Statistical Terminologies
Statistical Terminologies
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In this section, we'll explore the building blocks of statistics. We'll define key terms like population, sample, parameter, and statistic. You'll learn about different types of variables, such as categorical and numerical, and how to classify them as discrete or continuous. Understanding these fundamental concepts is essential for interpreting data and drawing meaningful conclusions.Â
In this section, we'll explore the building blocks of statistics. We'll define key terms like population, sample, parameter, and statistic. You'll learn about different types of variables, such as categorical and numerical, and how to classify them as discrete or continuous. Understanding these fundamental concepts is essential for interpreting data and drawing meaningful conclusions.Â
Statistics: This is the science of collecting, organizing, analyzing, interpreting, and presenting data.
Statistic: A single number calculated from a sample of data. For example, the average height of students in a class is a statistic.
Statisticians: These are people who use statistical methods to analyze data and draw conclusions.
Parameter: A numerical characteristic of a population. For example, the average height of all people in a country is a parameter.
Population: The entire group of individuals or objects being studied.
Sample: A subset of a population selected for study.
Qualitative Data: Data that describes qualities or characteristics. Examples include hair color, favorite food, or country of origin.
Quantitative Data: Data that measures quantities. Examples include height, weight, age, or income.
Discrete Data: Data that can only take on specific values, often whole numbers. Examples include the number of siblings, the number of cars in a parking lot, or the number of correct answers on a test.
Continuous Data: Data that can take on any value within a given range. Examples include height, weight, time, or temperature.
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