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2 years ago

Determining the Value of a Slope from a Graph

Mathematics

1 answer:

Brums [2.3K]2 years ago

5 0

Answer:the answer is B : -250

Step-by-step explanation:

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pav-90 [236]

Ending position (in order)

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4 0

2 years ago

Read 2 more answers

Jeff uses 3 fifth-size strips to model 3/5. He wants to use tenth-size strips to model an equivalent fraction. How many tenth-si

sergiy2304 [10]

Sixteen. For the fraction 6/10 which is equivalent to 3/5

4 0

2 years ago

Read 2 more answers

a tram moved downward 15 meters in 5 seconds at a constant rate. what was the change in the team's elevation each second?

Sergio [31]

Answer: 3 meters downward per second

Step-by-step explanation:

If it moved downward 15 meters for every 5 seconds and to find the change in the elevation each second then divide the meters by 5.

15/5 = 3

3 meters per second

4 0

2 years ago

cate and elena were playing a card game the stack of cards in the middle had 24 cards in it to begin wiht. Cate added 8 cards to

Kaylis [27]

24+8 = 30

30 - 12 = 18

18-9 = 8

There are 8 cards left in the stack

7 0

3 years ago

Read 2 more answers

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

2 years ago