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4 years ago

-3 = 7 - BLANK pls tell me what blank is

Mathematics

2 answers:

liberstina [14]4 years ago

4 0

Answer:

Step-by-step explanation:

-3 = 7 - x

Add x to both sides

x -3 = 7 - x +x

x - 3 = 7

Now, add 3 to both sides

x - 3 + 3 = 7 + 3

x = 10

Radda [10]4 years ago

4 0

Answer:

$\boxed{10}$

Step-by-step explanation:

$-3=7- \sf BLANK$

$\sf Subtract \ 7 \ from \ sides.$

$-3-7=-7+7- \sf BLANK$

$-10=- \sf BLANK$

$\sf Multiply \ both \ sides \ by \ -1.$

$-10(-1)=(-1)- \sf BLANK$

$10= \sf BLANK$

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A student decided to use the points (.5, 20) and (3, 150) to make what she believed was a better regression equation. Her answer

Mamont248 [21]

Answer:

They can expect to make $524

Step-by-step explanation:

Lets solve the problem

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∵ The student decided to use the points (0.5, 20) and (3, 150)

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∵ x = 10

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5 0

4 years ago

Help me with this question

Alona [7]

Answer:

Step-by-step explanation:

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3 years ago

A researcher reports survey results by stating that the standard error of the mean is 25 the population standard deviation is 40

bezimeni [28]

Answer:

a) A sample of 256 was used in this survey.

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Step-by-step explanation:

This question is solved using the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .