A portion of a line or Ray that extends from one point to another point is called what

Mathematics

2 answers:

madam [21]3 years ago

6 0

Answer:

line segment

Step-by-step explanation:

If a portion of a line has two endpoints (two little black dots on its end), then it is a line segment.

If it has one dot and an arrow, its a ray. This has an endpoint and goes on forever in the direction of the arrow.

Juli2301 [7.4K]3 years ago

5 0

Answer: line segment

Step-by-step explanation:

A line segment is a ray that extends from one point to another. Hope this helps!

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Solve the linear equation x + 4 + 3 + 72

elixir [45]

Answer:

x=17

Step-by-step explanation

4x+4=72

-4 -4

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/4 /4

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2 years ago

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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 $s = \frac{\sigma}{\sqrt{n}}$ .