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- https://stats.libretexts.org/Courses/Long_Beach_City_College/Book%3A_STAT_227_-_Introductory_Statistics/Text/04%3A_Discrete_Random_Variables/4.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Courses/City_University_of_New_York/Introductory_Statistics_with_Probability_(CUNY)/05%3A_Discrete_Random_Variables/5.05%3A_The_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/04%3A_Discrete_Random_Variables/4.03%3A_Geometric_DistributionThis page explains the geometric probability distribution, highlighting its focus on trials until the first success, with characteristics like repeated Bernoulli trials. It includes examples such as c...This page explains the geometric probability distribution, highlighting its focus on trials until the first success, with characteristics like repeated Bernoulli trials. It includes examples such as calculating probabilities related to pancreatic cancer, women's literacy rates, a baseball player's batting average, and spotting Dalmatians based on specific criteria.
- https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./03%3A_Distributions_of_Random_Variables/3.03%3A_Geometric_Distribution_(Special_Topic)How long should we expect to flip a coin until it turns up heads? Or how many times should we expect to roll a die until we get a 1? These questions can be answered using the geometric distribution. W...How long should we expect to flip a coin until it turns up heads? Or how many times should we expect to roll a die until we get a 1? These questions can be answered using the geometric distribution. We first formalize each trial - such as a single coin flip or die toss - using the Bernoulli distribution, and then we combine these with our tools from probability to construct the geometric distribution.
- https://stats.libretexts.org/Courses/Coalinga_College/Introduction_to_Statistics_(MATH_025_CID%3A_110)/03%3A_Discrete_Distributions/3.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Courses/Diablo_Valley_College/Math_142%3A_Elementary_Statistics_(Kwai-Ching)/Math_142%3A_Text_(Openstax)/04%3A_Discrete_Random_Variables/4.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Bookshelves/Probability_Theory/Introductory_Probability_(Grinstead_and_Snell)/05%3A_Distributions_and_Densities/5.01%3A_Important_DistributionsIn this chapter, we describe the discrete probability distributions and the continuous probability densities that occur most often in the analysis of experiments. We will also show how one simulates t...In this chapter, we describe the discrete probability distributions and the continuous probability densities that occur most often in the analysis of experiments. We will also show how one simulates these distributions and densities on a computer.
- https://stats.libretexts.org/Courses/Prince_George's_Community_College/MAT1140%3A_Introduction_to_Statistics/03%3A_Discrete_Random_Variables/3.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Courses/El_Camino_College/Introductory_Statistics/04%3A_Discrete_Random_Variables/4.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Courses/Lake_Tahoe_Community_College/MATH-201%3A_Elements_of_Statistics_and_Probability/04%3A_Discrete_Random_Variables/4.05%3A_Geometric_DistributionThere are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials cou...There are three characteristics of a geometric experiment: (1) There are one or more Bernoulli trials with all failures except the last one, which is a success. (2) In theory, the number of trials could go on forever. There must be at least one trial. (3) The probability, p, of a success and the probability, q, of a failure are the same for each trial. In a geometric experiment, define the discrete random variable X as the number of independent trials until the first success.
- https://stats.libretexts.org/Bookshelves/Probability_Theory/Applied_Probability_(Pfeiffer)/07%3A_Distribution_and_Density_Functions/7.01%3A_Distribution_and_Density_FunctionsIf the point \(t\) approaches \(t_0\) from the left, the interval does not include the probability mass at \(t_0\) until \(t\) reaches that value, at which point the amount at or to the left of t incr...If the point \(t\) approaches \(t_0\) from the left, the interval does not include the probability mass at \(t_0\) until \(t\) reaches that value, at which point the amount at or to the left of t increases ("jumps") by amount \(p_0\); on the other hand, if \(t\) approaches \(t_0\) from the right, the interval includes the mass \(p_0\) all the way to and including \(t_0\), but drops immediately as \(t\) moves to the left of \(t_0\).
