Which property is illurstaed by this problem. (6.3x)y=6.3(xy)

Simplify the expression:<br> 4r2–2+6

slava [35]

Collect like terms:
4r^2 + (-2 + 6)

Simplify:
4r^2 + 4

DONE !!

6 0

3 years ago

On the coordinate plane below, figure 1 was transformed twice to form figure 2.

sdas [7]

Is there a photo or something?

6 0

3 years ago

If sin (A+B)=1 and tan (A-B)=1/sqroot 3<br><br> are acute angles. find out the value of A and B

Nataliya [291]

Answer:

A = 60° , B = 30°

Step-by-step explanation:

$sin(A+B ) = 1\\\\\ \ \ (A + B) \ = \ \ sin^{-1} 1\\\\A + B = 90^\circ --(1)\\\\ \ tan (A - B) = \frac{1}{\sqrt{3}}\\\\(A-B) = tan^{-1}\frac{1}{\sqrt3}}\\\\A - B = 30^\circ --(2)\\\\ (1) + (2) => 2A = 120^\circ\\$

$A = 60^\circ$

$from \ (1) \\A + B = 90^\circ\\60^\circ + B = 90^\circ\\B = 90^\circ - 60^\circ\\B = 30^\circ$

7 0

3 years ago

A company advertises two car tire models. The number of thousands of miles that the standard model tires last has a mean μ S =6

Lera25 [3.4K]

Answer: .123

Step-by-step explanation: use random variable e-s which will follow a normal distribution with a mean of 70-60=10 and SD= sq root of 25+49. P(e-s<0)=.123

5 0

3 years ago

Data from the Centers for Disease Control and Prevention indicate that weights of American adults in 2005 had a mean of 167 poun

sesenic [268]

Answer:

92.65% probability that the total weight in a random sample of 47 American adults exceeds 7500 pounds in 2005.

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