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2 years ago

The temperature was -2F. Dropped 9F. What is the temperature after it dropped 9F

Mathematics

2 answers:

xz_007 [3.2K]2 years ago

8 0

-11 degrees F I hope this helps

Allisa [31]2 years ago

7 0

Answer:

________

-11

________

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Identify the expression as a numerical expressionor a variable expression. For a variable expression, name the variable.

Karolina [17]

Answer:

Numerical expression

Step-by-step explanation:

This is a numerical expression since there is no unknown value. Both values being multiplied are numbers.

8 0

3 years ago

Find the sum of (4x^3+2x) + (8x^3+4)

Savatey [412]

The answer would be 12x^3+ 2x + 4

5 0

2 years ago

Is the square root of -11.2 a rational number?

Schach [20]

No, it is an imaginary number.
Can't take the square root of a negative number without creating a method termed an imaginary number, which is the square root of -1 which they have used " i " to signify.
Then square root of -11.2 would be written Sqrt(11.2)i. The Sqrt(11.2) = 3.3466
so the answer is 3.3466i

5 0

3 years ago

Let X1,X2......X7 denote a random sample from a population having mean μ and variance σ. Consider the following estimators of μ:

Viefleur [7K]

Answer:

a) In order to check if an estimator is unbiased we need to check this condition:

$E(\theta) = \mu$

And we can find the expected value of each estimator like this:

$E(\theta_1 ) = \frac{1}{7} E(X_1 +X_2 +... +X_7) = \frac{1}{7} [E(X_1) +E(X_2) +....+E(X_7)]= \frac{1}{7} 7\mu= \mu$

So then we conclude that $\theta_1$ is unbiased.

For the second estimator we have this:

$E(\theta_2) = \frac{1}{2} [2E(X_1) -E(X_3) +E(X_5)]=\frac{1}{2} [2\mu -\mu +\mu] = \frac{1}{2} [2\mu]= \mu$

And then we conclude that $\theta_2$ is unbiaed too.

b) For this case first we need to find the variance of each estimator:

$Var(\theta_1) = \frac{1}{49} (Var(X_1) +...+Var(X_7))= \frac{1}{49} (7\sigma^2) = \frac{\sigma^2}{7}$

And for the second estimator we have this:

$Var(\theta_2) = \frac{1}{4} (4\sigma^2 -\sigma^2 +\sigma^2)= \frac{1}{4} (4\sigma^2)= \sigma^2$

And the relative efficiency is given by:

$RE= \frac{Var(\theta_1)}{Var(\theta_2)}=\frac{\frac{\sigma^2}{7}}{\sigma^2}= \frac{1}{7}$

Step-by-step explanation:

For this case we assume that we have a random sample given by: $X_1, X_2,....,X_7$ and each $X_i \sim N (\mu, \sigma)$

Part a

In order to check if an estimator is unbiased we need to check this condition:

$E(\theta) = \mu$

And we can find the expected value of each estimator like this:

$E(\theta_1 ) = \frac{1}{7} E(X_1 +X_2 +... +X_7) = \frac{1}{7} [E(X_1) +E(X_2) +....+E(X_7)]= \frac{1}{7} 7\mu= \mu$

So then we conclude that $\theta_1$ is unbiased.

For the second estimator we have this:

$E(\theta_2) = \frac{1}{2} [2E(X_1) -E(X_3) +E(X_5)]=\frac{1}{2} [2\mu -\mu +\mu] = \frac{1}{2} [2\mu]= \mu$

And then we conclude that $\theta_2$ is unbiaed too.

Part b

For this case first we need to find the variance of each estimator:

$Var(\theta_1) = \frac{1}{49} (Var(X_1) +...+Var(X_7))= \frac{1}{49} (7\sigma^2) = \frac{\sigma^2}{7}$

And for the second estimator we have this:

$Var(\theta_2) = \frac{1}{4} (4\sigma^2 -\sigma^2 +\sigma^2)= \frac{1}{4} (4\sigma^2)= \sigma^2$

And the relative efficiency is given by:

$RE= \frac{Var(\theta_1)}{Var(\theta_2)}=\frac{\frac{\sigma^2}{7}}{\sigma^2}= \frac{1}{7}$

5 0

3 years ago

*not drown to scale

bulgar [2K]

Answer:

26.9 inches

Step-by-step explanation:

2x Pythagorean theorem

First we find the length of AC with ABC. AC is the hypotenuse of triangle ABC.

AC = sqrt(7^2+24^2) = sqrt625 = 25.

Now, AD is the hypotenuse of ACD. So AD = sqrt(25^2+10^2) = sqrt(725) = 26.925824 which is about 26.9 inches.

8 0

2 years ago

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