Simplify completely 5х^3 + 10х^2 + 15х / 5x pleasseeeee HURRRRYYY

Mathematics

1 answer:

devlian [24]4 years ago

3 0

Answer: 5x^{3} +x^{2} +3

Step-by-step explanation:

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What is 4000000000000000000000 to the 50 power?

Nesterboy [21]

4000000000000000000000^50 is the same thing. Ain't no mathematician wants to simplify that. Mathematicians are lazy. So you would leave it the way it is.

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4 years ago

The perimeter of the rectangle below is 42 inches. Find the value of X. Please help

nirvana33 [79]

Answer:

x = 4

Step-by-step explanation:

42 = 5x + 5x + ( x - 3 ) + ( x - 3 )

42 = 12x - 6

48 = 12x

x = 4

Perimeter is the length around the rectangle (or any other shape). For rectangles, it's found by adding the side lengths. In this case, it required algebra to solve for x.

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3 years ago

Read 2 more answers

Anas wants to build a one-sample z interval with 85% confidence to estimate what proportion of users will click an advertisement

klasskru [66]

Answer:

See below

Step-by-step explanation:

Check One Sample Z-Interval Conditions

Simple Random Sample? √

np≥10? √

n(1-p)≥10? √

One-Sample Z-Interval Information

Formula --> $CI=\hat{p}\pm z^*\biggr(\sqrt{\frac{\hat{p}(1-\hat{p})}{n}}\biggr)$
Sample Proportion --> $\hat{p}=\frac{54}{250}=0.216$
Critical Value --> $z^*=1.4395$ (for a 85% confidence level)
Sample Size --> $n=250$
Margin of Error (MOE) --> $\sqrt{\frac{\hat{p}(1-\hat{p})}{n}}$

Problem 1

As stated previously, Anas should use the critical value $z^*=1.4395$ to construct the 85% confidence interval

Problem 2

Given our formula for the margin of error (MOE), the value is $MOE=\sqrt{\frac{\hat{p}(1-\hat{p})}{n}}=\sqrt{\frac{0.216(1-0.216)}{250}}\approx0.026$

Problem 3

The 85% confidence interval would be $CI=\hat{p}\pm z^*\biggr(\sqrt{\frac{\hat{p}(1-\hat{p})}{n}}\biggr)=CI=0.216\pm 1.4395(0.026)\appro=\{0.1786,0.2534\}$ , which means that we are 85% confident that the true proportion of people that clicked on the advertisement is between 0.1786 (~45 people) and 0.2534 (~63 people)

Problem 4

Increasing the sample size to $n=500$ is going to decrease the margin of error because it is a closer representation of the population, but, alas, requires more time, energy, and resources to observe.