Please please need help with this one having a hard time with it.

algol [13]

Hey There :)

This is because one is half of two. You could also multiply 2 * 0.5= 1, 0.5 represents $\frac{1}{2}$ and two is the whole number. This is how $\frac{1}{2}$ of two equals one.

Have A Brainly Day :)

8 0

3 years ago

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A recipe for 24 cookies calls for 4 tablespoons of sugar. If you make 40 cookies and use 5 tablespoons, will the cookies taste t

uranmaximum [27]

Answer:

Step-by-step explanation:

No, because they wouldn't contain the same amount of sugar per cookie

for the first recipe - 24 cookies with 6 tablespoons

thats 6/24 so 0.25 tablespoons of sugar per cookie

for the second recipe - 36 cookies with 10 tablespoons

thats 10/36 so 0.276 tablespoons per cookie

the cookies in the second recipe would be slightly sweeter than the cookies in the first

5 0

3 years ago

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Packages of mixed-colored socks contain 8 pairs of socks. In each package, there are 5 pairs of White socks. How many pairs of w

BabaBlast [244]

125 5 diced by 40 = 125

6 0

4 years ago

Suppose that a college determines the following distribution for X = number of courses taken by a full-time student this semeste

lidiya [134]

Answer:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$ In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$ And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).

Solution to the problem

For this case we have the following distribution given:

X 3 4 5 6

P(X) 0.07 0.4 0.25 0.28

We can calculate the mean with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$

In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$

And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

3 0

4 years ago

Write an expression for the calculation double 2 and then add 5

valina [46]

Answer:

Step-by-step explanation:

7 0

4 years ago

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