It refers to methods for summarizing and describing the main features of a data set. It helps present data in a simple and understandable way. Some common tools in descriptive statistics

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It goes beyond summarizing the data. It uses sample data to make generalizations or predictions about a larger population.

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a branch of mathematics that deals with the likelihood or chance of different outcomes occurring. It quantifies uncertainty and is used to predict the likelihood of events

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a type of probability that applies to situations where all possible outcomes are equally likely. It is often used in games of chance or experiments with a finite number of equally probable outcomes

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also known as experimental probability, is based on observing actual experiments or past data to estimate the probability of an event. Unlike classical probability, which assumes all outcomes are equally likely, empirical probability is calculated from the frequency of events occurring in practice.

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A type of probability that is based on personal judgment, intuition, experience, or beliefs rather than on empirical data or mathematical calculations. It reflects an individual's confidence in the occurrence of an event, often in the absence of complete data or objective evidence.

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represents the entire group of units which is the fpcu of the study

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The total number of items about which population information is desired

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A subgroup of a universe or a population

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The set of all possible outcomes of an experiment

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total number of sample

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Any procedure that can be infinitely repeated and has a well-defined set of possible outcomes

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a characteristic that is observable or measurable in every unit of the universe or population

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A set of possible values from a random experiment

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refers to data or random variables that take on a finite or countably infinite number of distinct values. These values are usually integers or whole numbers, and they can be listed or counted.

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refers to random variables that can take on any value within a given range, and these values are typically measured rather than counted. Unlike discrete variables, which have distinct, countable outcomes, continuous variables can assume an infinite number of values, often within a specified interval.

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