Probability Theory
June 2004 | 80 pages | Sage US
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Description

Aimed at demystifying probability theory, this text provides a brief and non-technical introduction to the subject. Employing few formulas, Rudas uses intuitive but precise descriptions and examples to explain procedures in probability as a springboard for understanding the concepts of expectation, variance, continuous distributions, normal distribution, chi-squared distribution, and the applications of probability theory in research practice. This book gives researchers and students a solid foundation for understanding probability, and can serve as a supplement in general statistics courses.

Contents

INTRODUCTION

INTRODUCTION

WHERE DO PROBABILITIES COME FROM?

  • DETERMINISTIC AND STOCHASTIC MODELS
  • FREQUENTIST AND OTHER APPROACHES
  • RELATIVE FREQUENCIES
  • EXPERIMENTS WITH INFINITELY MANY OUTCOMES

PROPERTIES OF PROBABILITY

  • BASIC PROPERTIES
  • ADDITIVITY
  • DENSITY FUNCTIONS
  • COUNTABLE ADDITIVITY

PROBABILITY DISTRIBUTIONS AND RANDOM VARIABLES

  • THE DISCRETE CASE
  • THE BINOMIAL DISTRIBUTION
  • THE CONTINUOUS CASE
  • THE NORMAL DISTRIBUTION
  • THE CHI-SQUARED DISTRIBUTION

CONCLUSIONS

CONCLUSIONS

NOTES

NOTES

REFERENCES

REFERENCES

ABOUT THE AUTHOR

ABOUT THE AUTHOR

Description

Aimed at demystifying probability theory, this text provides a brief and non-technical introduction to the subject. Employing few formulas, Rudas uses intuitive but precise descriptions and examples to explain procedures in probability as a springboard for understanding the concepts of expectation, variance, continuous distributions, normal distribution, chi-squared distribution, and the applications of probability theory in research practice. This book gives researchers and students a solid foundation for understanding probability, and can serve as a supplement in general statistics courses.

Contents

INTRODUCTION

INTRODUCTION

WHERE DO PROBABILITIES COME FROM?

  • DETERMINISTIC AND STOCHASTIC MODELS
  • FREQUENTIST AND OTHER APPROACHES
  • RELATIVE FREQUENCIES
  • EXPERIMENTS WITH INFINITELY MANY OUTCOMES

PROPERTIES OF PROBABILITY

  • BASIC PROPERTIES
  • ADDITIVITY
  • DENSITY FUNCTIONS
  • COUNTABLE ADDITIVITY

PROBABILITY DISTRIBUTIONS AND RANDOM VARIABLES

  • THE DISCRETE CASE
  • THE BINOMIAL DISTRIBUTION
  • THE CONTINUOUS CASE
  • THE NORMAL DISTRIBUTION
  • THE CHI-SQUARED DISTRIBUTION

CONCLUSIONS

CONCLUSIONS

NOTES

NOTES

REFERENCES

REFERENCES

ABOUT THE AUTHOR

ABOUT THE AUTHOR

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Probability Theory

A Primer


June 2004 | 80 pages | Sage US

Format Published Date ISBN Price

Aimed at demystifying probability theory, this text provides a brief and non-technical introduction to the subject. Employing few formulas, Rudas uses intuitive but precise descriptions and examples to explain procedures in probability as a springboard for understanding the concepts of expectation, variance, continuous distributions, normal distribution, chi-squared distribution, and the applications of probability theory in research practice. This book gives researchers and students a solid foundation for understanding probability, and can serve as a supplement in general statistics courses.

Table Of Contents:

  • INTRODUCTION
  • WHERE DO PROBABILITIES COME FROM?
  • DETERMINISTIC AND STOCHASTIC MODELS
  • FREQUENTIST AND OTHER APPROACHES
  • RELATIVE FREQUENCIES
  • EXPERIMENTS WITH INFINITELY MANY OUTCOMES
  • PROPERTIES OF PROBABILITY
  • BASIC PROPERTIES
  • ADDITIVITY
  • DENSITY FUNCTIONS
  • COUNTABLE ADDITIVITY
  • PROBABILITY DISTRIBUTIONS AND RANDOM VARIABLES
  • THE DISCRETE CASE
  • THE BINOMIAL DISTRIBUTION
  • THE CONTINUOUS CASE
  • THE NORMAL DISTRIBUTION
  • THE CHI-SQUARED DISTRIBUTION
  • CONCLUSIONS
  • NOTES
  • REFERENCES
  • ABOUT THE AUTHOR

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