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The price of milk increased from $2 to $2.50. What is the percent of change for the price of milk?

Alina [70]

25.00%

Or

25c

Have a Merry Christmas!

5 0

3 years ago

(x-3)(2x+1) Can someone help me on this please

a_sh-v [17]

2x^2-5x-3

This is the answer I believe, I apologize if it’s incorrect

6 0

3 years ago

a packe of cards conatins 4 red and 5 black cards. a hand of 5 cards is drawn without replacment. What is the proablity of all f

Vladimir79 [104]

Answer: Our required probability is 0.3387.

Step-by-step explanation:

Since we have given that

Number of red cards = 4

Number of black cards = 5

Number of cards drawn = 5

We need to find the probability of getting exactly three black cards.

Probability of getting a black card = $\dfrac{5}{9}$

Probability of getting a red card = $\dfrac{4}{9}$

So, using "Binomial distribution", let X be the number of black cards:

$P(X=3)=^5C_3(\dfrac{5}{9})^3(\dfrac{4}{9})^2\\\\P(X=3)=0.3387$

Hence, our required probability is 0.3387.

5 0

3 years ago

(3x/2)^4 any answers

Anika [276]

$\bf \left( \cfrac{3x}{2} \right)^4\implies \left( \cfrac{(3x)^4}{2^4} \right)\implies \left( \cfrac{3^4x^4}{2^4} \right)\implies \cfrac{81x^4}{16}$

6 0

3 years ago

Read 2 more answers

it is known that the population proton of utha residnet that are members of the church of jesus christ 0l6 suppose a random samp

Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$