LH

College Stat Important Symbols

Flashcards

Front: Mu (µ)
Back: "Mu" — represents the population mean (average of the entire population).

Front: X-bar ( XˉXˉ )
Back: "X-bar" — represents the sample mean (average of the sample).

Front: Sigma (σ)
Back: "Sigma" — represents the population standard deviation (spread of data in the population).

Front: S (or Sx)
Back: "S" — represents the sample standard deviation (spread of data in the sample).

Front: P
Back: "P" — represents the population proportion (percentage in the whole population).

Front: P-hat ( P^P^ )
Back: "P-hat" — represents the sample proportion (percentage in the sample).

Types of Variables

When working with data, variables can generally be classified into two main types: quantitative and categorical.

1. Quantitative Variables

  • Represent counts or measurements. They have numerical values for which arithmetic operations (like addition, subtraction, or finding an average) make sense.

  • Examples:

    • Discrete: Can only take on certain numerical values, often whole numbers that result from counting (e.g., number of students in a class, number of cars passing a point).

    • Continuous: Can take on any value within a given range, often results from measuring (e.g., height, weight, temperature, time).

2. Categorical Variables

  • Place individuals into groups or categories. They represent qualities or characteristics and do not have numerical meaning in the sense that arithmetic operations would be sensible.

  • Examples:

    • Nominal: Categories that do not have a natural order (e.g., eye color, marital status, types of fruit).

    • Ordinal: Categories that have a natural, meaningful order or ranking (e.g., education level (High School, Bachelor's, Master's), customer satisfaction (Very Satisfied, Satisfied, Neutral, Dissatisfied)).

How to Distinguish Between Them

To determine if a variable is quantitative or categorical, ask yourself:

  • Does it measure a quantity or a count? If the values are numbers that can be added, averaged, or subtracted meaningfully, it's likely a quantitative variable.

  • Does it describe a quality or a characteristic, placing items into groups? If the values are labels or categories (even if sometimes represented by numbers like zip codes, which cannot be averaged meaningfully), it's a categorical variable.