Continuous Random Variables Flashcards

1
Q

What are two characteristics of continuous random variables?

A
  1. May assume any numerical value in one or more intervals

2. Use a continuous probability distribution to assign probabilities to intervals of values

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2
Q

If the probability of x will be in a specific interval of numbers is the area under the curve of what symbol that corresponds to the interval?

A

f(x)

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3
Q

What are properties of continuous probability distributions ?

A
  1. f(x) > or equal to 0 for al x
  2. The total area under the f(x) curve is equal to 1

Essential point: the area under a continuous probability distribution is a probability

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4
Q

How do you symbolize the probability that x could take any value between the range of a to b in a continuous distribution?

A

P(a

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5
Q

The three shapes that can be made in a continuous distribution is what?

A
  1. Rectangular. The uniform distribution
  2. Symmetrical and bell shaped- the normal distribution
  3. Skewed left or right
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6
Q

The uniform distribution (rectangle) characteristics is:

A
  1. The probabilities are the same for all possible outcomes
  2. Symmetrical and area under the distribution is = 1
  3. The mean and the median are the same

û= a + b / 2

Height= area/width or 1/b-a

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7
Q

What are the characteristics of the normal probability distribution?

A

The normal distribution mean is in the middle
All central tendency’s are equal

Area under total curve is 1
Area under half the curve is .5

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8
Q

The area in a normal distribution that is one SD from the mean is what percentage of people

A

68.4 or 34.2 twice

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9
Q

The area in a normal distribution that is two SD from the mean is what percentage of people

A

27.1 % or 13.55% each side

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10
Q

The area in a normal distribution that is three SD from the mean is what percentage of people

A

4.2% or 2.1% each

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11
Q

What is the formula for Z?

A

Z= x-u/SD

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12
Q

What does the symbol lamda mean and when do you use it?

A

Lamda means a number of events that can occur per given interval

In exponential distribution

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