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2 years ago

Which perfect square lies between the whole numbers 40 and 50?

Mathematics

2 answers:

Neko [114]2 years ago

5 0

Answer:

The perfect square number between 40 and 50 is 49 which is a square of 7.

iragen [17]2 years ago

5 0

Answer: the perfect square that lies between 40 and 50 is 49

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The statement ‘5 is added to 9 times a certain number n and the result is 32’ is represented by? *

salantis [7]

Answer:

5+(9×n)=32

n=3

.:.n is represented by 3

3 0

2 years ago

The sum of two numbers is negative fifteen, and one number is five less than the other. Using the variables m and n to represent

Likurg_2 [28]

We need to use the variables m and n to represent both numbers.

Their sum must equal -15. Therefore, we can write the next equation:

m + n = -15

If one number is five less than the other, we need to choose one variable and then we can write it in terms of the other variable. Then:

n = m-5

To find the value for each number, we can replace the n equation on the first equation:

m + n = -15

m + (m-5)= -15

Then:

m + m - 5 = -15

2m -5 = -15

Solve the equation for m:

Add both sides 5 units:

2m - 5 +5 = -15+5

2m = -10

Divide both sides by 2:

2m/2 = -10/2

m = -5

Finally, replace the m value on the first equation:

m + n = -15

-5 + n = -15

Then, solve the equation for n:

Add both sides by 5:

-5+5 + n = -15 +5

n = -10

Hence, both numbers are m=-5 and n= -10.

The equations separated by a comma are m + n = -15,n = m-5.

The numbers separated by a comma are -5,-10.

6 0

1 year ago

9. Gold miners in Alaska have found, on average, 12 ounces of gold per 1000 tons of dirt excavated with a standard deviation of

netineya [11]

Answer:

9.18% probability the miners find more than 16 ounces of gold in the next 1000 tons of dirt excavated

Step-by-step explanation:

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.

In this problem, we have that:

$\mu = 12, \sigma = 3$