

z - 2 = elephants

(6) - 2 = 4 elephants

5(e) = monkeys

5(4) = 20 monkeys

20 + 4 + 7 = 30

Answer:

I, II, III, IV, V, VI, VII, VIII, IX, and X.

Step-by-step explanation:

ik the numerals

The proportion of the category of interest for a population is called a proportion.

A proportion is a measure of the relative frequency or occurrence of a particular category within a population. It is calculated by dividing the number of occurrences of the category by the total number of items in the population. A proportion is expressed as a fraction, decimal or percentage.

For instance, if there are 25 people in a room and 5 of them are wearing glasses, then the proportion of people wearing glasses is 5/25 or 0.2 or 20%.

conclusion, the proportion of the category of interest for a population is called a proportion. It is calculated by dividing the number of occurrences of the category by the total number of items in the population. A proportion is a measure of the relative frequency or occurrence of a particular category within a population. It can be expressed as a fraction, decimal or percentage. In order to make informed decisions based on data, it is essential to understand and interpret proportions correctly. Proportions are used in various fields such as statistics, research, marketing, and public policy to study, analyze, and report data.

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Hey there!

\( \sf{ \purple{ \boxed{\bold{m = - \dfrac{7}{3} }}}} \)

\( \\ \)

We are given the points \( \sf{P_1(\overbrace{ \blue{8}}^{\blue{x_1}} ,\underbrace{\orange{-8}}_{ \orange{y_1}}) \: and \: P_2(\overbrace{ \green{5}}^{\green{x_2}} ,\underbrace{\red{-1}}_{\red{y_2} })} \) . To find the slope \( \sf{\purple{m}} \) of such a line, we use the slope formula which is the following:

\( \sf{ \purple{m} }= \dfrac{\Delta y}{\Delta x} = \dfrac{ \red{y_2} - \orange{y_1}}{ \green{x_2 }- \blue{x_1}} \)

\( \\ \)

⇢Now, by plugging in our values, we get :

\( \sf{ \purple{m}} = \dfrac{ \red{ - 1} - \orange{( - 8)}}{ \green{5} \: - \: \blue{8}} = \dfrac{ \: \: 7 \: }{ - 3 \: } \\ \\ \implies \sf{ \purple{ \boxed{m = - \dfrac{7}{3} }}}\)

Therefore, the slope of the line is \( \sf{ \purple{ \boxed{m = - \dfrac{7}{3} }}} \)

\(\Large\maltese\underline{\textsf{A. What is Asked}}\)

What is the slope of a linear function that goes through (8,-8) and (5,-1)?

\(\Large\maltese\underline{\textsf{B. This problem has been solved!}}\)

Formula utilised, here \(\bf{\dfrac{y2-y1}{x2-x1}}\).

We utilise that formula because we have two points as our given information.

So, we

put in the values

\(\bf{\dfrac{-1-(-8)}{5-8}}\) | subtract on top and bottom

\(\bf{\dfrac{-1+8}{-3}}\) | simplify

\(\bf{\dfrac{7}{-3}\)

\(\cline{1-2}\)

\(\bf{Result:}\)

                \(\bf{=Slope=-\dfrac{7}{3}}\)

\(\LARGE\boxed{\bf{aesthetic\not1\theta l}}\)

Answer:

b

Step-by-step explanation:

I used the graph and figured out the answer

Hope this helps :)

Brainest pls?

Answer:

1/6

Step-by-step explanation:

Given the function

f(x)=x^3+x^2+x

Get the inverse. Let y = f(x)

y = x^3+x^2+x

Replace y with x

x = y³+y²+y

Differentiate with respect to x

1 =3y²dy/dx + 2ydy/dx + dy/dx

1 = (3y²+2y+1)dy/dx

dy/dx = 1/3y²+2y+1

g'(x) = 1/3(g(x))²+2g(x)+1

If x = 3

g'(3) = 1/3(g(3))²+2g(3)+1

g'(3) =1/3(1)²+2(1)+1

g'(3) = 1/3+2+1

g'(3) = 1/6

Hence g'(3) = 1/6

The Miller index notation for the (100) plane in an FCC crystal structure is [100].

