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3 years ago

Show how to make one addend the next tens number. 22+49=?

1 answer:

3 0

<span>The one addend technique is the act of breaking up numbers to make even tens. 22+49 can be broken up into 21+49+1 and then added to make 21+50 and then these numbers can be more easily added to make 71.</span>

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juin [17]

Answer:

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Step-by-step explanation:

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2 years ago

ILL MAKE BRAINLY??!!!?!!!!!

Leno4ka [110]

Answer:

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Step-by-step explanation:

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3 years ago

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makkiz [27]

Answer:

The answer is the third equation. A = 250*(1 +0.016)^(0.75)

Step-by-step explanation:

Since Javier deposited $250 into an account with annual interest rate, then as the years passes his account will grow in the manner shown below:

account(0) = 250

account(1) = account(0)*(1 + 1.6/100) = account(0)*(1 + 0.016) = account(0)*1.016

account(2) = account(1)*1.016 = account(0)*1.016*1.016 = account(0)*(1.016)²

account(3) = account(2)*1.016 = account(0)*(1.016)²*1.016 = account(0)*(1.016)³

account(n) = account(0)*(1.016)^n

Where n is the number of years, account(0) is the initial amount. In this case only 9 months have passed, so we need to convert this value to years, dividing it by 12, which is 9/12 = 0.75. The initial amount was 250, so the equation is:

A = 250*(1.016)^(0.75)

The answer is the third equation.

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3 years ago

Read 2 more answers

Explain why the commutative property does not work for subtraction or division

nirvana33 [79]

Answer:The reason there is no commutative property for subtraction or division is because order matters when performing these operations.

Step-by-step explanation:

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3 years ago

The average Act score follows a normal distribution, with a mean of 21.1 and a standard deviation of 5.1. What is the probabilit

ohaa [14]

Answer:

0.43% probability that the mean IQ score of 50 randomly selected people will be more than 23

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 normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, 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 $s = \frac{\sigma}{\sqrt{n}}$ .