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About 64 results
  • https://math.libretexts.org/Bookshelves/Algebra/College_Algebra_1e_(OpenStax)/09%3A_Sequences_Probability_and_Counting_Theory/9.08%3A_Probability
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Courses/Prince_Georges_Community_College/MAT_1350%3A_Precalculus_Part_I/13%3A_Sequences_Probability_and_Counting_Theory/13.07%3A_Probability
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Courses/Chabot_College/Chabot_College_College_Algebra_for_BSTEM/09%3A_Sequences_Probability_and_Counting_Theory/9.07%3A_Probability
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Courses/Mission_College/Math_10%3A_Elementary_Statistics_(Sklar)/01%3A_Sampling_and_Data/1.01%3A_Definitions_of_Statistics_Probability_and_Key_Terms
    The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text.
  • https://math.libretexts.org/Workbench/Book-_Precalculus_I_for_Highline_College_w/Rational_Inequalities_and_Equations_of_Circles/1.11%3A_Sequences_Probability_and_Counting_Theory/1.11.E%3A__Sequences_Probability_and_Counting_Theory_(Exercises)
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Workbench/Algebra_and_Trigonometry_2e_(OpenStax)/13%3A_Sequences_Probability_and_Counting_Theory/13.08%3A_Probability
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Bookshelves/Precalculus/Precalculus_2e_(OpenStax)/11%3A_Sequences_Probability_and_Counting_Theory/11.09%3A_Chapter_Review
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Bookshelves/Algebra/Algebra_and_Trigonometry_1e_(OpenStax)/13%3A_Sequences_Probability_and_Counting_Theory/13.07%3A_Probability
    Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outc...Probability is always a number between 0 and 1, where 0 means an event is impossible and 1 means an event is certain. The probabilities in a probability model must sum to 1. See Example. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in the event by the total number of outcomes in the sample space for the experiment.
  • https://math.libretexts.org/Under_Construction/Purgatory/Remixer_University/Username%3A_Matthew.Lathrop@heartland.edu/test_cb2/2%3A_Sampling_and_Data/2.2%3A_Definitions_of_Statistics%2C_Probability%2C_and_Key_Terms
    The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text.
  • https://math.libretexts.org/Courses/Florida_SouthWestern_State_College/MGF_1131%3A_Mathematics_in_Context__(FSW)/03%3A_Counting_and_Probability/3.06%3A_What_Are_the_Odds
    This section explains how to compute and convert odds and probabilities, particularly in contexts like lotteries and weather predictions. It defines odds in favor and against, illustrating how to expr...This section explains how to compute and convert odds and probabilities, particularly in contexts like lotteries and weather predictions. It defines odds in favor and against, illustrating how to express them as ratios. The formula for calculating the probability from given odds is provided, along with examples and exercises to enhance understanding. The importance of differentiating between odds and probabilities in communication is underscored throughout.
  • https://math.libretexts.org/Courses/Florida_SouthWestern_State_College/MGF_1131%3A_Mathematics_in_Context__(FSW)/03%3A_Counting_and_Probability/3.07%3A_Expected_Value
    This section discusses expected value in the context of random games like roulette, dice, and card games, explaining how to calculate and interpret it through examples. It highlights the negative expe...This section discusses expected value in the context of random games like roulette, dice, and card games, explaining how to calculate and interpret it through examples. It highlights the negative expected value often faced by players in gambling scenarios. Additionally, it covers expected values in life insurance and raffles, emphasizing their financial implications. Historical figures Blaise Pascal and Pierre de Fermat are referenced for their contributions.

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