Miller indices are a way to describe crystal planes and directions in a standardized manner. In the case of FCC crystal structure, the (100) plane is parallel to the x-y plane and intersects the x-axis, y-axis, and z-axis at points where the Miller indices are (1,0,0), (0,1,0), and (0,0,1), respectively.

However, to express the (100) plane in a concise and standardized manner, we can use the Miller index notation, which involves taking the reciprocals of the intercepts of the plane with the crystallographic axes and then reducing them to the smallest integer values. In the case of the (100) plane in FCC, all of the intercepts are 1, so the Miller indices are [100].

the pd expression for the (100) plane in FCC crystal structure is [100].

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Answer:

lily - 5

5+8= 13

James - 13

13+5= 18

18-75= 57

Michael - 57

The coefficient associated with CHILD is not significantly different from zero, since its p-value is greater than 0.10. The p-value for the CHILD coefficient is 0.208, which is greater than 0.10.

This means that we cannot reject the null hypothesis that the coefficient is equal to zero. Therefore, we cannot conclude that the coefficient is significantly different from zero.

The estimated value of the CHILD coefficient is -0.045, which means that a unit increase in the number of children per capita is associated with a decrease in GDP growth per capita by 0.045%. However, since the p-value is greater than 0.10, we cannot be confident that this decrease is real.

In other words, the data does not provide enough evidence to conclude that the number of children per capita has a significant impact on GDP growth per capita.

Here is a table of the p-values for the estimated coefficients:

Coefficient p-value

   BB         0.0004

 CHILD        0.208

As you can see, the p-value for the CHILD coefficient is much larger than the p-value for the BB coefficient. This means that there is much less evidence to suggest that the CHILD coefficient is significantly different from zero.

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Answer:

the one with the 6.....?...........

A set of treatment and control groups for a retrospective study on the effects of endocrine disruptors on humans a group of children with mothers exposed to PCBs during pregnancy and a group of children who were exposed to DDT after they were born (option c).

In a retrospective study, researchers investigate the effects of endocrine disruptors on humans by analyzing past data and observing correlations. To ensure reliable findings, it is crucial to establish appropriate treatment and control groups. These groups are designed to compare individuals who have been exposed to different levels or types of endocrine disruptors, allowing researchers to assess the effects accurately. Let's explore the potential treatment and control groups for such a study.

A group of children with mothers exposed to PCBs during pregnancy and a group of children who were exposed to DDT after they were born:

In this case, the treatment group would consist of children whose mothers were exposed to PCBs during pregnancy. The control group, on the other hand, would include children who were exposed to DDT after birth. PCBs and DDT are both endocrine disruptors, but by comparing these two groups, researchers can examine the effects of prenatal exposure (PCBs) versus postnatal exposure (DDT).

Hence the correct option is (c).

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Complete Question

Which could be a set of treatment and control groups for a retrospective study on the effects of endocrine disruptors on humans?

(a) A group of farmers that are planning to spray crops with atrazine and a group of farmers that are planning to use organic pesticides,

(b) A group of construction workers that have been exposed to asbestos and a group of construction workers that have been exposed to PCBs,

(c) A group of children with mothers exposed to PCBs during pregnancy and a group of children who were exposed to DDT after they were born,

(d) Members of a town that was downwind of a commercial farm that sprayed pesticides and members of a town that was downwind of an organic farm,

(e) Humans raised when DDT was used and humans raised after DDT was no longer used.

The source of error is computed in the denominator of the test statistic for the between-subjects design, but not the within-subjects design is Option (c) between-groups.

The test statistic is a numerical value that measures the difference between groups, and it is typically derived from the data collected in the experiment. In a between-subjects design, the test statistic is computed by comparing the means of two or more groups of participants on a given variable. This means that the test statistic reflects the difference between groups, rather than within groups.

In contrast, in a within-subjects design, the test statistic is computed by comparing the scores of the same group of participants on a given variable, before and after some intervention or treatment. This means that the test statistic reflects the difference within groups, rather than between groups.

The Given question States, which source of error is computed in the denominator of the test statistic for the between-subjects design but not the within-subjects design?  In a between-subjects design, the test statistic is typically computed using an analysis of variance (ANOVA), which involves partitioning the total variability in the data into two components: the variability between groups and the variability within groups. The denominator of the test statistic in a between-subjects ANOVA reflects the variability within groups, which is a measure of the random error in the data. This error arises from individual differences between participants that are not related to the experimental manipulation. By contrast, the variability between groups reflects the systematic effects of the experimental manipulation, and is used to estimate the effect size or the degree of association between the independent and dependent variables.

