Probability Theory Fundamentals
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Questions and Answers

ما هو تعريف الاحتمال؟

  • -result غیر قابل پیش بینی بودن یک evento
  • فرضیه ای که امکان وقوع آن وجود دارد
  • قياس احتمال حدوث حدث ما (correct)
  • مجموع všech نتایج ممکنه ل experimen
  • ما هو.setName() للاحداث المستقلة؟

  • أحداث غير متداخلة
  • أحداث متداخلة
  • حوادث مستقلة (correct)
  • أحداث متساوية
  • ما هو قاعدة الجمع لاحتمال حدوث حدثين؟

  • مجموع احتمالات الحدثين
  • مجموع احتمالات الحدثين ناقص احتمال تلاقيهم (correct)
  • مجموع احتمالات الحدثين مقسوم على احتمال تلاقيهم
  • مجموع احتمالات الحدثين плюس احتمال تلاقيهم
  • ما هو 名称 للاحداث التي تشمل جميع النتائج الممكنة؟

    <p>أحداث شاملة</p> Signup and view all the answers

    ما هو القانون لاحتمال حدوث حدثين مستقلين؟

    <p>積 احتمالات الحدثين</p> Signup and view all the answers

    ما هو الاسم لصيغة تحديث الاحتمال لحدث ما بعد حدوث حدث آخر؟

    <p>مبدأ بايز</p> Signup and view all the answers

    ما هو الفرق بين الاحتمال النظري والاحتمال التجريبي؟

    <p>الاحتمال النظري يعتمد على عدد النتائج الممكنة بينما الاحتمال التجريبي يعتمد على نتائج التجارب المتكررة</p> Signup and view all the answers

    ما هو规則 الجمع لاحتمال حدوث حدثين متداخلين؟

    <p>P(E ∪ F) = P(E) + P(F) - P(E ∩ F)</p> Signup and view all the answers

    ما هو الاسم لصيغة تحديث الاحتمال لحدث ما بعد حدوث حدث آخر؟

    <p>الاحتمال الشرطي</p> Signup and view all the answers

    ما هو النوع من الاحتمال الذي يعتمد على الحكم الشخصي؟

    <p>الاحتمال الشديد</p> Signup and view all the answers

    ما هو规ếu لاحتمال حدوث حدث ما في المجال الاحتمالي؟

    <p>P(E) ≤ 1</p> Signup and view all the answers

    ما هو الفرق بين الحدث والحدث المستقل؟

    <p>الحدث هو مجال الاحتمال بينما الحدث المستقل هو نتيجة أحداث متعددة</p> Signup and view all the answers

    Study Notes

    Basic Concepts

    • Experiment: An action or situation that can produce a set of outcomes.
    • Sample Space: The set of all possible outcomes of an experiment.
    • Event: A subset of the sample space.

    Probability Definition

    • Probability: A measure of the likelihood of an event occurring.
    • Probability Axioms:
      • The probability of an event is a non-negative real number.
      • The probability of the sample space is 1.
      • The probability of the union of disjoint events is the sum of their individual probabilities.

    Types of Events

    • Independent Events: The occurrence of one event does not affect the probability of the other event.
    • Dependent Events: The occurrence of one event affects the probability of the other event.
    • Mutually Exclusive Events: The occurrence of one event implies the non-occurrence of the other event.
    • Exhaustive Events: The events include all possible outcomes of the sample space.

    Probability Rules

    • Addition Rule: The probability of the union of two events is the sum of their individual probabilities minus the probability of their intersection.
    • Multiplication Rule: The probability of the intersection of two independent events is the product of their individual probabilities.

    Conditional Probability

    • Conditional Probability: The probability of an event occurring given that another event has occurred.
    • Bayes' Theorem: A formula for updating the probability of an event based on new information.

    Random Variables

    • Discrete Random Variable: A random variable that can only take on specific, distinct values.
    • Continuous Random Variable: A random variable that can take on any value within a certain range or interval.

    Probability Distributions

    • Bernoulli Distribution: A discrete distribution for binary outcomes (success or failure).
    • Binomial Distribution: A discrete distribution for the number of successes in a fixed number of independent trials.
    • Uniform Distribution: A continuous distribution where every possible value has an equal probability.
    • Normal Distribution: A continuous distribution that is symmetric and bell-shaped.

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    Test your understanding of probability concepts, including experiments, events, probability definition, types of events, probability rules, conditional probability, random variables, and probability distributions.

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