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Unit 1 Key Terms
Introduction to Statistics Terminology
Term | Definition |
---|---|
Population | All individuals, objects, or measurements whose properties are being studied; example: all students at Herzing University. |
Sample | A subset of the population being studied; example: a random sample of all students at Herzing University. |
Parameter | A number that is a used to represent a characteristic of a population; example: the mean age of all the students in the population. |
Statistic | A numerical characteristic of the sample; example: the mean age of the students. |
Variable | A characteristic that describes a person, place or thing; example: age. |
Data | The actual value of the variable; example: the ages of the students. |
Level of Measurement | A classification of values assigned to variables, includes nominal, ordinal, interval, and ratio scales. |
Nominal Scale | Observations are classified into categories, Examples are gender, ethnicity, and race. |
Ordinal Scale | Observation are classified into ranked categories. Examples are mild, moderate, or severe reactions. |
Interval Scale | Numerical values with a fixed interval. Examples are temperature, and blood pressure. |
Ratio Scale | An interval level value with a true zero. Examples are weight and age. |
Numerical/Quantitative Variable | Data represent characteristics that can be analyzed mathematically; example: the ages of Herzing students. |
Qualitative Variable | Data are usually presented as words or letters; example: the ethnicity of Herzing students. |
Discrete Variable | Discrete variables are whole numbers which can be counted; example: a count of students in the freshman, sophomore, junior, or senior classes. |
Continuous Variable | Continuous variables do not have to be whole numbers, they can have fractions or decimals. Continuous variables are the result of measuring; example: the ages of students in the freshman class. |