Terminologies in Statistics

Study Notes

Population: A large collection of objects, persons, places, or things.
Sample: A small portion or part of a population, representing a subgroup or subset.
Parameter: Numerical or nominal characteristics of a population, representing a value obtained from it.
Statistic: An estimate value derived from a sample, used to make inferences about parameters.
Data: Facts or observations collected for analysis.

Qualitative Data: Non-numerical data reflecting attributes or characteristics.
- Examples include favorite colors (e.g., red, blue), cuisine preferences (e.g., Italian), smartphone brands (e.g., Apple), and nationalities (e.g., Filipino).
Quantitative Data: Numerical data obtained from counting or measuring.
- Examples include the number of students (e.g., 30), heights in centimeters (e.g., 175 cm), annual incomes (e.g., $50,000), and daily temperatures (e.g., 25°C).

Discrete Variable: Can assume a finite number of values, measured through counting.
- Examples: Number of cars, number of siblings, number of goals scored in a game.
Continuous Variable: Can take infinite values within a defined range, measured through quantifiable means.
- Examples: Height, weight, temperature, amount of water, and time.

Dependent Variable: Affected by another variable.
- Example: Height of plants influenced by the amount of water given.
Independent Variable: Influences the dependent variable.
- Example: Hours spent studying impacting test scores.

Nominal Scale: The simplest form of measurement for identification.
- Examples: Nationality, gender, blood type.
Ordinal Scale: Data arranged in a specific order or rank.
- Examples: Student rankings, beauty pageant results, shirt sizes.
Interval Scale: Reflects the difference between objects but lacks a true zero.
- Examples: Examination scores, temperature.
Ratio Scale: Similar to interval scale but with an absolute zero point, allowing for meaningful ratios.
- Examples: Weight, height, time, and money.