Probability

What is probability?

History of Probability

Probability has a dual aspect: on the one hand the likelihood of hypotheses given the evidence for them, and on the other hand the behavior of stochastic processes such as the throwing of dice or coins. The study of the former is historically older in, for example, the law of evidence, while the mathematical treatment of dice began with the work of Cardano, Pascal and Fermat between the 16th and 17th century.

Probability is distinguished from statistics. (See history of statistics). While statistics deals with data and inferences from it, (stochastic) probability deals with the stochastic (random) processes which lie behind data or outcomes.

Probable and probability and their cognates in other modern languages derive from medieval learned Latin probabilis and, deriving from Cicero and generally applied to an opinion to mean plausible or generally approved.^[1] The mathematical sense of the term is from 1718. In the 18th century, the term chance was also used in the mathematical sense of "probability" (and probability theory was called Doctrine of Chances). This word is ultimately from Latin cadentia, i.e. "a fall, case". The English adjective likely is of Germanic origin, most likely from Old Norse likligr (Old English had geliclic with the same sense), originally meaning "having the appearance of being strong or able" "having the similar appearance or qualities", with a meaning of "probably" recorded from the late 14th century. Similarly, the derived noun likelihood had a meaning of "similarity, resemblance" but took on a meaning of "probability" from the mid 15th century

Chapter One: Basic of Probability

1.1 Basic Probability

1.2 Set Theory

1.3 Counting Techniques

Chapter Two: Probability

2.1 Classical or Theoretical Probability

2.2 Empirical or Statistical Probability

2.3 Probability of an Event

        1. Permutations

        2. Combination

2.4 Probabilty of Mutually Exclusive Events

2.5 Probability of Independent and Dependent Events

2.6 Conditional Probabilty

Chapter Three: Discrete Probability 

Distribution

3.1 Probabilty Distribution

      1. Random Variable

      2. Distribution Function

      3. Mean, Variance, Standard Deviation and Expected Value

3.2 Binomial Distribution

      1. Binomial Experiment

      2. Formula of Binomial Probability

      3. Mean, Variance and Standard Deviation

      4. The Shape of a Binomial Probability Distribution

Questions of Probability

http://www.mathopolis.com/questions/quiz.php