1 / 7

Continuous Random Variables

Continuous Random Variables. Discrete Vs. Continuous. Discrete. Continuous. Values of X are countable. Distribution is a table or histogram. Values of X can take on ANY value within an interval. Are usually a measurement. Distribution is a density curve. Density Curve Properties.

robbin
Download Presentation

Continuous Random Variables

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Continuous Random Variables

  2. Discrete Vs. Continuous Discrete Continuous • Values of X are countable. • Distribution is a table or histogram. • Values of X can take on ANY value within an interval. • Are usually a measurement. • Distribution is a density curve.

  3. Density Curve Properties • Always on or above the x-axis • Total area underneath the curve equals 1 • The normal distribution (bell-shaped curve) is an example of a density curve.

  4. The lifetime of a certain battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last less than 220 hours? Write the probability statement Draw & shade the curve P(X < 220) = .9087 NORMCDF(-9999, 220, 200,15)

  5. The lifetime of a certain type of battery is normally distributed with a mean of 200 hours and a standard deviation of 15 hours. What proportion of these batteries can be expected to last more than 220 hours? P(X>220) = .0912 NORMCDF(220,9999, 200,15)

  6. NOTE • In continuous distributions: P(X = some constant #) = 0 WHY?? ** Because the area of a line segment is zero! ** Is this true in a discrete distribution??

  7. The heights of the female students at SLHS are normally distributed with a mean of 65 inches. What is the standard deviation of this distribution if 18.5% of the female students are shorter than 63 inches? What is the z-score for the 63? P(X < 63) = .185 -0.9 63

More Related