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jolli1 [7]
3 years ago
5

Compare the decimals 16.30 and 16.3

Mathematics
1 answer:
pshichka [43]3 years ago
8 0
16.30 and 16.3 equal. If you ever have a problem like that then you just add on a zero.

Example:
19.4500 = 19.45 Just add two zeros on the end
19.45 + two zeros = 1.4500
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Can y’all help me me on question 2?! Have a good day!
AfilCa [17]

Answer:

9

Step-by-step explanation:

The formula to get the area of a triangle is A=\frac{(b)(h)}{2} so all you have to do is work backwards. 18x2=36. 36/4=9.

6 0
3 years ago
Write the equation that shows 40 is 8 times more than 5
Vlad1618 [11]

Answer:

8X5=40

Step-by-step explanation:

3 0
3 years ago
On your family trip, you used 14 gallons of gas.
Alecsey [184]

Answer:

19

Step-by-step explanation:

To get the total miles you drove first, you need to do 84947 (number after the trip) - 84679 (the number before it. You get 268.

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4 0
4 years ago
Parts being manufactured at a plant are supposed to weigh 65 grams. Suppose the distribution of weights has a Normal distributio
andrew-mc [135]

Answer:

0.64%.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, 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 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.

Mean of 75 grams and a standard deviation of 22 grams.

This means that \mu = 75, \sigma = 22

Sample of 144:

This means that n = 144, s = \frac{22}{\sqrt{144}} = 1.8333

More than 80 or less than 70:

Both are the same distance from the mean, so we find one probability and multiply by 2.

The probability that it is less than 70 is the pvalue of Z when X = 70. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{70 - 75}{1.8333}

Z = -2.73

Z = -2.73 has a pvalue of 0.0032

2*0.0032 = 0.0064.

0.0064*100% = 0.64%

The probability is 0.64%.

3 0
3 years ago
Drag the values into the boxes to classify each number as rational or irrational. picture below pls help quick.
larisa [96]

Answer:

Step-by-step explanation:

Rational numbers;

Numbers which can be written in the form of \frac{p}{q} or repeating decimal numbers are the rational numbers.

Examples : 1, 2, \frac{2}{3}

Irrational numbers:

Numbers which can't be written in he form of a fraction or non repeating decimal numbers are the Irrational number.

Example: \sqrt{8},\pi,\sqrt{\frac{8}{21} }

From the given numbers,

Rational numbers:  \frac{11}{3}, 6.25, 0.01045, \sqrt{\frac{16}{81} }, 0.424242....

Irrational numbers:  \sqrt{48}, \sqrt{\frac{3}{16} }

6 0
3 years ago
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