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- https://math.libretexts.org/Courses/Mission_College/Math_10%3A_Elementary_Statistics_(Sklar)/05%3A_Continuous_Random_Variables/5.00%3A_IntroductionThe graph of a continuous probability distribution is a curve. Probability is represented by area under the curve. The curve is called the probability density function (abbreviated as pdf).
- https://math.libretexts.org/Courses/Coastline_College/Math_C160%3A_Introduction_to_Statistics_(Tran)/06%3A_Continuous_Random_Variables/6.01%3A_IntroductionContinuous random variables have many applications. Baseball batting averages, IQ scores, the length of time a long distance telephone call lasts, the amount of money a person carries, the length of t...Continuous random variables have many applications. Baseball batting averages, IQ scores, the length of time a long distance telephone call lasts, the amount of money a person carries, the length of time a computer chip lasts, and SAT scores are just a few. The field of reliability depends on a variety of continuous random variables. In this chapter and the next, we will study the uniform distribution, the exponential distribution, and the normal distribution.
- https://math.libretexts.org/Courses/Coastline_College/Math_C160%3A_Introduction_to_Statistics_(Lee)/06%3A_Continuous_Random_Variables/6.01%3A_IntroductionContinuous random variables have many applications. Baseball batting averages, IQ scores, the length of time a long distance telephone call lasts, the amount of money a person carries, the length of t...Continuous random variables have many applications. Baseball batting averages, IQ scores, the length of time a long distance telephone call lasts, the amount of money a person carries, the length of time a computer chip lasts, and SAT scores are just a few. The field of reliability depends on a variety of continuous random variables. In this chapter and the next, we will study the uniform distribution, the exponential distribution, and the normal distribution.
- https://math.libretexts.org/Courses/Mission_College/Math_10%3A_Elementary_Statistics_(Hwang)/06%3A_Continuous_Random_Variables/6.01%3A_IntroductionThe graph of a continuous probability distribution is a curve. Probability is represented by area under the curve. The curve is called the probability density function (abbreviated as pdf).
- https://math.libretexts.org/Courses/Mt._San_Jacinto_College/Ideas_of_Mathematics/06%3A_Inferential_Statistics/6.02%3A_Continuous_Random_VariablesThe graph of a continuous probability distribution is a curve. Probability is represented by area under the curve. The curve is called the probability density function (abbreviated as pdf).
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.03%3A_The_Binomial_DistributionSuppose a random experiment has the following characteristics. There are n identical and independent trials of a common procedure. There are exactly two possible outcomes for each trial, one termed ...Suppose a random experiment has the following characteristics. There are n identical and independent trials of a common procedure. There are exactly two possible outcomes for each trial, one termed “success” and the other “failure.” The probability of success on any one trial is the same number p. Then the discrete random variable X that counts the number of successes in the n trials is the binomial random variable with parameters n and p. We also say that X has a binomial distribution
