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Jobisdone [24]
3 years ago
5

Find the factored form of 13x+x^2=0

Mathematics
1 answer:
ASHA 777 [7]3 years ago
8 0

Change it into the form

ax^2 + bx + c = 0

x^2 + 13x + 0 = 0

This equation has a common factor, x. Factorise it out.

<h2>x (x + 13) = 0</h2>
You might be interested in
URGENT!!!! WILL GIVE BRAINLIEST TO FIRST RIGHT ANSWER!!!!!!
Zepler [3.9K]

geometric sequence

\tt U_n=ar^{n-1}

a = 6 = first term

r = ratio = \tt \dfrac{9}{6}

the 6th term (n=6)

\tt U_6=6\times (\dfrac{9}{6})^{6-1}\\\\U_6=6\times \dfrac{9}{6}^5\\\\U_6=\dfrac{9^5}{6^4}=45.5625\rightarrow rounded~to nearest~thousandth=45.563

4 0
2 years ago
At a new exhibit in the Museum of Science, people are asked to choose between 94 or 220 random draws from a machine. The machine
Tresset [83]

Answer:

0.0869 = 8.69% probability of getting more than 61% green balls.

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 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}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

The machine is known to have 99 green balls and 78 red balls.

This means that p = \frac{99}{99+78} = 0.5593

Mean and standard deviation:

\mu = p = 0.5593

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.5593*0.4407}{99+78}} = 0.0373

a. Calculate the probability of getting more than 61% green balls.

This is 1 subtracted by the pvalue of Z when X = 0.61. So

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

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{0.61 - 0.5593}{0.0373}

Z = 1.36

Z = 1.36 has a pvalue of 0.9131

1 - 0.9131 = 0.0869

0.0869 = 8.69% probability of getting more than 61% green balls.

8 0
3 years ago
HELP MEEEE I NEED AN ANSWER ​
My name is Ann [436]
I believe b and c don’t have a solution
4 0
3 years ago
What Are the values of x and y?
dem82 [27]

Answer:

y = 72.5

x = 35.

Step-by-step explanation:

First Off, Let's Divide the question.

<em><u>Let's Find the variable y : </u></em>

<em><u /></em>

there are 2 y(s), so it is 2y.

equation:   2y +35   =180.

I put 180 because A straight Line is always 180.

2y+35=180

<u><em>1. Subtract both sides. </em></u>

2y =  145

y = 72.5

<u><em>Next,Find x </em></u>

So y + y + x = 180.

We already know y, which is<u> 72.5</u>

72.5 +72.5 + x = 180

72.5 +72.5

x + 145 = 180

x =  35.

Hope This Helps!

8 0
3 years ago
A square poster has a side length of 26 in. Drawn on the poster are four identical triangles. Each triangle has a base of 8 in.
Firdavs [7]
To find the probability of landing on a triangle, you will want find the combined areas of the triangles and the total area of the square target.

Divide the area of the combined areas and the total area to find the probability of landing on a triangle.

A = 1/2bh
      1/2 x 8 x 8
A = 32 square inches
32 x 4
128 square inches (areas of triangles)

A = bh
     26 x 26
A = 676 square inches

128/676 = 0.189

There is an approximate probability of 0.19 of hitting a triangle.
6 0
3 years ago
Read 2 more answers
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