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2 years ago

Order from least to greatest. 2.34, 2 3/4 , 9/4

Mathematics

2 answers:

gladu [14]2 years ago

6 0

B) 2 3/4 , 2.34, 9/4 hope this helps

tankabanditka [31]2 years ago

6 0

D. 9/4= 2.25
2.34
2 3/4 = 2.75

the easiest way to determine the order is to simplify the fractions into decimals

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What is the value of x ?enter your answer, as a decimal, in the box

VladimirAG [237]

Answer:

Final answer is $x=125.45$

Step-by-step explanation:

given that AB is parallel to NP

then ratio of corresponding segments must be equal

$\frac{MA}{AN}=\frac{MB}{BP}$

$\frac{MN-AN}{AN}=\frac{MB}{BP}$

$\frac{80.5-35}{35}=\frac{x}{96.5}$

$\frac{45.5}{35}=\frac{x}{96.5}$

Cross multiply

$35x=45.5\cdot96.5$

$35x=4390.75$

$x=\frac{4390.75}{35}$

$x=125.45$

Hence final answer is $x=125.45$

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3 years ago

Through: (4,-4), slope= 1/4

liq [111]

Answer:

(0,-3) I think

Step-by-step explanation:

The way I learned it 1/4 is the rise over run. so you are at your point and you go up one unit and then left or right 4 units.

8 0

3 years ago

Read 2 more answers

19. A sample of 50 retirees is drawn at random from a normal population whose mean age and standard deviation are 75 and 6 years

Juliette [100K]

Answer:

a) Approximately normal.

b) The mean is 75 years and the standard deviation is 0.8485 years.

c) 0.9909 = 99.09% probability that the mean age exceeds 73 years

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 $s = \frac{\sigma}{\sqrt{n}}$ .