PPT-Normal Distribution

J C F Gauss Central Limit Theorem Symmetry around μ μ is the confluence of the mean median and mode of the data μ splits the data in half Pareto Principle 2080 Rule 20 of . 1 Second Normal Form 32 Third Normal Form 33 Functional Dependencies 4 FOURTH AND FIFTH NORMAL FORMS 41 Fourth Normal Form 411 Independence 412 Multivalued Dependencies 42 Fifth Normal Form 5 UNAVOI ABL E RE DUNDA NCIES 6 INTERRECORD REDUNDA NCY 7 CO 1. 4. Continuous Random Variables and Probability Distributions. 4-1 Continuous Random Variables. 4-2 Probability Distributions and Probability Density Functions. 4-3 Cumulative Distribution Functions. Reading: . Chapter 11, Sections 12-1 and 12-2 . of Applied Hydrology. 04/04/2006. 2. Probability. A measure of how likely an event will occur. A number expressing the ratio of favorable outcome to the all possible outcomes . History. Abraham de . Moivre. (1733) – consultant to . gamblers. . Pronunciation. .. Pierre Simon . Laplace – mathematician, astronomer, philosopher, determinist.. Carl Friedrich . Gauss – mathematician and astronomer.. Mat 271E. Yard. Doç. Dr. Tarkan Erdik. Probability Distributions. Uniform and Normal Distributions- Week 7. 1. Probability Distributions. 2. It has been observed that . certain functions . F(x). and . Mrs. Aldous, Mr. . Beetz. & Mr. Thauvette. DP SL Mathematics. Normal Distribution. You should be able to…. Describe the properties of a normal distribution with mean and standard deviation . A Brief Introduction. Normal (Gaussian) Distribution. Bell-shaped distribution with tendency for individuals to clump around the group median/mean. Used to model many biological phenomena. Many . estimators . State:. Express the problem in terms of the observed variable . x. .. Plan:. Draw a picture of the distribution and shade the area of interest under the curve.. Do:. Perform calculations.. Standardize. Parameter & Statistic. Parameter. Summary measure about population. Sample Statistic. Summary measure about sample. P. . in. . P. opulation. . &. . P. arameter. S. . in. . S. ample. . @UWE_JT9. @. dave_lush. Scientific . Practice. The Binomial Distribution. This distribution can be seen when the outcomes have discrete values…. eg. rolling dice. Assumptions…. Fixed . number of . . and Exponential Distributions. 5. Introduction. Several specific distributions commonly occur in a variety of business situations:. N. ormal distribution—a continuous distribution . characterized . . and Exponential Distributions. 5. Introduction. Several specific distributions commonly occur in a variety of business situations:. N. ormal distribution—a continuous distribution . characterized . Normal random variables. The Normal distribution is by far the most important and useful probability distribution in statistics, with many applications in economics, engineering, astronomy, medicine, error and variation analysis, etc. The Normal distribution is often called the bell curve, due to its distinctive shape.. ). Let x. i. ~ N(. μ. i. , σ), then the probability density function is defined as. :. Letting: are . independent identical distributed with normal distribution, then the joint distribution of .