plz help me find x 9-10 but if you can do 9-12

The problem considers a random sample \( X_1, \ldots, X_n \) from a uniform distribution \( U(0, \theta) \) and aims to find the suitably normalized limit distribution for the statistics.

(a) To obtain the limit distribution of \( \frac{n+1}{n}X_{(n)} \), where \( X_{(n)} \) represents the maximum order statistic, we normalize it by multiplying by \( \frac{n+1}{n} \). The resulting limit distribution, as n approaches infinity, is the exponential distribution with rate parameter \( \lambda = \frac{1}{\theta} \).

(b) Similarly, for \( \frac{n-1}{n}X_{(n)} \), we normalize it by multiplying by \( \frac{n-1}{n} \). As n tends to infinity, the limit distribution is also the exponential distribution with rate parameter \( \lambda = \frac{1}{\theta} \).

(ii) When n is large, both \( \frac{n+1}{n}X_{(n)} \) and \( \frac{n-1}{n}X_{(n)} \) converge to the exponential distribution with rate parameter \( \frac{1}{\theta} \). However, \( X_{(n)} \) itself is not normalized and does not have a well-defined limit distribution.

In terms of choosing an estimator for \( \theta \), it is preferable to use either \( \frac{n+1}{n}X_{(n)} \) or \( \frac{n-1}{n}X_{(n)} \) over \( X_{(n)} \) alone. The normalized statistics provide more efficient estimators that converge to the true value of \( \theta \) as n increases.

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Answer:

e, f

Step-by-step explanation:

A measurement of variability is an overview of the amount of dispersion  in a dataset. The measures that can describe the variation on a data set are Range, Interquartile Range, Variance, and Standard Deviation.

So ,The among the given options the e. Interquartile range f. Range

Range of dataset is the difference between the larges and smallest elements in the dataset .

The middle of the data between the upper and lower quartiles are called the inter-quartile range. That means that 50 percent of data points between Q1 and Q3 are included within the interquartile range.

Answer:

x=-4 y=5

Step-by-step explanation:

3×(16-4y)+4y=8

48-12y+4y=8

-8y=-40

y=5

x=16-4×5

x=-4

Answer:

Is it the answer is C?

2+4+3+5+1=15

Answer:

Geometric.

Step-by-step explanation:

It is Geometric because there is a common ratio between the terms.

50p/100p = 1/2

25p/50p = 1/2

The common ratio is 1/2.

Each term is obtained by multiplying by 1/2, so the next term in this progression is 25p * 1/2 = 12.5p.

Answer:

$49.14 is the total amount

$3.64 is the sales tax

Step-by-step explanation:

45.5 x 0.08 = 3.64

45.5 + 3.64 = 49.14

Answer:Linear Algebra Examples ... Linear Algebra. Solve by Substitution y=x+3 , y=2x-1 ... Eliminate the equal sides of each equation and combine. ... Subtract 1 1 from 8 8 . ... The solution to the system of equations can be represented as a point.

Step-by-step explanation:

Answer:

5/4

Step-by-step explanation:

(y₂ - y₁) / (x₂ - x₁)

(4,9) (-8, -6)

plug in

(-6 - 9) / (-8 - 4)

solve within parentheses

-15/-12

simplify

5/4

what is the slope of points (4,9) (-8,-6)

Answer:

5/4

Step-by-step explanation:

let's think about it logically :

|x| can only be positive, from 0 to +infinity.

but the second part "- 4" will bring the result for small x values into the negative realm.

x = 0 gives us f(x) = -4.

x = 4 gives us f(x) = 0

x = -4 gives us f(x) = 0

so, if is the 3rd graph (bottom left).

Answer:

C

Step-by-step explanation:

Four comparisons of treatment means can be made.

When the null hypothesis for an ANOVA analysis comparing four treatment means is rejected, it implies that at least one of the treatment means significantly differs from the others. In this case, four comparisons of treatment means can be made to identify which specific treatments are significantly different. These post hoc comparisons are typically performed using methods such as Tukey's test, Bonferroni correction, or Scheffe's method. By conducting these pairwise comparisons, researchers can determine the specific treatments that exhibit statistically significant differences in means.

The number of comparisons that can be made when the null hypothesis for an ANOVA analysis comparing four treatment means is rejected is four. This implies that at least one treatment mean significantly differs from the others, and conducting posthoc tests allows researchers to identify the specific treatments with significant differences.

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Answer: A

Step-by-step explanation: 35 / 2 = 17.5

Answer:

C. is correct

Step-by-step explanation:

i hope this helps :) brainliest please?

Answer:

x≤−9 or x≥5 or x=0

Step-by-step explanation:

Let's solve your inequality step-by-step.

x2(x+9)(x−5)≥0

x4+4x3−45x2≥0

Let's find the critical points of the inequality.

x4+4x3−45x2=0

x2(x−5)(x+9)=0(Factor left side of equation)

x2=0 or x−5=0 or x+9=0(Set factors equal to 0)

x=0 or x=5 or x=−9

Check intervals in between critical points. (Test values in the intervals to see if they work.)

x≤−9(Works in original inequality)

−9≤x≤0(Doesn't work in original inequality)

0≤x≤5(Doesn't work in original inequality)

x≥5(Works in original inequality)

Answer:

x≤−9 or x≥5 or x=0

I also recommend MathPapa or Symbolab to help you with your math.

Answer: yes, the equation \(y = 5x +2\) is a slope-intercept form.

Step-by-step explanation:

-The equation of a slope-intercept form:

\(y = mx + b\)  (where \(m\) represents the slope, and \(b\) represents the y-intercept).

Answer:

-2/3

Step-by-step explanation:

To calculate the molecular weight of a gas with a density of 1.524 g/l at STP, we can use the ideal gas law: PV = nRT. At STP, the pressure (P) is 1 atm, the volume (V) is 22.4 L/mol, and the temperature (T) is 273 K. The molecular weight of the gas with a density of 1.524 g/L at STP is approximately 32.0 g/mol.

Rearranging the equation, we get n = PV/RT.

Next, we can calculate the number of moles (n) of the gas using the given density of 1.524 g/l. We know that 1 mole of any gas at STP occupies 22.4 L, so the density can be converted to mass by multiplying by the molar mass (M) and dividing by the volume: density = (M*n)/V. Rearranging the equation, we get M = (density * V) / n.

Substituting the given values, we get n = (1 atm * 22.4 L/mol) / (0.0821 L*atm/mol*K * 273 K) = 1 mol. Then, M = (1.524 g/L * 22.4 L/mol) / 1 mol = 34.10 g/mol. Therefore, the molecular weight of the gas is 34.10 g/mol.

To calculate the molecular weight of a gas with a density of 1.524 g/L at STP, you can follow these steps:

1. Recall the ideal gas equation: PV = nRT

2. At STP (Standard Temperature and Pressure), the temperature (T) is 273.15 K and the pressure (P) is 1 atm (101.325 kPa).

3. Convert the density (given as 1.524 g/L) to mass per volume (m/V) by dividing it by the molar volume at STP (22.4 L/mol). This will give you the number of moles (n) per volume (V):

  n/V = (1.524 g/L) / (22.4 L/mol)

4. Calculate the molar mass (M) of the gas using the rearranged ideal gas equation, where R is the gas constant (8.314 J/mol K):

  M = (n/V) * (RT/P)

5. Substitute the values and solve for M:

  M = (1.524 g/L / 22.4 L/mol) * ((8.314 J/mol K * 273.15 K) / 101325 Pa)

6. Calculate the molecular weight of the gas:

  M ≈ 32.0 g/mol

Therefore, the molecular weight of the gas with a density of 1.524 g/L at STP is approximately 32.0 g/mol.

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Answer:

divide both sides by 3

Step-by-step explanation:

The solution to the equation a(y + 1) = b, which is the value of y, is solved as: y = b/a - 1 or y = (b - a)/a.

To solve an equation for a variable, you need to isolate the variable on one side of the equation. To do this, you need to use the basic operations of arithmetic: addition, subtraction, multiplication, and division.

