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In-s [12.5K]
2 years ago
5

Use the distributive property to write an equivalent expression of the following

Mathematics
2 answers:
Nina [5.8K]2 years ago
8 0

Answer:

2b+2c

35h+15m

4x+4y

3ac+bc

scoray [572]2 years ago
5 0

Answer:

Solution given:

2 ( b + c )=2b+2c

5 (7h + 3m)=35h+15m

4 (x+y)=4x+4y

c ( 3a + b )=3ac+bc

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You have 15 pennies in your pocket. Of those pennies, 3 are Canadian. Suppose you pick a penny out of your pocket at random. Fin
den301095 [7]
The best and most correct answer among the choices provided by your question is the fourth choice or letter D. The probability is 4/5.

<span>P ( canadian)= 3/15 = 1/5
On the other hand, P (not canadian) = 1 - 1/5 = 4/5</span>

I hope my answer has come to your help. Thank you for posting your question here in Brainly.
4 0
3 years ago
A sample size 25 is picked up at random from a population which is normally
Margarita [4]

Answer:

a) P(X < 99) = 0.2033.

b) P(98 < X < 100) = 0.4525

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 estabilishes 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.

Mean of 100 and variance of 36.

This means that \mu = 100, \sigma = \sqrt{36} = 6

Sample of 25:

This means that n = 25, s = \frac{6}{\sqrt{25}} = 1.2

(a) P(X<99)

This is the pvalue of Z when X = 99. So

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

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{99 - 100}{1.2}

Z = -0.83

Z = -0.83 has a pvalue of 0.2033. So

P(X < 99) = 0.2033.

b) P(98 < X < 100)

This is the pvalue of Z when X = 100 subtracted by the pvalue of Z when X = 98. So

X = 100

Z = \frac{X - \mu}{s}

Z = \frac{100 - 100}{1.2}

Z = 0

Z = 0 has a pvalue of 0.5

X = 98

Z = \frac{X - \mu}{s}

Z = \frac{98 - 100}{1.2}

Z = -1.67

Z = -1.67 has a pvalue of 0.0475

0.5 - 0.0475 = 0.4525

So

P(98 < X < 100) = 0.4525

6 0
2 years ago
What is this answer plz help
scZoUnD [109]

Answer:

y=-3/4

i think

6 0
2 years ago
On a family outing, Tyler bought 5 cups of hot cocoa and 4 pretzels for $18.40. Some of his family
elena55 [62]

Answer:

hindi ko po gits malay mo po sa iba mo po ma lalaman ang sagut

5 0
3 years ago
You go for a half day hike. In 44 hours, you hike 10
nataly862011 [7]
44 divided by 10 will give you the answer

6 0
3 years ago
Read 2 more answers
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