I need some tips and examples for subtracting integers. Appreciated!

Mathematics

2 answers:

Tcecarenko [31]3 years ago

5 0

one tip:

Example: 4 - (-3)

it instantly becomes positive because the negatives are close to each other as shown.

hope that helps :)

gavmur [86]3 years ago

5 0

Since an integer is any whole (not fractional) number on the number line, all you have to do is move to the left however many units you're subtracting by from the point given. Say the problem is 3 - 7. This means we start at 3, and move to the left 7 units, which lands us at -4. However, if we had a problem like 12 - (- 2), the two negatives would cancel out, meaning we will move to the right 2 units on the number line, or 12 + 2, which is 14. Some other examples are:

-12 - 4, (you should get -16)

3 - 8, ( you should get -5)

16 - (- 3), ( you should get 19)

I hope these tips helped you out! I know that when I first had to subtract integers, using a number line really helped me out. Eventually, it'll just be a natural thing. :D

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A survey was conducted that asked 1003 people how many books they had read in the past year. Results indicated that x overbar eq

Sergio [31]

Answer:

The 99% confidence interval would be given (11.448;14.152).

Step-by-step explanation:

1) Important concepts and notation

A confidence interval for a mean "gives us a range of plausible values for the population mean. If a confidence interval does not include a particular value, we can say that it is not likely that the particular value is the true population mean"

$s=16.6$ represent the sample deviation

$\bar X=12.8$ represent the sample mean

n =1003 is the sample size selected

Confidence =99% or 0.99

$\alpha=1-0.99=0.01$ represent the significance level.

2) Solution to the problem

The confidence interval for the mean would be given by this formula

$\bar X \pm z_{\alpha/2} \frac{s}{\sqrt{n}}$

We can use a z quantile instead of t since the sample size is large enough.

For the 99% confidence interval the value of $\alpha=1-0.99=0.01$ and $\alpha/2=0.005$ , with that value we can find the quantile required for the interval in the normal standard distribution.