Given the equation or formula, a(y + 1) = b, we are asked to find the value of y, which means we have to use basic operations to isolate the variable, "y" to one side of the equation.

Follow the steps below:

a(y + 1) = b [given]

Divide both sides by a

a(y + 1)/a = b/a [division property of equality]

y + 1 = b/a

Subtract 1 from both sides:

y + 1 - 1 = b/a - 1

y = b/a - 1

or

y = (b - a)/a

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Within-treatment variation: Variation among individuals of different groups. Between-treatment variation: Variation between individuals in different groups. Variation explained by factors included in the ANOVA model: Variation attributed to the factors or variables being studied. Variation that is not part of the ANOVA model: Residual or error variation not accounted for by the model.

What is ANOVA?

ANOVA stands for Analysis of Variance. It is a statistical method used to analyze and compare the means of two or more groups or treatments to determine if there are significant differences among them.

The within-treatment variation reflects variation among individuals of different groups.

Within-treatment variation refers to the variability observed within each group or treatment condition in an analysis of variance (ANOVA) model. It measures the differences or variations among individuals within the same group or treatment condition. This variation is typically attributed to random or uncontrolled factors that affect individuals within each group separately.

On the other hand, the variation between individuals in different groups is referred to as the between-treatment variation. It measures the differences or variations observed between the group means or treatment conditions in an ANOVA model. This variation is of interest as it helps determine if there are significant differences among the groups being compared.

The variation explained by factors included in the ANOVA model refers to the portion of the total variation that can be attributed to the specific factors or variables being studied in the analysis. It represents the variation that can be explained or accounted for by the factors included in the model.

Lastly, the variation that is not part of the ANOVA model refers to the residual or error variation. It represents the remaining variation that cannot be explained by the factors or variables included in the ANOVA model. This variation is often attributed to uncontrolled or unmeasured factors, measurement errors, or other sources of variability that are not accounted for in the model.

In summary:

Within-treatment variation: Variation among individuals of different groups.

Between-treatment variation: Variation between individuals in different groups.

Variation explained by factors included in the ANOVA model: Variation attributed to the factors or variables being studied.

Variation that is not part of the ANOVA model: Residual or error variation not accounted for by the model.

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The absolute Maximum of  f(t) = 7 cos t, −3π/2 ≤ t ≤ 3π/2 is 7 and the absolute Minimum of f(t) = 7 cos t, −3π/2 ≤ t ≤ 3π/2 is -7.

The function f(t) = 7 cos(t) has a period of 2π, which means that it repeats itself every 2π units. In the given interval, the function takes its maximum and minimum values at the endpoints of the interval and at the critical points where the derivative of the function is zero.

The critical points of f(t) in the interval −3π/2 ≤ t ≤ 3π/2 are t = −π/2, π/2, and 3π/2, where the derivative of the function f(t) is zero:

f'(t) = -7 sin(t) = 0

This occurs when sin(t) = 0, which implies that t = −π/2, π/2, and 3π/2.

Therefore, the absolute maximum and minimum of f(t) occur at the endpoints of the interval and the critical points, and are as follows:

Absolute maximum: f(π/2) = 7

Absolute minimum: f(−3π/2) = -7

So, the absolute maximum value of f(t) is 7, which occurs at t = π/2, and the absolute minimum value of f(t) is -7, which occurs at t = −3π/2.

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The sample mean of the observations is 19.25 and the standard deviation is 2.15

Sample mean is found by adding up all the individual values of the sample, then dividing by the total number of values in the sample.  

Sample standard deviation is the square root of the variance

mean = (23 + 25 + 16 + 20 + 13 + 10 + 28 + 19)/8

mean = 19.25

variance = (x₁ - mean)²/n(n-1)

variance = ((23 - 19.25)² + (25 - 19.25)² + (16 - 19.25)² + (20 - 19.25)² + (13 - 19.25)² + (10 - 19.25)² + (28 - 19.25)² + (19 - 19.25)²)/(8(7))

variance = 259.5/56

variance = 4.63

Standard deviation = √variance = √4.63 = 2.15

Therefore, the sample mean of the observations is 19.25 and the standard deviation is 2.15

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37 and 1 / 4 = 37 * 6 = 74 * 3 = 222

Answer:

374x

brrrrrrrrrrrrruhhhhhhhhhhhhhh

Answer:

374x

Step-by-step explanation:

Just add 32 and 342 together

32 + 342

374

Then add the x back on

374x

Hope this helped :)

Answer:

These two warehouses will contain the same number of boxes in 51 days.

