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Uniform Distribution definitions

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  • Continuous Random Variable
    Can take any value within a range, represented by a probability density function, with infinitely many possible values.
  • Discrete Random Variable
    Has a set of distinct values, often shown in a table or bar graph, with gaps between possible values.
  • Probability Density Function
    Describes how probability is distributed over a range of values for a continuous random variable.
  • Uniform Distribution
    A distribution where every value within a specified range has the same probability density.
  • Probability
    Represents the likelihood of an event, calculated as area under the curve for continuous variables.
  • Area Under the Curve
    Corresponds to the probability for a continuous random variable within a given interval.
  • Range
    The interval of possible values a random variable can assume, such as between zero and six.
  • Height
    The value of the probability density function at a specific point, constant in uniform distributions.
  • Width
    The length of the interval over which probability is calculated for continuous random variables.
  • Total Probability
    The sum of probabilities for all possible outcomes, always equal to one for any probability distribution.
  • Rectangle
    The shape formed under the probability density function in uniform distributions, used to calculate area.
  • Interval
    A segment of the range, such as between one and three, used to determine probability for continuous variables.
  • Infinite Possibilities
    Characteristic of continuous random variables, where there are uncountably many values within any range.
  • Graph
    Visual representation of probability distributions, with bars for discrete and shaded regions for continuous variables.
  • Table
    Organizes possible values and their probabilities for discrete random variables.