In a within-subjects design, the variability between groups is not relevant, because there is only one group of participants that is measured twice (or more) on the same variable. Instead, the denominator of the test statistic in a within-subjects design reflects the variability within subjects, which is a measure of the random error in the data. This error arises from factors such as measurement error, natural variability in the participants' responses, and other sources of noise that are not related to the experimental manipulation.

The source of error computed in the denominator of the test statistic depends on the type of experimental design used. In a between-subjects design, the denominator reflects the variability within groups, while in a within-subjects design, it reflects the variability within subjects. The choice of design depends on the research question, the nature of the variables being measured, and other practical considerations.

Therefore, the source of error is computed in the denominator of the test statistic for the between-subjects design, but not the within-subjects design is Option (c) between-groups.

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Complete Question

Which source of error is computed in the denominator of the test statistic for the between-subjects design, but not the within-subjects design?

a. Between-persons

b. Within-groups

c. Between-groups

d. Within-persons

Roberto's z-score is approximately 2.29. This means that his score is about 2.29 standard deviations above the mean.

A z-score (also known as a standard score) is a measure of how many standard deviations a data point is away from the mean of a distribution. It is used to standardize data so that we can compare values from different distributions.

For example, if a student's score on a test is 80 and the mean score is 75 with a standard deviation of 5, the z-score for the student's score would be:

z = (80 - 75) / 5

z = 1

This means that the student's score is one standard deviation above the mean.

To find Roberto's z-score, we can use the formula:

(x - μ) / σ

where x is Roberto's score, μ is the mean of the test, and σ is the standard deviation of the test.

We are given that the mean was 69 and the standard deviation was 7. Roberto scored 85. So we can plug in these values into the formula and solve for z:

z = (85 - 69) / 7

z = 16 / 7

z ≈ 2.29

Therefore, Roberto's z-score is approximately 2.29.

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In this triangle it is clear that the unknown side x is the hypotenuse of both the triangles that are being formed . So , let us take any one of the triangles and with it's length let us find the length of their hypotenuse which is side x .

= 5² + 5² = x² ( according to the pythagorean theorem the square on the hypotenuse will be equal to the sum of the squares on the other two legs )

= 25 + 25 = x²

= 50 = x²

= 7.0710678119 = x

But they have given that we have to round it off to the nearest tenths , so ;

= 7.0710678119 will be equal to = 7.10

= 7.1 = x

Therefore , the length of the unknown side x = 7.1 .

In an instruction like "z = x y," the symbols x, y, and z are examples of variables.

Variables are placeholders that represent unknown or changing values in mathematical expressions or equations. They allow us to generalize mathematical relationships and solve problems using algebraic methods.

In mathematics, variables are symbols that represent unknown or varying quantities. They are used to express mathematical relationships, equations, and formulas.

In the given instruction "z = x y," the symbols x, y, and z are variables.

In this case, x and y represent the input values, and z represents the output or result of the mathematical operation defined by the equation.

Variables are used extensively in algebra to solve equations, manipulate expressions, and analyze mathematical relationships. They enable us to express and solve problems symbolically, without knowing the specific values of the variables.

By assigning specific values to variables, we can evaluate expressions, solve equations, and find solutions to mathematical problems.

Variables can represent a wide range of quantities, including numbers, measurements, constants, or even abstract concepts. They provide flexibility and generality in mathematical modeling and problem-solving.

By using variables, we can establish connections between different mathematical quantities and derive meaningful conclusions based on their relationships.

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Answer:

The answer is B.

Reasoning:

A. 5 + (-17) = -12✔

B. -17 - 5 = -22 ✖

C. -17 + 5 = -12 ✔

D. -12 ✔

Answer:

B: -17+5

Step- by- step explanation

The expression:

To get the value of x

Step 1: solve the expression

Step 2: solve the expression introducing the negative sign

The answer is:

x=-1 or x =11

Answer:

to this question is it is 1.01

sin(45) =opp/18

opp=18sin(45)

h = 9 root 2