Probability Mathematics

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Probability is the measure of the likelihood that an event will occur. Probability is quantified as a number between 0 and 1, where, loosely speaking,0 indicates impossibility and 1 indicates certainty. The higher the probability of an event, the more certain that the event will occur. A simple example is the tossing of a fair (unbiased) coin. Since the coin is fair, the two outcomes ("heads" and "tails") are both equally probable; the probability of "heads" equals the probability of "tails"; and since no other outcomes are possible, the probability of either "heads" or "tails" is 1/2 (which could also be written as 0.5 or 50%).

Probability Mathematics for all level of student’s beginner to advance

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Probability Mathematics covers following topics of Probability Mathematics

PROBABILITY

INTRODUCTION

DETERMINISTIC EXPERIMENT

PROBABILISTIC OR RANDOM EXPERIMENT

CLASSICAL APPROACH TO PROBABILITY

TRIAL AND ELEMENTARY EVENTS

COMPOUND EVENTS

EXHAUSTIC NUMBER OF CASES

MUTUALLY EXCLUSIVE EVENTS

EQUALLY LIKELY EVENTS

FAVOURABLE NUMBER OF CASES

INDEPENDENT EVENTS

CLASSICAL DEFINITION OF PROBABILITY OF AN EVENT

AXIOMATIC APPROACH TO PROBABILITY

SAMPLE SPACEEVENT

ELEMENTARY EVENTS

COMPOUND EVENTS

IMPOSSIBLE AND CERTAIN EVENTS

OCCURRENCE OR HAPPENING OF AN EVENT

MUTUALLY EXCLUSIVE EVENTS

MUTUALLY EXCLUSIVE AND EXHAUSTIVE SYSTEM OF EVENTS

FAVOURABLE EVENTS

AXIOMATIC DEFINITION OF PROBABILITY

ADDITION THEOREMS ON PROBABILITY

CONDITIONAL PROBABILITY

MULTIPLICATION THEOREMS ON PROBABILITY

INDEPENDENT EVENTS

MULTIPLICATON THEOREM FOR INDEPENDENT EVENTS

ADDITION THEOREM FOR INDEPENDENT EVENTS

THE LAW OF TOTAL PROBABILITY BAYE’S RULE

RANDOM VARIABLE AND ITS PROBABILITY DISTRIBUTION

RANDOM VARIABLE BINOMIAL DISTRIBUTION

MEAN AND VARIANCE OF BINOMIAL DISTRIBUTION

MEAN OF BINOMIAL DISTRIBUTION

VARIANCE OF BINOMIAL DISTRIBUTION

RELATION BETWEEN MEAN AND VARIANCE.

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APP FEATURES

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