Factor the following trinomials . x2 + 2x - 35 x2 - x - 12

2 answers:

6 0

X2-2x-35=0x2-7x+5x-35=0x(x-7)+5(x-7)=0(x-7)(x+5)=0x-7=0 or x+5=0x=7 or x=-5 Check: x=7 ,LHS = 49-14-35 =0 =RHS x=-5, LHS = 25+10-35 =0=RHSAns: x=7 or x=-5

x2−x−12=0

NNADVOKAT [17]3 years ago

5 0

(x + 7) • (x - 5)= Answerx^2+2x-35
What multiplies to -35 and adds up to 3?
-5+7=2
-5*7=-35
NEXT
 x^2 - 5x + 7x - 35

Add up the first 2 terms, pulling out like factors :
x • (x-5)

Add up the last 2 terms, pulling out common factors :
7 • (x-5)
Add up the four terms of step 4 :
(x+7) • (x-5)

___________________________________________________________

(x + 3) • (x - 4)=Answer
x^2-x-12
What multiplies up to -12 and adds to -1?
-4+3=-1
-4*3=-12

x^2 - 4x + 3x - 12

Add up the first 2 terms, pulling out like factors :
x • (x-4)

Add up the last 2 terms, pulling out common factors :
3 • (x-4)
Add up the four terms
(x+3) • (x-4)

You might be interested in

Select the expression that makes the equation true.

svetoff [14.1K]

Answer:

a.) -18 x 10^6

Step-by-step explanation:

multiply 9 x-2

add exponents 9 and -3

4 0

3 years ago

Help please 6+6x4+8.................

Natasha_Volkova [10]

,12x12=144.................

6 0

3 years ago

Read 2 more answers

The scores on the GMAT entrance exam at an MBA program in the Central Valley of California are normally distributed with a mean

Kaylis [27]

Answer:

58.32% probability that a randomly selected application will report a GMAT score of less than 600

93.51% probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600

98.38% probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600

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