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vladimir1956 [14]
3 years ago
10

Solve for r.Show your work! 12=r -- (34 -- 2) pls help

Mathematics
2 answers:
kvv77 [185]3 years ago
7 0

Answer:

r=20

Step-by-step explanation:

34-2=32 32 - 12 =20 r= 20

lord [1]3 years ago
5 0

it was already answered LOL

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No it is not because 5 tons is 10 thousand pounds
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What is the value of y?
NNADVOKAT [17]

Answer:

b-65

Step-by-step explanation:

They give you 130 and so to get the next measure its 180-130 and you get 50. So the blank angle is 50. Then the next two angles are y which means theyre equal to each other so they have to be the same number. Get 180 again and subtract 50 and get 130. Split 130 in half and get 65.

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3 years ago
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A sample of 5 buttons is randomly selected and the following diameters are measured in inches. Give a point estimate for the pop
Helen [10]

Answer:

s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}

But we need to calculate the mean with the following formula:

\bar X = \frac{\sum_{i=1}^n X_I}{n}

And replacing we got:

\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072

And for the sample variance we have:

s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance \sigma^2

E(s^2) = \sigma^2

Step-by-step explanation:

For this case we have the following data:

1.04,1.00,1.13,1.08,1.11

And in order to estimate the population variance we can use the sample variance formula:

s^2 = \frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}

But we need to calculate the mean with the following formula:

\bar X = \frac{\sum_{i=1}^n X_I}{n}

And replacing we got:

\bar X = \frac{ 1.04+1.00+1.13+1.08+1.11}{5}= 1.072

And for the sample variance we have:

s^2 = \frac{(1.04-1.072)^2 +(1.00-1.072)^2 +(1.13-1.072)^2 +(1.08-1.072)^2 +(1.11-1.072)^2}{5-1}= 0.00277\ approx 0.003

And thi is the best estimator for the population variance since is an unbiased estimator od the population variance \sigma^2

E(s^2) = \sigma^2

3 0
3 years ago
Last​ year, a person wrote 123 checks. Let the random variable x represent the number of checks he wrote in one​ day, and assume
Sunny_sXe [5.5K]

Answer:The mean number of checks written per​ day = 0.3370

The standard deviation = 0.5805

The variance = 0.3370

Step-by-step explanation:

Let the random variable x represent the number of checks he wrote in one​ day.

Given : The number of checks written in last year = 123

Let the number of days in the year must be 365.

Now, the mean number of checks written per​ day will be  :-

\lambda=\dfrac{123}{365}=0.33698630137\approx0.3370

We know that in Poisson distribution , the variance is equals to the mean value .

\text{Thus , Variance }=\sigma^2= 0.3370

\Rightarrow\ \sigma=\sqrt{0.3370}=0.580517010948\approx0.5805

Thus,  Standard deviation = 0.5805

3 0
3 years ago
1. f(x) = x^3– 4x^2 – 7x + 10
True [87]

9514 1404 393

Answer:

  zeros: {-2, 1, 5}

Step-by-step explanation:

A graphing calculator works nicely for identifying turning points, roots, increasing/decreasing intervals, and more.

8 0
3 years ago
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