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dimulka [17.4K]
3 years ago
9

If it takes 1 3/4 m of cloth to make a dress. How many dresses can be made from 10 1/2 m of cloth?

Mathematics
1 answer:
Amanda [17]3 years ago
7 0

Answer:

6

Step-by-step explanation:

1¾ can go into 10½ 6 times

just divide them

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Ann deposits 20% of her earnings each week into her savings account. if she deposited $17 this week, how much did she earn
nika2105 [10]

earnings * 20 percent = 17

earnings * .2 = 17

divide by .2 on each side

earnings = 17/.2

earnings = $85.00

7 0
3 years ago
What is the answer of these, how do you do these
Charra [1.4K]
1 is perpendicular bc it's the opposite reciprocal so Basically it's the original fraction upside down. 2 is parallel bc both fractions have the same slope but one is negative
3 0
3 years ago
What is the area of the following figure?
Snowcat [4.5K]

Answer:

16.56‬

Step-by-step explanation:

The area of the square is 2 × 2

The area of the circle is-

A=πr²

A=3.14 × 2²

A=3.14 × 4

A=12.56

You don't need to divide it by half because there are two half circles so it would be a whole circle

12.56 + 4 = 16.56

Sorry if it is wrong

7 0
3 years ago
Read 2 more answers
A triangle has an area of 55 cm² and a base of 10 cm². What is the height? please help!!!!!!!!!!
AlekseyPX

Answer:

11cm2

Step-by-step explanation:

11cm2x10cm2/2 = 55cm2

3 0
3 years ago
Life Expectancies In a study of the life expectancy of people in a certain geographic region, the mean age at death was years an
Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

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.

We have:

Mean \mu, standard deviation \sigma.

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

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

Find the probability that the mean life expectancy will be less than years.

The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

8 0
2 years ago
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