Simplify: 2(5+3x)+(x+10

Mathematics

2 answers:

Volgvan3 years ago

7 0

20+7x Use Photomath

melomori [17]3 years ago

4 0

Answer:

7x + 20

Step-by-step explanation:

This is as simplified as it's gonna get.

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QUESTION 9 of 10: You are considering leasing a store site that has 1,800 square feet. The landlord is asking for rent of $55 pe

algol [13]

B) $8,250

explanation: since you have a total of 1800 sq ft and it’s $55 dollars per sq ft for the yr, you would start by finding how much it would cost for a year by taking $55 x 1800 sq ft= $99,000 then since you are trying to find the rent for a month you would take the yr value ($99,000) and divide it by 12 since there are 12 months in a yr
99,000/12 = $8,250

6 0

4 years ago

Consider the table below that represents a quadratic function.

zlopas [31]

It would be -1/2 because the formula to find slope (rate of change) is (y2-y1)/(x2-x1) and in this case it would be (4.5-2)/(-3--2) which simplifies to (2.5)/(-5) which is -1/2

6 0

3 years ago

A study investigating the relationship between age and annual medical expenses randomly samples 400 individuals in a city. It is

ICE Princess25 [194]

Answer:

The probability is 0.789

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