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mixas84 [53]
2 years ago
15

Explain to me how it s possible for 1+1=3

Mathematics
2 answers:
stich3 [128]2 years ago
5 0
It does it =2
—————————
Oksana_A [137]2 years ago
3 0

Answer:

1+1≠3 because the sum of 1+1 is only 2 not 3.

Step-by-step explanation:

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Answer:

D. 29

Step-by-step explanation:

180 - 151 = 29

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3 years ago
How many times does the diameter go around a circle?
marissa [1.9K]

Answer:

The circumference of a circle is approximately three times its diameter. If you divide the circumference by its diameter, the constant ratio is called Pi, which is an irrational number shown with this symbol: For example, the circle below has a radius of 4.5 inches.

Step-by-step explanation:

Hope this helps!

Brain-List?

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3 years ago
Find the slope of the line passing through the 2 points (-7,8), (-4,3
jeyben [28]

Answer:

5/-3

Step-by-step explanation:

Slope = (y2 - y1)/(x2 - x1)

m = (8 - 3)/(-7 + 4)

m = 5/-3

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2 years ago
Suppose the weights of Farmer Carl's potatoes are normally distributed with a mean of 8.0 ounces and a standard deviation of 1.1
svet-max [94.6K]

Answer:

a) 0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

b) 0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

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 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.

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 8.0 ounces and a standard deviation of 1.1 ounces.

This means that \mu = 8, \sigma = 1.1

(a) If 5 potatoes are randomly selected, find the probability that the mean weight is less than 9.3 ounces?

n = 5 means that s = \frac{1.1}{\sqrt{5}} = 0.4919

This probability is the pvalue of Z when X = 9.3. So

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

By the Central Limit Theorem

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

Z = \frac{9.3 - 8}{0.4919}

Z = 2.64

Z = 2.64 has a pvalue of 0.9959

0.9959 = 99.59% probability that the mean weight is less than 9.3 ounces

(b) If 6 potatoes are randomly selected, find the probability that the mean weight is more than 9.0 ounces?

n = 6 means that s = \frac{1.1}{\sqrt{6}} = 0.4491

This probability is 1 subtracted by the pvalue of Z when X = 9. So

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

Z = \frac{9 - 8}{0.4491}

Z = 2.23

Z = 2.23 has a pvalue of 0.9871

1 - 0.9871 = 0.0129

0.0129 = 1.29% probability that the mean weight is more than 9.0 ounces

8 0
3 years ago
Patty went to a dinner celebrating the wedding anniversary of her aunt and uncle. She asked her aunt how long they’ve been marri
bija089 [108]

Answer:

hello and 1900

Step-by-step explanation:

kbj

7 0
2 years ago
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