STATS Module 1

• Statistics


  • Numerical facts
  • Field or discipline of study
• Statistics


  • Science of collecting, analyzing, presenting, and interpreting data
  • Making decisions based on such analyses
• Statistical Methods

  • Descriptive Statistics
  • Inferential Statistics
• Descriptive Statistics


  Methods for organizing, displaying, and describing data by using tables, graphs, and summary measures
• Inferential Statistics


  Utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data

  
• Case Study 1-1: Lobbying Spending by Selected Companies

  • Descriptive statistics

  
• Case Study 1-2: American's Life Outlook 2014

  • Inferential statistics

  
• Such decision making about the population based on sample results is called inferential statistics

  
• Element


  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
• Constant


  A value that is fixed
• Observation or Measurement


  The value of a variable for an element
• Data set


  A collection of observations on one or more variables
• Types of Variables


  • Quantitative Variables
  • Qualitative or Categorical Variables
• Quantitative Variable


  A variable that can be measured numerically
• Quantitative Data


  Data collected on a quantitative variable
• Discrete Variable


  A variable whose values are countable and can assume only certain values with no intermediate values
• 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
• Do you have a Facebook profile? is a categorical (qualitative) variable
• How many text messages have you sent in the past three days? is a numerical (discrete) variable
• How long did the mobile app update take to download? is a numerical (continuous) variable
• Example: Classifying Data


  • Height of a bridge
  • Time to complete a 5K run
  • Letter grade in a class
  • Hours worked in one week
  • Type of pets owned (cat, dog, etc.)
  • Flower varieties planted in a garden
• Height of a bridge, Time to complete a 5K run, Hours worked in one week are numerical variables
• Letter grade in a class, Type of pets owned (cat, dog, etc.), Flower varieties planted in a garden are categorical variables
• Cross-Section Data


  Data collected on different elements at the same point in time or for the same period of time
• Time-Series Data


  Data collected on the same element for the same variable at different points in time or for different periods of time
• Population


  All elements – individuals, items, or objects – whose characteristics are being studied
• Sample


  A portion of the population selected for study
• A survey that includes every member of the population is called a census
• The technique of collecting information from a portion of the population is called a sample survey

  
• 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
• Most samples taken in statistics are without replacement
• Reasons for Sampling


  • Time
  • Cost
  • Impossibility of Conducting a Census
• Types of Samples


  • Random/Probability
  • Non-Random/Non-Probability
• Random Sample


  A sample drawn in such a way that each member of the population has some chance of being selected

  
• Non-Random Sample


  Some members of the population may not have any chance of being selected in the sample
• A random sample is usually a representative sample