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A confidence interval estimator for the shift parameter is found by inverting the CDF of a sufficient statistic for the parameter.
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In this first lesson on interval estimation, we address three methods in the frequentist domain for finding interval estimators. The first is the inversion of a test statistic, the second is using…
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The previous lesson concluded with joint and marginal distributions for the discrete case. We now consider the same concepts, but for continuous random vectors. While discrete random vectors and the…
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The beta distribution is the last continuous distribution we will discuss. Like the gamma distribution, the beta distribution earns its name from being associated with the beta function. The beta…
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In this lesson, we learn about the most important distribution in statistics - the normal distribution. We investigate the probability density function and cumulative distribution function and the…
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The gamma family of distributions is a very special family that has many distributions as a specific case. In this lesson, we begin with the gamma function. We then introduce the gamma…
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An overview of the uniform distribution is given, including its probability density function (PDF) and cumulative distribution function (CDF). The mean, variance, and moment generating function are…
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In this lesson, a brief review of the general properties of continuous distributions is provided. The end of the lesson is a comparison of the properties for continuous and discrete distributions.
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The Poisson distribution is different from all of the discrete distributions we have considered up until this point. Instead of counting the number of "successes" or counting the number of…
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The negative binomial distribution is an extension of the geometric distribution, and so is also related to the Bernoulli distribution. Whereas the geometric distribution results from counting the…
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Like the binomial and hypergeometric distributions, the geometric distribution is related to the Bernoulli(p) distribution. Unlike the binomial and hypergeometric distributions, the geometric…
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The Bernoulli and binomial distributions are used for modeling a dichotomous experiment or a sequence of independent dichotomous experiments, respectively. Alone, both distributions apply to a wide…
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In this lesson, a brief review of the general properties of discrete distributions is provided.
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In this lesson, probability density functions are introduced, defined, and discussed. Properties of probability mass functions and probability density functions are presented. Concepts are…
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This lesson is the first of many that discuss probability functions. We begin the discussion of probability functions with the cumulative distribution function (CDF). The CDF is defined and…
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