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tiny-mole [99]
2 years ago
6

Find the simplified product :

Mathematics
2 answers:
Nataliya [291]2 years ago
7 0

Answer:

Edge 2021

Step-by-step explanation:

2nd one is C, 3x^4

Molodets [167]2 years ago
3 0
The last one 6x the power of 4
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A baker bakes 50 muffins. 1/5 of the muffins are chocolate chip. 1/2 of the muffins are blueberry. The rest are cinnamon. How ma
vitfil [10]

Answer:

15 muffins are cinnamon.

Step-by-step explanation:

Given that:

Number of muffins baked = 50 muffins

Chocolate chip muffins = 1/5 of 50 = \frac{1}{5}*50

Chocolate chip muffins = 10 muffins

Blueberry muffins = 1/2 of 50 = \frac{1}{2}*50

Blueberry muffins = 25

Cinnamon muffins = Muffins baked - chocolate chip muffins - blueberry muffins

Cinnamon muffins = 50 - 10 - 25

Cinnamon muffins = 50 - 35 = 15

Hence,

15 muffins are cinnamon.

5 0
3 years ago
What is 3/1,000 as a decimal
Katen [24]

Answer: 3/1000 as a decimal is 0.003.

Explanation;

3/10 = 0.3

0.3/10 = 0.03

0.03/10 = 0.003

3 0
2 years ago
Read 2 more answers
Can you please explain to me how I would solve this problem? Can you please explain/and show all the steps?
Lena [83]
22 = z + (-9) Switch the sides
z = 22 - (-9) Solve
z = 31 So, z = 31
7 0
3 years ago
Which point would be reflected across the y-axis to (-3,-9)
OlgaM077 [116]

Answer:

b

Step-by-step explanation:

when an reflected across the y axis only the x value changes and it changes negatively

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
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