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DanielleElmas [232]
3 years ago
14

Which pair of undefined terms is used to define a ray?

Mathematics
1 answer:
Zigmanuir [339]3 years ago
3 0

Answer:

A point and a line.

Further explanation:

Ray is part of the line with one endpoint. Ray is an endless straight path in one direction from a starting point, e.g., .

The arrow above the point shows the direction of the longitudinal beam. The length of the ray cannot be calculated.

Undefined terms are basic figure that is not defined in terms of other figures. The undefined terms (or primitive terms) in geometry are a point, line, and plane.

These key terms cannot be mathematically defined using other known words.

A point represents a location and has no dimension (size).  It is labeled with a capital letter and a dot.

A line is an infinite number of points extending in opposite directions that have only one dimension. It has one dimension. It is a straight path and no thickness.

A plane is a flat surface that contains many points and lines.  A plane extends infinitely in all four directions.  It is two-dimensional.  Three noncollinear points determine a plane, as there is exactly one plane that can go through these points.

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The answers to the questions are;

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Step-by-step explanation:

To solve the question, we note that

n = 58

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Here we have n·p = 17.4 and n·q = 40.6 both ≥ 5 that is the normal distribution can be used to estimate the probability

A) We are to use the binomial probability formula to find P(X)

Where x = 12, we have P(12) = ₅₈C₁₂×0.3¹²×0.7⁴⁶

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\frac{1}{\sigma\sqrt{2 \pi } } e^{\frac{-(x-\mu)^2}{2\sigma^2} }

where:

σ = Standard deviation = \sqrt{npq} = \sqrt{np(1-p)} = \sqrt{58*0.3*(1-0.3)} = 3.48999

μ = Sample mean = n·p = 58×0.3 =17.4

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C)  The probabilities differ by 3.55 ×10⁻² -  3.453 ×10⁻² =  9.7×10⁻⁴

D) The normal distribution be used to approximate this probability because     n·p and n·p·(n-p) ≥ 5

E)   f_i represents the area under the curve towards left of the ith data observed in a normally distributed population.

Therefore, the value of fi represents the expected proportion of observation less than or equal to the ith data value  

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