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Theoretical Distributions - 1 Video Lecture | Crash Course for CA Foundation

FAQs on Theoretical Distributions - 1 Video Lecture - Crash Course for CA Foundation

1. What are the main types of theoretical distributions commonly studied in statistics?

Ans. The main types of theoretical distributions include the Normal distribution, Binomial distribution, Poisson distribution, Exponential distribution, and Uniform distribution. Each of these distributions has unique properties and applications in various fields of study.

2. How is the Normal distribution characterized?

Ans. The Normal distribution is characterized by its bell-shaped curve, which is symmetric around the mean. It is defined by two parameters: the mean (µ) and the standard deviation (σ). Approximately 68% of the data falls within one standard deviation from the mean, 95% within two standard deviations, and 99.7% within three standard deviations.

3. In what scenarios is the Binomial distribution used?

Ans. The Binomial distribution is used in scenarios where there are a fixed number of independent trials, each with two possible outcomes (success or failure). It is particularly applicable in situations like flipping a coin, passing a test, or manufacturing quality control where you want to determine the probability of a certain number of successes in a given number of trials.

4. What is the difference between discrete and continuous theoretical distributions?

Ans. Discrete theoretical distributions, such as the Binomial and Poisson distributions, deal with countable outcomes (e.g., number of successes in trials). Continuous theoretical distributions, like the Normal and Exponential distributions, deal with measurable outcomes that can take any value within a range (e.g., height, weight, time).

5. How can one determine which theoretical distribution to use for a given data set?

Ans. To determine which theoretical distribution to use, one should analyze the nature of the data (discrete vs. continuous), the number of trials or observations, and the outcome characteristics. Statistical tests, such as the Chi-square goodness-of-fit test or visual methods like histograms, can also help in identifying the best-fitting distribution for the data.

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Sep 09, 2025 Last updated

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