photo.jpg

## Statistics ### Interpretation and Characterization Statistics is the interpretation and characterization of a characteristic of a population or data. ### Classification of Data * **Qualitative data:** Data that is not quantitative like literacy, honesty, or employment. * **Quantitative data:*...

## Statistics ### Interpretation and Characterization Statistics is the interpretation and characterization of a characteristic of a population or data. ### Classification of Data * **Qualitative data:** Data that is not quantitative like literacy, honesty, or employment. * **Quantitative data:** Data that is measured by age, height, weight, income, expenditure, sales, profits, etc. These are classified into continuous and discrete variables: * **Continuous Variable:** Can take all possible values, including decimals. * **Example:** Age, measured in years, months, days, minutes, seconds, etc., can take values like 3 years, 3.5 years, 3.75 years, and so on. * **Discrete Variable:** Can only take specific values, like whole numbers or integers. * **Example:** The number of students in a classroom, the number of accidents on the road, or the number of typing mistakes per page. ### Manifold Attributes Manifold attributes are attributes classified into more than two classes. For example: * **Intelligence:** Genius, Highly Intelligent, Average Intelligent, Below Average, Dull. * **Population:** Male/Female, Smoker/Non-Smoker, Hindu/Non-Hindu.