M1 - lesson 3

Cards (21)

  • Element or Member
    A specific subject or object (for example, a person, firm, item, state, or country) about which the information is collected
  • Variable
    A characteristic under study that assumes different values for different elements
  • Observation or Measurement
    The value of a variable for an element
  • Data Set
    A collection of observations on one or more variables
  • Quantitative Variable
    A variable that can be measured numerically
  • Discrete Variable

    A variable whose values are countable
  • Continuous Variable

    A variable that can assume any numerical value over a certain interval or intervals
  • Qualitative or Categorical Variable

    A variable that cannot assume a numerical value but can be classified into two or more non-numeric categories
  • Cross-Section Data are data collected on different elements at the same point in time or for the same period of time
  • Time-Series Data are data collected on the same element for the same variable at different points in time or for different periods of time
  • Population
    All subjects (human or otherwise) that are being studied
  • Sample
    A group of subjects selected from a population
  • Statistic
    A characteristic or measure obtained by using the data values from a sample
  • Parameter
    A characteristic or measure obtained by using all data values for a specific population
  • Census
    A survey that includes every member of the population
  • Sample Survey

    A survey that includes only a portion of the population
  • The purpose of conducting a sample survey is to make decisions about the corresponding population
  • Representative Sample
    A sample that represents the characteristics of the population as closely as possible
  • Sampling with Replacement
    Each time an element is selected from the population, it is put back before the next selection
  • Sampling without Replacement
    The selected element is not replaced in the population
  • Data
    are the values (measurements or observations) that the variables can assume.