1 / 19

Random Error Theory

Random Error Theory. Introduction. From now on, we will assume that systematic errors have been eliminated This leaves random errors and possible blunders Random errors conform to the laws of probability. Probability.

olinda
Download Presentation

Random Error Theory

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. Random Error Theory

  2. Introduction • From now on, we will assume that systematic errors have been eliminated • This leaves random errors and possible blunders • Random errors conform to the laws of probability

  3. Probability • Defined as the ratio of the number of times an event should occur to the total number of possibilities • For example, tossing a “2” with a fair die will have a probability of 1/6 • When an event can occur in m ways and fail to occur in n ways …

  4. Probability - continued • Probability ranges from 0 to 1 • Sum of all probabilities for an event must be one • Compound events are two independent events that occur simultaneously • Their probability is the product of the independent probabilities of the events • The probability of tossing two 2’s in a row is (1/6)x(1/6) = 1/36

  5. What is probability that 2 red balls will be drawn when one ball is randomly selected from each box? Box 1: 1W, 2R, 3W, 4W; Box 2: 1R, 2R, 3W, 4W, 5W TR BOX 1 BOX 2 1 1 WHITE1 1 RED1 2 1 RED2 1 RED1 3 1 WHITE3 1 RED1 4 1 WHITE4 1 RED1 5 1 WHITE1 1 RED2 6 1 RED2 1 RED2 7 1 WHITE3 1 RED2 8 1 WHITE4 1 RED2 9 1 WHITE1 1 WHITE3 10 1 RED2 1 WHITE3 P( 2 REDS ) = 2/20 = 1/10 = 1/4 × 2/5 = 2 /20 = 1/10 TR BOX 1 BOX 2 11 1 WHITE3 1 WHITE3 12 1 WHITE4 1 WHITE3 13 1 WHITE1 1 WHITE4 14 1 RED2 1 WHITE4 15 1 WHITE3 1 WHITE4 16 1 WHITE4 1 WHITE4 17 1 WHITE1 1 WHITE5 18 1 RED2 1 WHITE5 19 1 WHITE3 1 WHITE5 20 1 WHITE4 1 WHITE5

  6. The following 5 cards are showing from a standard deck of cards. What is the probability that one or both of the next two cards are clubs (complete the flush)? Ace of clubs, 6 of clubs, 5 of spades, 10 of clubs, Jack of clubs Winning possibilities: Card 1 – club, card 2 – not club Card 1 – not club, card 2 club Card 1 – club, card 2 club Total = 0.3497

  7. Normal Distribution

  8. Normal Distribution • As n approaches infinity, the histograms will approach the normal distribution (AKA bell) curve

  9. Properties of the Normal Distribution • Area under the curve from -∞ to +∞ = 1 • Slope = 0 at x • Inflection points at ±σ from x

  10. Normal Distribution Function

  11. Standard Normal Distribution Function For a mean of zero (μ=0) and standard deviation of one (σ=1) See NORMDIST and NORMSINV spreadsheet functions or STATS program.

  12. Various Errors Standard Error (±σ) = 68.3% E50 = 0.6745 σ E95 = 1.960 σ (look at STATS and Excel functions)

  13. Example 3.2 50 seconds-readings are given. Find mean, standard deviation, and E95.

More Related