I need help please.

Mathematics

1 answer:

Virty [35]4 years ago

6 0

You just need to translate the sentences into formulas: let x be the number, we have

The difference of a number and 7 means $x-7$
Twice that difference means $2(x-7)=2x-14$

So, the left hand side of our equation is 2x-14. Similarly, we have

The sum of the number and 9 means $x+9$
Three times that sum means $3(x+9)=3x+27$

So, the right hand side of our equation is 3x+27. We can set and solve the equation

$2x-14=3x+27 \iff -14-27=3x-2x \iff -41=x$

So, the solution is -41.

You might be interested in

What pattern do you notice

Lemur [1.5K]

Everything is divided by 2

3 0

4 years ago

Read 2 more answers

I can’t find the area

evablogger [386]

Divide it into chunks of area you can find. One way to divide it is
.. a rectangle 2 mi x 5 mi at upper left.
.. a rectangle 8 mi x 6 mi down the middle
.. a rectangle 3 mi x 4 mi at lower right
.. a triangle 5 mi x 6 mi at lower left

Then the sum of areas is
.. (2 mi)*(5 mi) +(8 mi)*(6 mi) +(3 mi)*(4 mi) + (1/2)*(5 mi)*(6 mi)
.. = 10 mi^2 +48 mi^2 +12 mi^2 +15 mi^2
.. = 85 mi^2

4 0

3 years ago

2. The Hereford Cattle Society says that the mean weight of a one-year-old Hereford bull is 1135 pounds, with a standard deviati

Andrews [41]

Answer:

16.35% probability their combined weight exceeds 46000 pounds.

Step-by-step explanation:

To solve this question, we have 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 random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$