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Explain the concept of discrete variables.
Quantitative variables that can only take whole number values (e.g., number of siblings).
Explain the concept of continuous variables.
Quantitative variables that can take any value within a given range (e.g., height, weight).
Explain the concept of nominal level of measurement.
Categorical data with no inherent order or ranking (e.g., eye color).
Explain the concept of ordinal level of measurement.
Categorical data with a meaningful order or ranking (e.g., customer satisfaction levels).
Explain the concept of interval level of measurement.
Quantitative data where differences are meaningful, but there is no true zero point (e.g., temperature in Celsius).
Explain the concept of ratio level of measurement.
Quantitative data with a meaningful zero point (e.g., height, weight).
What are the differences between categorical and quantitative variables?
Categorical: Attributes/labels, not numbers | Quantitative: Numerical values, can be measured/counted
What are the differences between discrete and continuous variables?
Discrete: Whole numbers only | Continuous: Any value within a range
What are the differences between nominal and ordinal levels of measurement?
Nominal: No inherent order | Ordinal: Meaningful order or ranking
What are the differences between interval and ratio levels of measurement?
Interval: No true zero point | Ratio: Meaningful zero point
What is the definition of 'individual' in statistics?
Objects or people described by a set of data.
What is a 'variable'?
A characteristic that can vary from one individual to another.
What is 'data'?
The values that variables take on.
Define 'distribution' in statistics.
The pattern of variation of a variable.
What are 'categorical variables'?
Variables representing attributes or categories; values are names or labels.
What are 'quantitative variables'?
Variables representing numerical values that can be measured or counted.