FREE IGNOU MCO-03 SOLVED ASSIGNMENT 2023

c) Frequency distribution and Probability distribution

Frequency Distribution: Frequency distribution is a tabular or graphical representation of the number of occurrences (frequency) of each value or category in a dataset. It displays the distribution of data across various intervals or categories and provides insights into the data’s patterns and variability. The key characteristics of frequency distribution are:

1. Categories or Intervals: Data is grouped into distinct categories or intervals (bins) to facilitate analysis.
2. Frequency: The frequency of each category represents the number of data points falling within that category.
3. Continuous Data: Frequency distribution is commonly used for continuous data, where individual data points can take any value within a range.
4. Histogram: A histogram is a graphical representation of a frequency distribution, where the categories are represented on the X-axis and the frequencies on the Y-axis.

Probability Distribution: Probability distribution is a mathematical function that describes the likelihood of each possible outcome in a random experiment. It provides the probabilities associated with different events or outcomes, making it essential in probability theory and statistics. The key characteristics of a probability distribution are:

1. Probability: The probability of each outcome represents the likelihood of that outcome occurring in a random experiment.
2. Total Probability: The sum of the probabilities of all possible outcomes in the distribution equals 1.
3. Discrete or Continuous Data: Probability distributions can be either discrete (e.g., binomial distribution) or continuous (e.g., normal distribution) based on the nature of the data.
4. Probability Density Function (PDF) or Probability Mass Function (PMF): The probability distribution can be represented mathematically as a probability density function (for continuous data) or a probability mass function (for discrete data).