Does 5mm, 1mm, 10mm make a triangle

Mathematics

1 answer:

pogonyaev3 years ago

6 0

Answer:

Step-by-step explanation:

No. Each side must be less than the sum of the remaining two sides.

10 ≮ 5+1

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Select the solutions to the following inequality: |x| < 7

Rasek [7]

|x| < 7
means x < 7 and x > -7

answer is -7 < x < 7

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3 years ago

Solve the equation 18=n-18 n=_____

Maksim231197 [3]

Answer:

Step-by-step explanation:

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3 years ago

Prove the statement holds for all positive integers: 2 + 4 + 6 + ... + 2n = n² + n

crimeas [40]

Proving a relation for all natural numbers involves proving it for n = 1 and showing that it holds for n + 1 if it is assumed that it is true for any n.

The relation 2+4+6+...+2n = n^2+n has to be proved.

If n = 1, the right hand side is equal to 2*1 = 2 and the left hand side is equal to 1^1 + 1 = 1 + 1 = 2

Assume that the relation holds for any value of n.

2 + 4 + 6 + ... + 2n + 2(n+1) = n^2 + n + 2(n + 1)

= n^2 + n + 2n + 2

= n^2 + 2n + 1 + n + 1

= (n + 1)^2 + (n + 1)

This shows that the given relation is true for n = 1 and if it is assumed to be true for n it is also true for n + 1.

By mathematical induction the relation is true for any value of n.

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3 years ago

Consider the following hypothesis test: H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 There are two independent samples taken from the two pop

nlexa [21]

Answer:

The value of the test statistic is $z = 1.78$

Step-by-step explanation:

Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.

Central Limit Theorem

The Central Limit Theorem establishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Subtraction between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

Sample 1:

$\mu_1 = 110, s_1 = \frac{7.2}{\sqrt{81}} = 0.8$