What is this expression 27-((7x3)

2 answers:

5 0

27-(7x3)

First you will need to solve the problem inside the parentheses, in this case the answer would be 21. After that, you will need to solve any other problems, in this case your problem would look like this:
27-21=
Subtract it and you'll get your answer; 6

Hatshy [7]3 years ago

4 0

27-(7x3)=6
27-21=6 Its 6 your welcome

You might be interested in

During summer, when the snow melts, the water level of the Yukon River increases. If the water level of the river increased by 4

Paul [167]

Answer:

Step-by-step explanation:

8 0

2 years ago

Prove the theorem (AB )^T= B^T. A^T

Lisa [10]

Answer:

$(AB)^T = B^T.A^T (Proved)$

Step-by-step explanation:

Given (AB )^T= B^T. A^T;

To prove this expression, we need to apply multiplication law, power law and division law of indices respectively, as shown below.

$(AB)^T = B^T.A^T\\\\Start, from \ Right \ hand \ side\\\\B^T.A^T = \frac{B^T.A^T}{A^T}.\frac{B^T.A^T}{B^T} (multiply \ through) \\\\ = \frac{A^{2T}.B^{2T}}{A^T.B^T} \\\\=\frac{(AB)^{2T}}{(AB)^T} \ \ (factor \ out \ the power)\\\\= (AB)^{2T-T} \ (apply \ division \ law \ of \ indices; \ \frac{x^a}{x^b} = x^{a-b})\\\\= (AB)^T \ (Proved)$

3 0

3 years ago

What is the result of subtracting the second equation from the first?

FrozenT [24]

Answer: well this is hard

Step-by-step explanation:

First of all you’re adding 7Y and you’re getting -8 and for subtracting you subtract 5why and you’re getting negative one so technically you’re getting different answers?

8 0

3 years ago

Is the confidence interval affected by the fact that the data appear to be from a population that is not normally distributed?

sp2606 [1]

Answer:

D. No, because the sample size is large enough.

Step-by-step explanation:

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

If the sample size is higher than 30, on this case the answer would be:

D. No, because the sample size is large enough.

And the reason is given by The Central Limit Theorem since states if the individual distribution is normal then the sampling distribution for the sample mean is also normal.

From the central limit theorem we know that the distribution for the sample mean $\bar X$ is given by: