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3 years ago

Please help thank you so much Math experts

Mathematics

2 answers:

GaryK [48]3 years ago

7 0

A. 49.3 (I hope I’m not too late)

maria [59]3 years ago

4 0

Answer:

A.) 49.3

Step-by-step explanation:

To find the mean of a given set of data points, you need to add up all of the numbers given in the data set. So let's add these altogether:

43 + 55 + 51 + 62 + 64 + 38 + 35 + 45 + 51 = 444.

With that said, now we have to divide the number of how many numbers given into our so-far-answer of 444. There are 9 numbers in this data set, so we need to divide 9 into 444.

444 ÷ 9 = 49.33333...

The question asks us to round to the nearest tenth, which would be the first 3 in this situation. Normally, we would need a longer process for rounding, but since these are all 3's, we can do this faster. We can get rid of the other 3's and be left with the first letter of A.)'s answer.

I hope that this helps.

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Find m<PKL if m<JKP=120° and m<JKL=168°

brilliants [131]

MajshssnayssgsvhahsyswhJusjsjsjJjsjwsjsjssjHhsvsysjwbkekwjwjsjeejwbsjejsywhwhsbennwsbbsbebsuejsksowiwejsudhehevhehhehe

Is your answer

3 0

3 years ago

A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and

mr Goodwill [35]

Answer:

Bias for the estimator = -0.56

Mean Square Error for the estimator = 6.6311

Step-by-step explanation:

Given - A normally distributed random variable with mean 4.5 and standard deviation 7.6 is sampled to get two independent values, X1 and X2. The mean is estimated using the formula (3X1 + 4X2)/8.

To find - Determine the bias and the mean squared error for this estimator of the mean.

Proof -

Let us denote

X be a random variable such that X ~ N(mean = 4.5, SD = 7.6)

Now,

An estimate of mean, μ is suggested as

$\mu = \frac{3X_{1} + 4X_{2} }{8}$

Now

Bias for the estimator = E(μ bar) - μ

= $E( \frac{3X_{1} + 4X_{2} }{8}) - 4.5$

= $\frac{3E(X_{1}) + 4E(X_{2})}{8} - 4.5$

= $\frac{3(4.5) + 4(4.5)}{8} - 4.5$

= $\frac{13.5 + 18}{8} - 4.5$

= $\frac{31.5}{8} - 4.5$

= 3.9375 - 4.5

= - 0.5625 ≈ -0.56

∴ we get

Bias for the estimator = -0.56

Now,

Mean Square Error for the estimator = E[(μ bar - μ)²]

= Var(μ bar) + [Bias(μ bar, μ)]²

= $Var( \frac{3X_{1} + 4X_{2} }{8}) + 0.3136$

= $\frac{1}{64} Var( {3X_{1} + 4X_{2} }) + 0.3136$

= $\frac{1}{64} ( [{3Var(X_{1}) + 4Var(X_{2})] }) + 0.3136$

= $\frac{1}{64} [{3(57.76) + 4(57.76)}] } + 0.3136$

= $\frac{1}{64} [7(57.76)}] } + 0.3136$

= $\frac{1}{64} [404.32] } + 0.3136$

= $6.3175 + 0.3136$

= 6.6311

∴ we get

Mean Square Error for the estimator = 6.6311

6 0

3 years ago

Phythagorean theorem help me plsss

marysya [2.9K]

Answer:

Step-by-step explanation:

We know that a^2+b^2=c^2 from the Pythagorean theorem where a and b are the legs and c is the hypotenuse

4^2+3^2 = c^2

16+9 = c^2

25 = c^2

Taking the square root of each side

sqrt(25) = sqrt(c^2)

5 =c

3 0

3 years ago

Read 2 more answers

If line a is perpendicular to line b and the slope of line a is 7 whats the slope of line b

amm1812

Answer:

If a line is perpendicular to another line, that means that the slope is completely opposite that of the original line. The first thing that we do to the slope is we negate the number which means that if we have a slope of $-7$ our slope because $7$ in this step. In our case our slope is $7$ so in this step it becomes $-7$ .

Moving onto the second part which is to get the reciprocal of the number which means that if we have $\frac{1}{2}$ then we would switch it to $2$ . In our case our number is $-7$ so we would make that into a fraction like this $-\frac{1}{7}$ .

In conclusion, our final slope of the perpendicular line is $-\frac{1}{7}$ .

Hope this helps! Let me know if you have any questions

8 0

2 years ago

Read 2 more answers

Southern Oil Company produces two grades of gasoline: regular and premium. The profit contributions are $0.30 per gallon for reg

Contact [7]

Answer:

a) MAX--> PC (R,P) = 0,3R+ 0,5P

b) Optimal solution: 40.000 units of R and 10.000 of PC = $17.000

c) Slack variables: S3=1000, is the unattended demand of P, the others are 0, that means the restrictions are at the limit.

d) Binding Constaints:

1. 0.3 R+0.6 P ≤ 18.000

2. R+P ≤ 50.000

3. P ≤ 20.000

4. R ≥ 0

5. P ≥ 0

Step-by-step explanation:

I will solve it using the graphic method:

First, we have to define the variables:

R : Regular Gasoline

P: Premium Gasoline

We also call:

PC: Profit contributions

A: Grade A crude oil

• R--> PC: $0,3 --> 0,3 A

• P--> PC: $0,5 --> 0,6 A

So the ecuation to maximize is:

MAX--> PC (R,P) = 0,3R+ 0,5P

The restrictions would be:

1. 18.000 A availabe (R=0,3 A ; P 0,6 A)

2. 50.000 capacity

3. Demand of P: No more than 20.000

4. Both P and R 0 or more.

Translated to formulas:

Answer d)

1. 0.3 R+0.6 P ≤ 18.000

2. R+P ≤ 50.000

3. P ≤ 20.000

4. R ≥ 0

5. P ≥ 0

To know the optimal solution it is better to graph all the restrictions, once you have the graphic, the theory says that the solution is on one of the vertices.

So we define the vertices: (you can see on the graphic, or calculate them with the intersection of the ecuations)

V:(R;P)

• V1: (0;0)

• V2: (0; 20.000)

• V3: (20.000;20.000)

• V4: (40.000; 10.000)

• V5:(50.000;0)

We check each one in the profit ecuation:

MAX--> PC (R,P) = 0,3R+ 0,5P

• V1: 0

• V2: 10.000

• V3: 16.000

• V4: 17.000

• V5: 15.000

As we can see, the optimal solution is

V4: 40.000 units of regular and 10.000 of premium.

To have the slack variables you have to check in each restriction how much you have to add (or substract) to get to de exact (=) result.

3 0

3 years ago