All categories

3 years ago

19 - 5 (2m - 3) + 9m = 36

Mathematics

1 answer:

sergij07 [2.7K]3 years ago

6 0

Answer:

m = -2

Step-by-step explanation:

For this problem, we will simply solve the equation for m.

19 - 5 ( 2m - 3 ) + 9m = 36

19 - 10m + 15 + 9m = 36

34 - m = 36

-m = 2

m = -2

Hence, for this equation to be true, m must equal negative 2.

Cheers.

You might be interested in

Plz help on the 6 problems

Leokris [45]

1.) 9
2.)7
3.)106
4.)13
5.)192
6.)11

5 0

3 years ago

A storage unit is cubical in shape. Each

Triss [41]

WHOA I’m sorry try searching it up because this looks really hard. Yea I don’t know

5 0

2 years ago

Fred wants to put a carpet in this room. The carpet costs $15.00 a square yard, how much would it cost for a 3 ft by 6 feet by 9

Minchanka [31]

Solution :

Cost of carpeting per square yard = $ 15.00

1 yard = 3 feet

∴ 1 feet = $\frac{1}{3}$ yard

So,

Therefore, area of 3 ft by 6 ft is = $3 \times \frac{1}{3} \times 6 \times \frac{1}{3}$

= 1 x 2

= 2 square yard

Therefore, cost of carpeting 2 square yard = 2 x 15

= $ 30

1 yard = 3 feet

∴ 1 feet = $\frac{1}{3}$ yard

So,

Therefore, area of 9 ft by 12 ft is = $9 \times \frac{1}{3} \times 12 \times \frac{1}{3}$

= 3 x 4

= 12 square yard

Therefore, cost of carpeting 2 square yard = 12 x 15

= $ 180

3 0

2 years ago

The cost to produce a batch of granola bars is approximately Normally distributed with a mean of $7.19 and a standard deviation

Bumek [7]

Answer:

0.7780

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .