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3 years ago

Celine was working on the following problem and can't seem to get the problem right. Choose the step where she made a mistake.

Mathematics

1 answer:

Leya [2.2K]3 years ago

3 0

Answer:

- 5

Step-by-step explanation:

Given

(- 2 × 2 - 6) ÷ 2

Evaluate the parenthesis performing the multiplication before subtracting.

= (- 4 - 6) ÷ 2

= - 10 ÷ 2

= - 5

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Ms. Rose bought a pack of star stickers. Out of every 10 stars, 4 are gold. If there are 60 stars in the pack, what fraction of

bezimeni [28]

Answer:

for the fraction its 2,5 for the percentage its 40%

3 0

3 years ago

Marty's cat weighs 10.4 pounds. this is 24.4 pounds less than the weight of marty's dog. how much does marty's dog weigh?

Aleksandr-060686 [28]

I hope this helps you

dogs-24,4=10,4

dog=34,8

3 0

4 years ago

Expanded notation with exponents for the number 354

Aleks04 [339]

I'm assuming you're looking for 3.54x10^2

8 0

4 years ago

24. 9 more than the quotient of -36 and 4.

alisha [4.7K]

Answer:

Step-by-step explanation:

9 more than the quotient of -36 and 4.

the quotient of -36 and 4 → -36 : 4 = -9

9 more → + 9

9 more than the quotient of -36 and 4 → -36 : 4 + 9 = -9 + 9 = 0

7 0

4 years ago

A broker has calculated the expected values of two different financial instruments X and Y. Suppose that E(x)= $100, E(y)=$90 SD

Sveta_85 [38]

Expectation is linear, meaning

E(a X + b Y) = E(a X) + E(b Y)

= a E(X) + b E(Y)

If X = 1 and Y = 0, we see that the expectation of a constant, E(a), is equal to the constant, a.

Use this property to compute the expectations:

E(X + 10) = E(X) + E(10) = $110

E(5Y) = 5 E(Y) = $450

E(X + Y) = E(X) + E(Y) = $190

Variance has a similar property:

V(a X + b Y) = V(a X) + V(b Y) + Cov(X, Y)

= a^2 V(X) + b^2 V(Y) + Cov(X, Y)

where "Cov" denotes covariance, defined by

E[(X - E(X))(Y - E(Y))] = E(X Y) - E(X) E(Y)

Without knowing the expectation of X Y, we can't determine the covariance and thus variance of the expression a X + b Y.

However, if X and Y are independent, then E(X Y) = E(X) E(Y), which makes the covariance vanish, so that

V(a X + b Y) = a^2 V(X) + b^2 V(Y)

and this is the assumption we have to make to find the standard deviations (which is the square root of the variance).

Also, variance is defined as

V(X) = E[(X - E(X))^2] = E(X^2) - E(X)^2

and it follows from this that, if X is a constant, say a, then

V(a) = E(a^2) - E(a)^2 = a^2 - a^2 = 0

Use this property, and the assumption of independence, to compute the variances, and hence the standard deviations:

V(X + 10) = V(X) ==> SD(X + 10) = SD(X) = $90

V(5Y) = 5^2 V(Y) = 25 V(Y) ==> SD(5Y) = 5 SD(Y) = $40

V(X + Y) = V(X) + V(Y) ==> SD(X + Y) = √[SD(X)^2 + SD(Y)^2] = √8164 ≈ $90.35

8 0

4 years ago