Step-by-step explanation:

Since the number of boxes in Warehouse "A" currently totaling 476 is increasing at a rate of 4 boxes per day, while the number of boxes in Warehouse "B" currently totaling 986 is decreasing at a rate of 6 boxes per day, To determine in how many days these two warehouses contain the same number of boxes, the following calculation must be performed:

Warehouse A = 476 + 4X

Warehouse B = 986 - 6X

476 + 4 x 50 = 476 + 200 = 676

986 - 6 x 50 = 986 - 300 = 686

476 + 4 x 51 = 476 + 204 = 680

986 - 6 x 51 = 986 - 306 = 680

Therefore, these two warehouses will contain the same number of boxes in 51 days.

Answer:

x = 17

Step-by-step explanation:

let x be the number she is thinking about

5x + 8 = 93

Rearrange

5x = 85

x = 17

The distribution in residence is different today at a 0.05 level of significance can be conclude because the p-value = 0.0172

from the data given we can make the table below:

Categories       Observed(fo)        Expected (fe)        (fo-fe)²/fe

NW Oregon        3109           4357*0.727=3167.539       1.082

SW Oregon        902             4357*0.207=901.899           0

Central Oregon    244          4357*0.048=209.136         5.812

Eastern Oregon    102           4357*0.028=121.996         3.277

Sum =                    4357        4357                                   10.171

first,  null and alternative hypotheses need to be tested:

H0​:p1​=0.727,p2​=0.207,p3​=0.048,p4​=0.028

Ha​: The population proportion partially deviates from the value given by the null hypothesis

This corresponds to a Chi-Square test for Goodness of Fit.

then, Based on the data provided, the significance level is α=0.05, the number of degrees of freedom is df=4−1=3, so then the rejection region for this test is R={\(X^{2}X^{2}\)>7.815}.

after that we should do test statistic

The Chi-Squared statistic is calculated as follows:

∑\(^{n} _{i=1}\)\(\frac{(Oi-Ei)}{y} \\\) =   1.082+0+5.812+10.171 +3.277= 10.171

the we can make a decision about the null hypothesis by

\(X^{2} = 10.71 > X^{2} _{c} = 7.815\)

it is then concluded that the null hypothesis is rejected.

Therefore, there is enough evidence to claim that some of the population proportions differ from those stated in the null hypothesis, at the α=0.05 significance level.

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Answer:

343

Step-by-step explanation:

8 bags with 7 items in them = 56 items.

56 + the 287 that Kacey has = 343

Answer:

b = sp

Step-by-step explanation:

box = seeds per packet

The given relation can be used to find the total number of seeds in box b, using the equation b = sp. Hence, 3rd option is the right choice.

Equations are relations shown between two equal algebraic expressions.

We are given a box of sunflower seeds, containing p packets of seeds, each of which contains s number of seeds.

We are asked to write an equation that can be used to find the total number of seeds in the box, b.

We know that the box contains p packets of seeds.

In 1 packet we have s number of seeds.

∴ In p packets, we will have an s*p number of seeds or sp seeds.

Since the box contains p packets and the total number of seeds in the box is b, then we can say that

b = the number of seeds in p packets

or, b = sp, which is the required equation.

∴ The given relation can be used to find the total number of seeds in box b, using the equation b = sp. Hence, 3rd option is the right choice.

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Answer:

Solution given:

for second

we have

f(x)=x²-9x-36

let

y=x²-9x-36

when

x=0

y=-36

when

y=0

0=x²-9x-36

x²-12x+3x-36=0

x(x-12)+3(x-12)=0

(x-12)(x+3)=0

either

x=12

x=-3

So,

x and y intercepts are (-3,0)(12,0) and 0,-36)