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n Data Quality: Inaccurate data can result in deceptive chances.
Complexity: The intricate nature of some probabilistic models may be daunting.
Human Bias: Subjective probability may be skewed by personal biases and perceptions.

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n Discrete Probability Distribution: Deals with discrete random variables, the place outcomes are finite or countable (e.g., rolling a die).
Continuous Probability Distribution: For steady random variables, the place outcomes form a continuum, like measuring heights or inventory costs.
Noteworthy examples embody the Normal Distribution (bell curve) and the Uniform Distribution.

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Embrace the Journey
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